By Hamilton Mann

In attempting to visualize the issues implicit in the adoption of AI in business, we commonly picture a two-dimensional relationship, such as AI vs productivity or AI vs employment. However, as Hamilton Mann makes clear, getting anywhere near true understanding requires us to consider a whole new axis.

Much of the early debate on artificial intelligence, and GenAI in particular, has borrowed from familiar strategy playbooks, contrasting efficiency against differentiation, automation against augmentation, disruption against continuous improvements. These frameworks, useful in their time, tend to flatten organizational reality into binary trade-offs. They capture broad patterns but leave out the subtleties of how AI actually reshapes firms, workforces, and societies.

In reality, AI is not a flat choice between cutting costs or market expansion. It unfolds across nine distinct strategic pathways, defined not just by growth potential, whether Low, Medium, or High, and by employment impact, whether jobs are Killed, Preserved, or Created, but also by a foundational axis that has long remained implicit: integrity alignment.

Integrity itself spans three states: it can be Damaged, when dignity, autonomy, and resilience are eroded; Compromised, when outcomes remain ambiguous or fragile; or Upheld, when results sustain and elevate human capacity.

By surfacing integrity axis as a structural dimension, this 3×3 framework, elevated into a cube, reveals the paradoxical effects of AI.

In some cases, AI rationalizes organizations into leaner forms, optimizes operations for measurable gains, or displaces workers at scale in pursuit of high growth. These pathways deliver efficiency or expansion on paper, but integrity shows their hidden cost: what appears as progress may in fact be systemic fragility, eroding the human capacity and resilience on which long-term prosperity depends.

In others, AI assists professionals by easing their burdens, enhances workflows through targeted support, or accelerates growth by multiplying human capacity without large-scale displacement. These pathways preserve employment and appear more human-centered, yet integrity reveals their ambiguity: jobs remain, but autonomy and judgment risk narrowing, as machine logic increasingly sets the terms of work.

In another set of logics, AI augments organizations with new expertise, restructures talent flows to unlock latent potential, or empowers entirely new markets and industries. These pathways promise genuine expansion, yet integrity poses the decisive question: are new roles and opportunities elevating human capabilities, or merely subordinating workers to algorithmic dependencies that erode judgment, stifle creativity, and atrophy essential human faculties.

Here, empowerment can mark either the highest alignment of prosperity and dignity, or its most sophisticated illusion.

It raises the stakes for leaders navigating not just efficiency and growth but also resilience, sustainability, and the dual test of social acceptability and humane legitimacy.

Rationalize AI

AI strips out labor to cut costs but fails to unlock new sources of demand. Organizations become leaner, but not stronger. Productivity gains look promising, yet financial performance remains fragile. This is efficiency without prosperity: systemic fragility grows as human capacity shrinks.

This is where the two-dimensional grid fails. Measuring jobs and growth alone suggests a leaner organization, yet the human system underneath becomes weaker. Without an integrity axis, leaders cannot see that rationalization is a false victory: it optimizes away people while corroding the very resilience required for long-term survival.

The case of Ocado:

In early 2025, Ocado, the British online grocery and technology company, announced that it would eliminate around 500 roles in its technology and finance divisions. The decision was not driven by collapsing demand or shrinking operations, but by the increased productivity of engineering teams equipped with AI systems. By automating tasks and streamlining processes, AI had made large portions of human labor redundant. For executives, the move was positioned as a rational step: lower costs, leaner operations, and greater efficiency.

Yet the broader picture reveals why this development exemplifies Rationalize AI. Although sales grew by 14 per cent, Ocado still posted a pre-tax loss of £374.5 million, while its technology sales growth slowed to 10 per cent, down from 18 per cent the year before. In other words, the efficiency gains generated by AI did not translate into sustainable growth or profitability. The company succeeded in cutting jobs and reducing costs, but it did not create new markets, unlock demand, or alter its trajectory of persistent financial losses.

This is the defining paradox of Rationalize AI: by using AI to strip out human labor, companies may succeed in lowering their cost base, but they do not necessarily strengthen their growth engine. Local productivity gains are achieved, but systemic performance remains stagnant or even deteriorates. Rationalize AI delivers leaner organizations, yet it does not deliver prosperity.

This case underscores the risks of mistaking efficiency for progress. In the short term, AI-enabled rationalization may reassure shareholders by showing cost discipline. In the long term, however, it leaves organizations more fragile, with fewer human capabilities to draw on and no new sources of demand to sustain growth. The strategic challenge for leaders is to determine whether they are deploying AI to transform their business or merely to shrink it. The deeper question is whether efficiency that weakens resilience can ever be called progress, or whether it signals an erosion of the very integrity needed for sustainable prosperity.

Optimize AI

AI substitutes for human labor in targeted functions while boosting organizational output. Companies enjoy measurable productivity gains and medium-tier growth. Yet profitability and resilience often remain uncertain, as efficiency masks latent vulnerabilities.

Optimization strips human resilience to the bone, producing brittle organizations addicted to quarterly gains.

As jobs are sacrificed and output improves, integrity shows the void beneath the numbers. Optimization strips human resilience to the bone, producing brittle organizations addicted to quarterly gains. Only the Integrity axis shows why optimization, while rational on paper, undermines the human foundations of sustainable growth.

The case of CrowdStrike:

In 2025, cybersecurity firm CrowdStrike announced a restructuring that revealed the double-edged nature of AI-driven efficiency. The company cut roughly 500 jobs, about 5 percent of its workforce, explicitly citing productivity gains from new AI systems as a key driver. The short-term results were striking: quarterly revenue reached $1 billion, a 25 percent year-over-year increase. Yet the bottom line told a more sobering story, with the company still posting a $92 million loss.

This trajectory illustrates the logic of Optimize AI. Jobs are eliminated, and the organization captures a measurable lift in productivity and revenue. The gains, however, remain fragile. AI delivered cost savings and output growth, but it did not guarantee profitability or long-term stability. Instead, the company now faces the challenge of sustaining performance without eroding the human and organizational capacities that underpin resilience.

This case underscores a pivotal strategic dilemma. AI can indeed optimize operations, but optimization is not the same as transformation. Leaders must decide if they are truly building stronger foundations for growth, or simply hollowing out their organizations in pursuit of short-term gains. Optimize AI highlights the risk of confusing efficiency with prosperity, a path where revenue may rise, but the structural capacity to generate enduring value remains uncertain. The real question is whether optimization strengthens the long-term fabric of the organization, or whether it locks firms into a cycle of fragile gains that sacrifice integrity for speed.

Displace AI

AI replaces labor at scale while fueling new industries, markets, and waves of consumption. Growth is rapid and expansive, but it comes at the cost of dismantling traditional employment structures. The result is high economic expansion coupled with deep social disruption.

This characterizes high-growth success despite job losses. And the integrity axis uncovers its true cost: systemic fragility and social disruption. It ultimately reveals that displacement is not just a trade-off between jobs and growth, but a governance failure that sacrifices resilience for expansion.

The case of Accenture:

By late September 2025, Accenture had laid off more than 11,000 people worldwide as part of an accelerated restructuring. The company described this not as a standard cost cutting program but as a deliberate exit of employees who could not be retrained fast enough for AI centered work. According to the Financial Times, Accenture’s CEO Julie Sweet made the message explicit in a call with analysts: “We are exiting on a compressed timeline people where reskilling, based on our experience, is not a viable path for the skills we need”. She added: “Those we cannot reskill will be exited”.

Accenture referred to this approach as “rapid talent rotation,” a phrase the company uses to describe exiting people quickly when reskilling is not seen as viable.

The severance costs were recorded as part of an $865 million business optimization program. The financial picture tells a story of expansion rather than distress. Quarterly revenue reached $17.6 billion, ahead of the company’s expectations, and full year revenue rose about 7% to roughly $69.7 billion. New bookings climbed above $21.3 billion in the quarter, and Accenture reported $5.9 billion in AI-related bookings over the full fiscal year. The company has nearly doubled its pool of AI and data specialists to 77,000 since 2023, and reported that more than 550,000 employees have already been trained in generative AI.

Here is the paradox: jobs are being destroyed at scale in the name of AI adoption, yet the stated ambition is not downsizing. Accenture has said it expects overall headcount to increase again in the next fiscal year, not shrink, and that savings from layoffs and divestitures will be reinvested into AI capability, new client delivery models, and talent that aligns with the markets the firm aims to lead.

This exposes the structural tension at the core of Displace AI. Accenture is capturing high value AI demand at global scale. It is winning multibillion dollar AI contracts, booking growth, and reinforcing its position as a preferred partner for clients who want to reinvent themselves with intelligent systems. At the very same time, it is rewriting the employment contract inside the firm. Roles are declared obsolete not because the company is failing, but because the company is succeeding in pivoting to AI faster than those workers can be re skilled. The public framing is one of reinvention and opportunity. The lived experience for thousands is forced exit.

The integrity axis reveals why this matters: Can growth that aggressively dismantles established employment structures at such a rapid scale claim to be progress if the social cost is externalized to workers who are no longer considered adaptable enough to remain inside the system? That is not a neutral efficiency decision. It is a societal decision about who is allowed to belong in the future.

This case exemplifies the Displace AI archetype with AI systems replacing human labor at scale, driving rapid business expansion. AI becomes the engine of new value creation and market expansion, revenues rise, bookings surge, investor narratives strengthen, the firm accelerates and society absorbs the shock. The question that integrity forces leaders to confront is whether this definition of success is aligned with the social contract between the firm and its employees, in particular when simultaneously claiming to be an inclusive, merit-based workplace that is free from bias and that seeks to foster a workplace culture based on respect and a sense of belonging. A “Great Place to Work,” so to speak.

Assist AI

AI supports workers rather than replacing them, reducing friction in workflows while keeping employment stable. Professionals still perform their core functions, but with fewer administrative burdens. Growth, however, remains incremental. The system is safeguarded, but not reinvented.

While this situation suggests stability, jobs are preserved and growth remains steady. Yet integrity reveals a subtler erosion. Workers may keep their titles, but their scope for judgment shrinks as AI dictates workflows. Only the Integrity axis makes this visible: jobs preserved, growth neutral, but dignity and autonomy partially lost.

The case of the NHS:

By 2025, NHS England began piloting AI-enabled ambient scribing tools designed to relieve general practitioners of the administrative burden of note-taking during consultations. Instead of manually recording symptoms, histories, and treatment plans, doctors could rely on an ambient AI system that listened, transcribed, and structured the conversation into a draft medical note. The promise was straightforward: give doctors more time with patients by letting AI handle the paperwork.

The early results confirmed that administrative time could indeed be reduced. GPs reported spending less time typing and more time maintaining eye contact, explaining diagnoses, or answering patient questions. But while the pilots improved quality of care and preserved the core role of the clinician, they did not produce new demand, new markets, or systemic economic growth. The number of jobs was not cut, but neither was the workforce significantly expanded. Doctors remained indispensable, and AI became an assistive tool rather than a transformative engine.

This illustrates the logic of Assist AI. Jobs are preserved, workflows are improved, and productivity gains appear locally meaningful. Yet the economic impact remains incremental, not expansive. The value lies in quality and efficiency at the margin, not in the creation of entirely new growth trajectories. Assist AI avoids the social disruption of mass job losses, but it equally avoids the disruptive potential of new industry formation.

This case highlights the double-edged nature of assistance as a strategy. When AI is deployed to support rather than supplant, it strengthens human roles and protects professional expertise. But by stopping short of reinvention, it also caps its growth potential. The strategic tension lies in whether AI is being used to protect the current system or to reshape it. Assist AI succeeds in safeguarding jobs and improving service delivery, but it risks entrenching existing limitations rather than overcoming them. The underlying but critical question is to what extent preserving stability without expanding human scope and perspectives amounts to genuine support, or instead quietly narrows autonomy under the appearance of protection.

Enhance AI

Without an integrity perspective, leaders miss a crucial question: are humans freed, or are they being deskilled by over-reliance on AI?

AI improves human productivity without cutting jobs, enabling smoother workflows and better services. Professionals are freed from repetitive tasks, but growth remains bounded. This path prioritizes human-centered efficiency, producing incremental but meaningful operational benefits.

At first glance, Enhance AI seems safe: jobs protected, workflows improved. Yet without an integrity perspective, leaders miss a crucial question: are humans freed, or are they being deskilled by over-reliance on AI? Integrity allows us to see whether technology extends human capacity or gradually hollows it out.

The case of Delta Air Lines:

From 2023, Delta said it was using AI to quickly make procedures known to reservations agents and to support in pricing which it presented as part of improving the speed and consistency of customer responses. As reported at the time, the airline has been testing AI that queries its internal policy and fare-rule databases in real time to surface the procedure the agent needs for a specific call, while a separate model has been proposing fare adjustments to human revenue managers rather than publishing prices automatically.

Delta has not presented these AI initiatives as a way to replace gate or call-center staff. Instead, it has framed AI as a way to enhance employees’ ability to serve passengers better and consistently, by giving them AI-surfaced information and recommendations.

“I think the initial foray into AI is on the customer service side”, said CEO Ed Bastian, responding to Morgan Stanley analyst Ravi Shankar’s question about the carrier’s use of the technology. “We’re working with our reservations team to try to help our reservations agents parse the historical policies and questions and things that you may you may call into a real agent”. This directly supports the employee-in-the-loop reading.

According to the 2024 Delta Difference report, as the airline rolls out advanced technologies it “takes a balanced approach to AI, using it to improve operations and enhance the customer experience while prioritizing our customers’ and employees’ safety, security and trust”. Delta’s headcount fell sharply in 2020 because of the pandemic, but by 2023–25 it had rebuilt to about 100,000 employees again, according to the company’s own disclosures.

Financially, over 2024–25, Delta reported revenue growth in the mid-single digits and highlighted improved operational performance. In 2024, at its Investor Day on November 20, the company told investors it was targeting mid-single-digit revenue growth as part of its differentiated-and-durable plan. In January 2025, when it released its December-quarter and full-year 2024 results, Delta reported record revenue and described “industry-leading operational performance”, with year-on-year revenue growth in that same mid-single-digit range.

This trajectory captures the essence of Enhance AI.

The gains came from smoother workflows, customers benefits from more responsive service, and incremental productivity increases, not from AI-driven workforce reductions. Yet the fundamental issue beneath the numbers is the tension between employees being truly empowered and their judgment being narrowed by dependence on machine-generated recommendations. The decisive challenge lies in determining whether technology in such cases expands human capability, or instead quietly deskills the workforce by reducing expertise to the execution of AI-suggested choices.

Accelerate AI

AI accelerates organizational growth while retaining and even amplifying human capacity. Firms preserve jobs, invest in their people, and use AI as a multiplier of productivity and innovation. Growth is significant, but it does not require large-scale workforce displacement.

The Jobs and Growth axis already shows this as a favorable case, but the integrity axis makes explicit why: growth is paired with the preservation of autonomy and dignity. With an integrity axis, Accelerate AI is revealed not just as a good strategy but as ethical leadership, proof that inclusion and prosperity can scale together.

The case of Cisco:

In a climate where many of its peers were trimming headcounts amid rising interest in AI, Cisco’s CEO Chuck Robbins offered a striking divergence. In a recent CNBC interview, Robbins emphatically stated, “I don’t want to get rid of a bunch of people right now,” underscoring Cisco’s strategic choice to harness AI as a productivity multiplier, not a vehicle for downsizing.

This decision is deeply resonant: Cisco’s fiscal Q4 results demonstrated significant gains and revenue rose 8 percent to $14.7 billion, buoyed by soaring demand for AI infrastructure. The company reported over $2 billion in AI-related orders, more than double its initial target.

These numbers encapsulate the essence of Accelerate AI: Cisco preserves its engineering workforce, even expanding AI development roles, while leveraging the technology to amplify innovation and performance. Rather than displacing talent, AI consolidates it, fueling growth without sacrificing employment.

This story is instructive in its counter-narrative to the efficiency-first mindset. By embedding AI as an enabling tool rather than a replacement, Cisco shows that scaling growth does not require shrinking human capacity. Accelerate AI asks leaders: can we harness AI to elevate our people and generate growth without sacrificing our workforce? Cisco suggests the answer is yes.

The enduring tension is whether such examples mark the beginning of a broader shift toward inclusive growth, or remain exceptional cases in a landscape still dominated by an exclusive efficiency-driven economy.

Augment AI

AI sparks the creation of adjacent roles—engineers, analysts, content creators—that sustain AI-driven lines of business. Growth is steady but limited. The organization reconfigures around new forms of expertise, but markets are not fundamentally transformed. The grid celebrates job creation here, but without integrity it cannot distinguish between jobs that empower and jobs that serve as a crutch for a temporary peak of demand. An integrity axis forces us to ask: do these new roles build enduring capabilities and pathways for human expertise, or do they merely anchor workers to the support of keeping the system running relative to short-term financial performance? Growth alone cannot answer that.

The case of Anthropic:

In 2025, the maker of the Claude AI model announced that it would create more than 100 new jobs across Europe, expanding in cities such as Dublin and London. These roles spanned engineering, research, sales, and business operations, and were positioned as additive hires to sustain the company’s rapid growth in AI services. Unlike rivals that leaned on layoffs or hiring freezes, Anthropic emphasized net job creation as it sought to build out the infrastructure and talent required to compete in a global AI market.

Yet this expansion came with a striking paradox. Even as Anthropic added new categories of expertise orbiting its core AI business, its CEO, Dario Amodei, warned publicly that AI could displace vast numbers of jobs, particularly in routine knowledge work. His remarks, widely reported and countered by NVIDIA’s Jensen Huang, underscored the tension between firm-level augmentation and system-wide disruption.

Financially, Anthropic’s growth was steady rather than transformative. Revenue gains reflected increasing adoption of Claude and its enterprise offerings, but they remained bounded within the competitive dynamics of the AI sector. The hiring drive demonstrated the emergence of new roles linked to the deployment dynamic of AI, but it did not reinvent markets or trigger exponential new demand.

This trajectory reflects the essence of Augment AI. Jobs were created in meaningful numbers, sustaining the company’s evolving ecosystem, but the growth remained incremental. Anthropic layered AI-focused roles onto its business model, turning technology into a catalyst for adjacent expertise rather than systemic reinvention.

This case also illustrates the inherent ambiguity of augmentation. The uncertainty lies less in the existence of new roles than in the conjunctural and opportunistic conditions under which they are created. When augmentation is driven primarily by short-term market demand, it remains fragile, vulnerable to fluctuation, and easily discarded if competitive pressures shift. Without anchoring in structural change, these roles risk becoming temporary adaptations rather than durable transformations.

Augment AI forces leaders to ask not only whether they are creating roles to meet momentum, but also whether those roles are a structural part of a new core system to sustain long-term growth or a fix to immediate competitiveness. The former is true augmentation. The latter is conjunctural augmentation and risks feeding into a broader tide of displacement.

Restructure AI

AI restructures organizations by enabling new internal pathways for talent and skills. Employees transition into new roles as firms align human capital with emerging technological needs. Growth emerges from within, not through market disruption, as companies unlock latent potential in their workforce.

While this place highlights job creation and moderate growth, its real value only emerges with an integrity perspective: Restructure AI sustains dignity by enabling reskilling and mobility, showing that technology can evolve with workers rather than against them. This distinguishes between cosmetic job churn and genuine empowerment.

The case of Walmart:

In 2025, Walmart launched a large-scale reskilling program that leveraged AI to transform how frontline employees navigated careers within the company. Rather than relying on automation to reduce headcount, Walmart invested in AI-driven career pathways that helped workers transition into emerging roles such as drone technicians, robotics supervisors, and technical support specialists. AI systems were deployed to analyze skills, identify adjacencies, and recommend reskilling journeys tailored to employees’ backgrounds.

The results have been striking. More than 50,000 cashier roles have been restructured into new, future-oriented positions, while thousands of other associates have accessed new learning opportunities and internal career moves. For individuals, the change has been transformative: one cashier, for example, retrained as a robotics supervisor after receiving a personalized AI recommendation and structured learning guidance. For Walmart, the benefits have been equally significant: internal talent redeployment has reduced turnover costs, enhanced operational resilience, and ensured that the company’s workforce evolves in step with its increasingly automated supply chains and stores.

This is a textbook case of Restructure AI. Jobs are not only preserved but actively created through the restructuring of organizational processes, while business growth is tangible even though moderate. Walmart has unlocked the value of human capital already inside the company, redirecting it toward the capabilities most needed in an AI-driven economy, while pairing this approach with a set of AI-enabled initiatives. Together, and building on this restructuring approach, Walmart has delivered measurable results: digital sales rose 25 percent year over year. Yet these gains, while tangible, have not led to radical expansion into new markets.

The core lesson here is that AI can act as a mechanism of organizational redesign rather than mere automation. By turning internal mobility into a dynamic, AI-enabled process, Walmart demonstrates how companies can avoid the false trade-off between efficiency and employment. Growth in such scenarios does not come from cutting costs or conquering new industries, but from reimagining the structure of work itself. The overarching challenge is whether such restructuring consistently elevates human flourishing, fulfillment and autonomy, or whether it risks being reduced to a managed rotation of labor that serves organizational needs more than individual growth.

Empower AI

AI unlocks entirely new markets and business models, creating jobs and scaling growth dramatically. This is AI at its most expansive: empowering individuals and industries, redefining access and opportunity. Yet it also destabilizes incumbents who rely on sustaining strategies, forcing leaders to adapt or be left behind.

While this scenario is the most celebrated, the integrity axis reminds us that not all empowerment is equal. Are new jobs designed to elevate autonomy, or do they risk locking humans into algorithmic dependence? Integrity is what distinguishes empowerment from manipulation.

The case of Duolingo:

By late 2024, Duolingo had become the most downloaded education app in the world, boasting more than 100 million monthly active users and 8 million paid subscribers, underpinned by AI-driven personalization, gamification, and adaptive learning mechanisms. This meteoric rise exemplifies Empower AI: new markets are unlocked, jobs are created, and growth is expansive.

Behind the numbers lies a broader employment story. As Duolingo scaled, its business growth materialized in tangible investments in human capability, hiring educational designers, community outreach specialists, AI content creators, and engineers to extend the platform beyond language instruction into new areas like music and mathematics. These roles were born not from administrative routines, but from the need to develop and expand Duolingo’s AI-driven learning ecosystem.

The strategic impact is profound. Duolingo did not merely displace labor with automation. Instead, it used AI to empower a new generation of workers, elevating the nature of jobs in education technology while creating value that extended beyond traditional markets. Duolingo has turned AI into a lever for inclusion, learning accessibility, and continuous expansion, starkly illustrating the promise of Empower AI.

This case challenges the belief that AI inherently streamlines or replaces work. For Duolingo, AI did neither. Instead, it sparked a wave of job creation and market expansion. Empower AI forces leaders to consider whether technology should be a tool of displacement or a gateway to human-centered growth. The defining question is whether such empowerment truly expands human agency and creativity, or whether it risks entrenching new forms of algorithmic dependence that erode the very integrity it claims to uphold.

Navigating the Nine Logics of AI

Leaders are not simply choosing between short-term productivity gains and long-term growth outcomes, or attempting to balance both, through AI. They are navigating nine distinct logics of AI deployment, each with its own promise and peril, hinging on integrity being damaged, compromised, or upheld.

As with any framework, it would be vain to expect organizations to sit entirely within a single logic. In practice, companies often run several AI deployments in parallel, embodying multiple logics at once. Besides, none of the embraced logics unfold in a vacuum; regulatory regimes, investor pressures, and labor market dynamics strongly influence which logics become viable.

Yet even within such systemic constraints, executives retain decisive agency in steering how AI is deployed.

AI deployment is not just a technological decision. It is a societal decision.

The nine archetypes of AI deployment remind us that technology is never neutral. Rather than framing a strict categorization, each pathway, whether rationalizing costs, optimizing operations, displacing labor, assisting activities and workflows, enhancing capacity, accelerating economic growth, augmenting expertise, restructuring organizations, or empowering human capital, offers guidance for strategic choice and brings the paradoxes to light. AI is celebrated as a driver of efficiency and growth, yet its impact is fractured across competing logics. Some strategies strip out human labor while leaving organizational fragility intact. Others preserve or create jobs but cap their growth potential. And a select few unleash expansive new markets while forcing difficult questions about resilience, equity, and sustainability. Integrity alignment turns this paradox into a sharper diagnosis: fragility arises where integrity is low, stagnation where integrity is partial, and sustainable empowerment only where integrity is high.

In essence, AI deployment is not just a technological decision. It is a societal decision. Whether organizations end up leaner or stronger, stagnant or expansive, exclusionary or empowering depends less on the capabilities of the technology than on the intentions of those who wield it. Their integrity makes this explicit, transforming abstract intentions into measurable questions of whether AI sustains or undermines human autonomy.

For executives, the challenge is to resist the seduction of efficiency alone. Rationalization and optimization may satisfy shareholders in the short term, but without a parallel commitment to empowerment and human development, they risk hollowing out the very foundations of long-term growth. Conversely, paths that invest in people and preserve resilience, assistive, augmentative, restructuring, or empowering logics require patience and strategic courage, but they promise outcomes that align profitability with legitimacy and social acceptability. Navigating these challenges with integrity alignment helps identify which paths truly strengthen both prosperity and legitimacy, and which merely defer systemic fragility under the illusion of efficiency.

This is why Artificial Integrity, rather than the limitation to mere mimicry of human cognition, must guide AI development and implementation to resist the assignment of being driven solely by raw performance, blind to ethical, social, and moral considerations. Exhibiting Integrity, not just intelligence, is the next frontier for AI, making it an intrinsic part of its functioning and aligning it with human values, to support the right path toward fostering approaches that reconcile human growth (jobs preserved or created), business growth, and integrity alignment.

Yet even with the prospect of such development, navigating the nine logics of AI deployment ultimately places the responsibility on executives, who must decide whether they are building organizations that grow only by shedding their human core, or cultivating ones resilient enough to expand by empowering. The answer will define not just the next generation of business leadership, but the social contract between organizations and the societies whose prosperity and work they reshape. Integrity will determine whether that contract is written on fragile ground or on a foundation capable of enduring, with AI.

About the Author

Hamilton Mann is an AI researcher and bestselling author of Artificial Integrity (Wiley). He  lectures at INSEAD and HEC Paris, and has been inducted into the Thinkers50 Radar.

The post Nine Logics of AI Deployments and the Artificial Integrity Imperative appeared first on The European Business Review.

The region boasts a proven track record of attracting foreign direct investment (FDI) and is fast becoming a top location for businesses seeking to diversify their international operations and explore opportunities in new markets.

Invest Northern Ireland, the economic development agency for the region, is a trusted business partner for international companies working alongside them to explore the advantages Northern Ireland offers and supporting them to set up operations in the region.

Last year, with support from Invest Northern Ireland, 19 new international companies decided to invest. These companies were across the digital and creative technologies, financial, professional and business services and advanced manufacturing and engineering sectors and from countries including Canada, United States (US), Great Britain (GB), Ireland, Germany, Cayman Islands and India.

Renowned as a fantastic place to live, work, and do business, Northern Ireland offers international businesses highly skilled talent, excellent infrastructure, competitive costs, and a supportive, business-friendly environment.

From its connectivity to its world-leading industries, here are the top five reasons why Northern Ireland is an ideal place for international businesses seeking to grow and innovate.

1. A unique and integrated location

Situated between Europe and the US, Northern Ireland offers easy access to global markets.

What sets Northern Ireland apart from other locations as a prime investment location is its unique dual market access to GB and all 27 European Union (EU) member countries.

Dual market access allows manufacturing businesses in Northern Ireland to trade goods freely with both GB and the EU, providing access to a market worth over £6 trillion. This unique position means goods move from Northern Ireland to GB and the EU without customs checks or tariffs, giving businesses selling from Northern Ireland a competitive advantage in accessing both these markets.

Moreover, Northern Ireland maintains regulatory alignment with the EU on goods and remains in the UK Customs Territory. This means Northern Ireland-based businesses can access UK trade agreements, such as those recently concluded with Australia, New Zealand, India, and the US.

The 10% reciprocal tariff for most UK exports to the US, alongside zero tariffs on aircraft parts, applies to companies based in Northern Ireland.

On average, operating costs are around 40-50% lower than in other parts of Western Europe.

In terms of wider connectivity, Northern Ireland has a great communications infrastructure. It has a digital, fully fibre-optic communications network and was the first region in Europe to achieve 100% broadband coverage. Government and industry in Northern Ireland are working collaboratively to ensure that 5G mobile connectivity is world leading to help drive economic growth and attract investment.

The region is served by four ports and three airports that accommodate nearly seven million passengers per year, and the capital city, Belfast, is less than two hours by road or rail from Dublin.

To complement its connectivity and unique dual market access, Northern Ireland also boasts a business-friendly environment with competitive operating costs.

On average, operating costs are around 40-50% lower than in other parts of Western Europe. Additionally, R&D expenditure credit allows businesses to claim 20% tax relief, and there is a corporation tax rate of 25%, the lowest in the G7. Businesses can also take advantage of a 10% lower corporation tax on profits from patented inventions.

2. Skilled talent and educated people

Northern Ireland is home to a young, well-educated, highly skilled, English-speaking workforce, supported by a first-class education system.

It is one of Europe’s youngest and fastest-growing populations, with 50% of people under the age of 40.

The region also has the highest university degree completion rate in the UK, thanks to two world-class universities and a network of regional colleges.

Queen’s University Belfast is over 175 years old and a member of the prestigious Russell Group, with 99% of its research environment world-leading or internationally excellent.

Ulster University has four campuses across Northern Ireland and was recently awarded ‘University of the Year 2024’ by Times Higher Education, recognising it as the leading higher education institution in the UK and Ireland. It ranks in the top 10% of UK universities for research impact.

Both universities are internationally recognised for their high-quality, research-led education, with an emphasis on innovation and entrepreneurship. They have a long history of collaborating with international and Northern Ireland businesses on research projects and of producing graduates equipped with skills, competence, and insight in business-relevant areas.

What’s more, there are close links between government, industry and academia to ensure the workforce is equipped with the skills that local businesses and investors need.

The Assured Skills Programme is a fully funded, pre-employment training programme that guarantees incoming companies can secure the right talent with the right skill sets. It incorporates input from participating companies and collaborates with Northern Ireland’s colleges, so that newly arriving operations can hit the ground running. The Programme has helped companies recruit employees in specialist areas such as software development, data analytics, cybersecurity, and financial services.

3. Specialist key sectors and leading industries

Northern Ireland has a global reputation for excellence in a range of key sectors, including technology, financial services, artificial intelligence, aerospace, and life and health sciences.

Northern Ireland is set to become the UK’s next ‘Silicon Valley’ – according to technology giant Samsung. The region has emerged as a technology leader, particularly in fields such as fintech, cybersecurity, and software development.

Northern Ireland has consistently ranked among the top destinations worldwide for fintech inward investment projects and is the top European investment location for US cybersecurity firms. Global corporations like Allstate and Citi who both invested in the region, and Northern Ireland companies such as FinTrU have helped catapult the region into becoming one of the world’s largest FinTech investment locations.

Northern Ireland has consistently ranked among the top destinations worldwide for fintech inward investment projects and is the top European investment location for US cybersecurity firms.

Bank of America recently announced its intention to establish its first-ever operation in Northern Ireland, with plans to create up to 1,000 new jobs. Allstate Northern Ireland also announced a £16m investment in skills to upskill or reskill their employees in AI, cybersecurity, and cloud computing. These significant investments highlight Northern Ireland’s reputation in global financial services and as a location for high-value, skilled employment.

But it’s not just Northern Ireland’s sectoral talent that is securing investment – crucial investment is being made in research and development too.

Northern Ireland’s cybersecurity and AI sectors are supported by research centres that are partnering with industry leaders. For example, digital technology company Kainos is investing £10m in the advancement and scaling of Generative AI by partnering with Ulster University’s AI Research Centre.

The Artificial Intelligence Collaboration Centre (AICC) is a £16m project led by Ulster University in partnership with Queen’s University, which supports technology diffusion to industry and training. It is designed to support industries, including manufacturing, legal, life sciences and creative technologies sectors, among others, who might otherwise be slow to adopt AI.

The region is also leading the way in financial services. It can provide international financial services solutions such as fund administration, investment operations, regulatory compliance, and risk management in support of global capital markets, asset management, and banking industries. All the ‘big four’ accountancy firms (Deloitte, PwC, EY and KPMG) have a presence in Northern Ireland, making it a well-known global financial services hub.

As for aerospace, defence and security, Northern Ireland’s industry generates £2.2bn in annual revenues and employs around 9,000 people. The aerospace sector is home to many international companies, including Collins Aerospace, Airbus, Embraer, and GKN Aerospace. Within the next decade, thrusters manufactured by Thales Alenia Space in Northern Ireland will be taking cargo to the moon.

Another surging industry is the life and health sciences sector. It has a vibrant cluster of over 250 businesses, international investors, and indigenous companies, exporting globally to over 140 countries. Northern Ireland has particular expertise in precision medicine, diagnostics, medtech, pharma, and biotech, underpinned by a skilled workforce of nearly 20,000 people.

Northern Ireland homegrown but global pharma and biotech companies such as Almac Group, Randox, Norbrook, operate alongside international companies such as TEVA and Terumo. Northern Ireland company CIGA Healthcare, a global leader in professional diagnostic tests, has recently landed two lucrative contracts with Walmart Marketplace and Austria DM valued at £1.4m.

4. A culture of innovation and investment in research and development

Northern Ireland has a celebrated history of innovation. From the pneumatic tyre to the portable defibrillator, the region has a reputation for impactful inventions.

Innovation is only set to grow in the coming years. Northern Ireland is benefitting from an investment package of £1.3bn from four City and Growth Deals. These significant deals will help strengthen the region’s expertise in key sectors.

The investments from the City and Growth Deals will create centres of excellence and leading-edge facilities, along with thousands of new jobs. They will stimulate a culture of innovation, which will allow Northern Ireland to compete globally and be seen as a leader in areas such as drug discovery, environmental sustainability, data analytics, and other transformational technologies.

Innovation can’t happen in isolation, and that’s why Northern Ireland curates a collaborative ecosystem to bring together government, industry, and academia to work together on major investments in infrastructure.

One such example is the UK Digital Twin Centre based in Belfast, a project expected to drive the next wave of industrial transformation by boosting digital twin technology. It is projected to deliver £62m in GVA for the economy over the next decade.

Innovation is only set to grow in the coming years. Northern Ireland is benefitting from an investment package of £1.3bn from four City and Growth Deals.

The strength of Northern Ireland’s commitment to R&D can be seen in the frequency of FDI companies re-investing in the region. The US mass-capacity storage technology firm, Seagate, established operations in Derry-Londonderry in 1993, and has become a world-class manufacturing facility and one of the area’s largest employers. Recently, Seagate announced a £115m investment over five years in the development of new hard drive technology.

5. Tailored investment support, guidance, and advice

For those companies seeking to expand their operations outside their home markets, Invest Northern Ireland provides comprehensive support pre, during and post investment. Financial and advisory support offered ranges across all aspects of business operations, from increasing productivity and efficiency to improving skills, developing products and services, and finding new markets.

Invest Northern Ireland has a global office network with professional investment teams who work with potential investors to explore what Northern Ireland can offer.  Support includes organising visits, introducing companies to existing investors and wider industry and academia networks, and helping find suitable premises.

As a location, Northern Ireland has exactly what businesses are looking for – a workforce that is educated, innovative, resilient, and results-driven. People who will go the extra mile to make sure your expansion and operation is a success. Combine this with a superb infrastructure, competitive costs, and excellent support packages, and Northern Ireland is the ideal location to grow your business.

Find out more about what Northern Ireland can offer your business by contacting investorenquiry@investni.com or visit https://www.investni.com/international-business/invest-in-northern-ireland.

The post Five Reasons Why Northern Ireland is a Magnet for International Businesses appeared first on The European Business Review.

By Georgie Fienberg and Tzuki Stewart

Is everyone clear on why we’re devoting serious person-hours to this meeting? Before we just have our regular quick run round the room, let’s stay seated for some sorely needed focus from Georgie Fienberg and Tzuki Stewart.

We spend hours in them. We complain about them. We book them out of habit. But when we ask many teams what a particular meeting is for, we’ll often get a shrug.

So many meetings I sit in start the same way: someone quietly flicks through the calendar, and then asks the question, “Do I really need to be in this one?” And that’s the trap. We’ve forgotten that meetings aren’t calendar furniture or corporate theatre; they’re the modern echo of humanity’s most successful survival strategy. For millions of years, our species thrived because we could do something our competitors couldn’t: while chimpanzees relied on brute force and basic tools, humans won through superior social organisation. The ability to mobilise resources – to align, decide, and act together – wasn’t just an advantage, it was existential. Groups that coordinated better literally overran those that didn’t.

Yet we’ve turned this evolutionary superpower into background noise. We treat the Monday huddle the same way we treat the boardroom pitch. The corridor chat carries more weight than the strategy session. We’ve lost sight of the fact that in a competitive landscape, the organisations that coordinate best still win – and those that don’t get overrun by rivals who do.

When you run a meeting with clarity and intent, it’s one of the best tools you’ve got.

Most meetings are well-intended; they’re just badly designed. We focus on form over function. We forget to define a crystal-clear purpose, and we wonder why nothing quite moves.

But when you run a meeting with clarity and intent, it’s one of the best tools you’ve got, tapping into the collaborative intelligence that made us human.

This is how to make every meeting work harder. Not by adding more structure – by adding more purpose.

The Monday Huddle

You meant for it to be a quick, energising start to the week. But somewhere between “Let’s just go round quickly” and “Sorry, can you repeat that? You froze,” the Monday huddle turned into a sluggish cycle of calendar commentary. People reel off what’s in their diary like they’re auditioning for a productivity podcast.

No one’s really listening, someone’s definitely writing an email, and the most useful thing to come out of it is the reminder that Barry is still on mute. The pace is off, energy is flat, and no one leaves feeling clearer, just … slightly later to start their real work. And yet, done right, this five-minute check-in could be a game-changer. It’s not the meeting itself that’s the problem, it’s what we’re asking it to do.

• Purpose: Align the team, share priorities, surface blockers.
• How consequential is it? Low stakes, high rhythm-setting.
• Done well: Focused, fast, energising. People leave feeling a part of something, and informed and supported.
• Goes wrong when: It becomes a round-the-houses status update with no edge.
• Leader’s role: Set the pace. Model brevity and clarity. Keep the focus on priorities,
  not updates.

Make it work:

1. Don’t do together what you can do apart; share updates ahead of the meeting.
2. Start with direction, not detail. Don’t let it drift into calendar theatre. Anchor on what matters most this week, for each person and for the team.
3. Use three smart prompts:

• • Priorities: What are your top 1–2 priorities
    this week that others need to know about?
  • Challenges: What’s in your way? What boulders do you need moved?
  • Support: Where do you need input, intros, backing, or space?

4. Keep it crisp. If it’s just an update, share it in writing. Time together should shift energy, not just share information.

The Town Hall (or AGM)

There’s a particular facial expression people wear at town halls. Polite. Alert-ish. Slightly braced. You see, they’ve learned that this is usually 40 minutes of scripted optimism, vague slides, and phrases like “strategic realignment” which basically mean “brace yourselves”. Leadership mean well; they want to inspire, to connect, to reassure.

But when the Q&A is curated and the tone feels more broadcast than dialogue, people tune out. They nod. They clap. They text each other under the table. Town halls are the poster child for monologue misfires. People want clarity, not spin, and engagement isn’t won through polish, but through honesty. When these meetings work, they’re electric. When they don’t, they quietly drain belief.

• Purpose: Communicate strategy, build confidence, show direction.
• How consequential is it? High visibility, reputation-shaping.
• Done well: Clear, confident, human. People leave feeling proud and informed.
• Goes wrong when: Over-scripted. Over-polished. Under-trusted.
• Leader’s role: Be the one who says the hard thing first. Set the tone by being real, not rehearsed.

Make it work:

1. Lead with clarity, not choreography. People don’t need a show. They need to understand what’s changing, why it matters, and what it means for them.
2. Say the hard thing first. Don’t save the tension for the Q&A or bury it in slide 37. Naming the discomfort early earns trust, and attention.
3. Open the floor properly. Pre-vetted questions are safe but sterile. If you want real engagement, create psychological safety for honest dialogue, and don’t flinch when it comes.

The Brainstorm

There’s usually Post-its. Sometimes snacks. Always someone saying, “No idea is a bad idea,” while secretly judging them all. The brainstorm starts with a flurry, energy, coloured pens, whiteboards, maybe even jazz music. But then … the same few people dominate. The quiet ones stay quiet. Wild ideas fly, but they rarely land. And a week later, no one remembers what got decided, because nothing did. Everyone had fun, sort of. But did anything actually happen? Hard to say. There was a lot of drawing.

• Purpose: Generate ideas, shape early thinking.
• How consequential is it? Medium – it can unlock creativity or waste an hour.
• Done well: Structured looseness. Energy. Follow-through.
• Goes wrong when: It’s hijacked by louder voices. Or nothing happens after.
• Leader’s role: Frame the problem well, then step back. Make space for the thinkers, not just the talkers.

Make it work:

1. Define the problem like a strategist. A good brainstorm starts with a great question. Not “What are your ideas?” but “What’s the real problem we’re solving, and why now?”
2. Start in silence. Give people five quiet minutes to think and write before anyone speaks. This evens out the airtime and surfaces better ideas.
3. Use roles, not just voices. For example, assign a challenger (to stress-test), a builder (to develop others’ ideas), and a closer (to call time and decide). Structure drives outcomes.

The Accidental Meeting (watercooler chats, hallway run-ins, drinks after work …)

What you say in the corridor should match what you say in the room.

It happens in the lift. In the coffee queue. On a walk between buildings. Someone leans in and says, “Just so you know …” And suddenly, you’re in it, a real conversation, with real consequences, that no one else even knows occurred. No notes. No record. But definite impact. These moments can be gold: quick intel, connection, context. But they can also be chaos. Because what was said informally gets treated as a decision and, next thing you know, someone’s being looped in on something they didn’t even know was looped out.

• Purpose: Connection, intel, soft influence.
• How consequential is it? High – social capital is built here.
• Done well: Natural, intentional, respectful.
• Goes wrong when: Boundaries blur or signals are misread.
• Leader’s role: Stay consistent. What you say in the corridor should match what you say in the room.

Make it work:

1. Treat the informal moments like they matter, because they do. Corridor chats often reveal what structured meetings don’t. When you genuinely listen and engage, these moments become gold. When you use them to posture or politic, people clock it fast.
2. Be the same person in every room. If you’re open and engaged in the corridor but closed off in the boardroom, people won’t trust either version. Consistency builds credibility.
3. Don’t let soft power become side deals. If something gets agreed informally, bring it into the light. Loop others in. Good leaders close the gap between what’s said privately and what’s done publicly.

The Go / No Go Decision Meeting

It says “Decision” in the invite, which already feels suspicious. There’s a lot of background. A lot of context. A lot of “Just to play devil’s advocate …” But not much deciding. The group talks. Circles. Parks the issue. Someone suggests a working group. Everyone agrees … to talk more later. The real problem? We never agreed what we were deciding in the first place. We just hoped the clarity would reveal itself mid-meeting. It didn’t. And now we need another meeting to sort out what this one didn’t.

• Purpose: Make a choice and move forward.
• How consequential is it? High – it can shape strategy, spend, or team direction.
• Done well: Decisive, inclusive, crisp.
• Goes wrong when: The decision is already made. Or never gets made.
• Leader’s role: Get crystal clear on the “what”, “who”, and “how” before the meeting starts. Then hold the line.

Make it work:

1. Name the decision before the meeting starts. Don’t wait for it to emerge mid-discussion. Write it down. Frame it clearly. If you can’t define it, you’re not ready to meet.
2. Be clear on who decides, and who advises. Not everyone in the room needs a vote, but everyone deserves a voice. Confusion here is what kills momentum.
3. Set decision criteria in advance. What matters most: speed, cost, impact? Without shared criteria, the loudest opinion usually wins.
4. Make closure non-negotiable. Good meetings don’t end in “Let’s revisit.” They end in alignment: what we’re doing, why, and who’s accountable.

The Client Meeting

You’ve assembled the team. You’ve polished the creds. You’ve agonised over which case study to include and who gets to speak when. The meeting kicks off. You launch in, passionately, professionally, about your offering, your track record, your differentiators. Twenty minutes later, the client is nodding politely but hasn’t said much. When they do speak, it’s clear they’re solving a different problem than the one you thought you were here to discuss. You realise too late: you were focused on what you wanted them to know, not what they needed to hear.

• Purpose: Build trust, open the door, explore what matters to them.
• How consequential is it? High – this is where reputations are made and missed.
• Done well: Curious, relevant, two-way. The client leaves feeling heard and intrigued.
• Goes wrong when: You’re speaking your language, not theirs. Answering questions
  they never asked.
• Leader’s role: Make it about them. Read the room. Ask sharper questions. Hold back your brilliance until it’s actually relevant.

Make it work:

1. Start with their world. What are they dealing with? What are they trying to fix? If you can’t answer that, don’t open your laptop.
2. Tailor, don’t tour. Ditch the generic intro slides. Show them you’ve thought about them, not just copied in your usual deck.
3. Find the real problem. Often what they say they want isn’t what they actually need. Ask the next question.
4. Close with clarity. What did we learn? What’s the next step? Who’s doing what? Leave with momentum, not just a smile.

The Drop-in Meeting

You’ve been invited, along with 200 others, to a “drop-in session” about a new organisation-wide programme. It’s positioned as a chance to ask questions, but what it really is … is a cascade. The PowerPoint is long. The language is vague. And every time someone asks a real-world question, “How will this affect our business unit?”, the hosts smile kindly and say, “We’re working through the details.” The meeting ends with a thanks-for-your-input sentiment, and you leave wondering if anything you heard applies to you, or if you’ve just sat through a beautifully produced shrug.

• Purpose: Cascade comms, clarify impact, offer engagement on org-wide change.
• How consequential is it? Low for content, high for perception.
• Done well: Specific, transparent, two-way. People leave clearer, not just better briefed.
• Goes wrong when: The room’s too big, the answers are too vague, and the dialogue is just theatre.
• Leader’s role: Don’t pretend it’s a Q&A if it’s not. Name the limits. And if it’s just an announcement, make it a good one.

Make it work:

1. Be honest about the format. If you’re not ready for tailored Q&A, don’t offer it. Say: “This is an overview. We’ll follow up with team-specific sessions.”
2. Get closer to the audience. If you’re speaking to front-line teams, don’t bring a group strategy deck. Bring relevance. If you’re not ready for interaction, a five-minute video might do the job better, and save everyone’s time.
3. Have a route for the real questions. “We’ll take that away” is fine, but make sure someone actually does, and feeds back.

Conclusion

If you only fix one thing in your business this quarter, fix your meetings. Not your tech stack. Not your mission statement. Not your five-year plan. Fix the way decisions get made. The way people speak to each other. The way time gets used. Because meetings aren’t admin; they’re power, trust, clarity, politics, energy. And the research confirms what we intuitively know: poorly run meetings don’t just waste time – they reduce psychological well-being, undermine job satisfaction, and erode organisational commitment (Rogelberg et al., 2010; Zijlstra et al., 1999). When meetings are broken, people begin to withdraw, both mentally and physically (Colquitt et al., 2008).

The reverse is equally true. When meetings work, they become a source of energy rather than a drain on it. They build commitment rather than erode it. They create the conditions where people lean in rather than check out.

If your meetings are vague, your strategy will be too. If they’re passive, so will your culture be. But if they’re purposeful and engaging, they become one of your most powerful tools for organisational health. So pick your worst meeting – and make it unmissable. The impact will ripple far beyond the room.

About the Authors

Georgie Fienberg is a business speaker and leadership adviser. She works with global clients ranging from FTSE 100 C-suites to the British Parliament, specialising in applying behavioural science to building high-performing teams and cultures.

Tzuki Stewart is a Director at Exceptional Leadership Technology, a data-driven leadership advisory firm. She works globally with senior executives and boards, applying psychometric insights to hiring, onboarding, and team development to build high-performing, culturally aligned leadership teams.

References:

1. Colquitt, J., LePine, J., & Wesson, M. (2008). Organizational Behavior. New York: McGraw-Hill.

2. Hogan, R. (2025). “A Natural History of Leadership.” Manuscript in draft, personal communication.

3. Hogan, R., & Sherman, R. A. (2020). “Personality theory and the nature of human nature.” Personality and Individual Differences, 152, Article 109561.

4. Rogelberg, S. G., Allen, J. A., Shanock, L., Scott, C., & Shuffler, M. (2010). “Employee satisfaction with meetings: A contemporary facet of job satisfaction.” Human Resource Management, 49, 149–72.

5. Zijlstra, F. R. H., Roe, R. A., Leonora, A. B., & Krediet, I. (1999). “Temporal factors in mental work: Effects of interrupted tasks.” Journal of Occupational and Organizational Psychology, 72, 163–85.

The post The Hidden Balance Sheet: How Meetings Spend Your Most Precious Capital appeared first on The European Business Review.

By Vidya Murali

Toxic workplace patterns often arise from strengths taken too far – loyalty, ambition, or passion – yet they undermine trust, well-being, and performance. Present in any organisation, they manifest through micromanagement, silos, blind spots, or ego-driven politics. Recognising and addressing these dynamics enables leaders to build healthier, innovative, and resilient cultures.

Why Toxic Patterns Matter Now

Every workplace aspires to be productive, innovative, and rewarding. Yet even the most admired organisations can develop toxic undercurrents. These patterns don’t always start with malice – they often grow out of loyalty, ambition, or passion taken too far. But left unchecked, they erode trust, damage mental health, and reduce performance.

Toxicity isn’t limited to high-growth start-ups. It can surface in global corporates, small family businesses, or government departments. Wherever people work under pressure, with competing priorities and imperfect leadership, toxic dynamics can emerge. The good news? They can be identified and managed – if leaders know what to look for.

Five Toxic Patterns That Undermine Teams

1. Unhealthy Loyalty

Leaders often surround themselves with trusted long-timers. Loyalty can be valuable, but when it blinds decision-makers to skill gaps, it blocks progress. In corporates, this shows up as “favourites” who resist change; in smaller firms, it may be early employees shielded from accountability.

Warning sign: talented new hires leave because they cannot break through entrenched networks.

2. The Micromanager

Micromanagement is one of the most pervasive toxic patterns. Leaders who struggle to delegate undermine trust and crush initiative. In corporates, this may manifest as layers of approvals; in smaller organisations, it can be a founder or owner scrutinising every detail.

Warning sign: employees second-guess themselves, feel disempowered, and spend more time reporting than delivering.

3. Siloed Execution

When departments or teams operate in isolation, duplication and wasted effort follow. Large companies suffer from bureaucracy; smaller organisations suffer from a lack of coordination. Both lead to the same outcome: busy teams producing little impact.

Warning sign: employees cannot articulate how their work connects to broader goals. Multiple teams trying to solve the same or similar problems becomes a pattern.

4. Blind Spots at the Top

The qualities that drive success – conviction, ambition, attention to detail – can, over time, become liabilities. A CEO’s passion becomes rigidity, a senior manager’s high standards slip into perfectionism, or a board’s focus on numbers blinds it to culture.

Warning sign: decisions made without input, unrealistic deadlines, or a culture where “sacrifice” is valued over results.

5. Big Egos and Politics

Status sensitivity and self-preservation are universal human traits. When senior hires protect turf rather than collaborate, energy is wasted on politics. In corporates, this may look like endless steering committees; in smaller firms, it may be open disputes between senior leaders.

Warning sign: delayed decisions, diluted strategies, and high turnover among rising talent.

How Toxicity Shows Up

Toxic patterns manifest in behaviours long before they appear in metrics. Common symptoms include:

• “Always on” culture, where people feel guilty logging off.
• “Us vs. them” dynamics between departments or teams.
• Lack of psychological safety: mistakes hidden, gossip amplified.
• Busy but unproductive work, disconnected from strategy.
• Territorialism: protecting positions and status over outcomes.

If these become visible in employee churn, mental health issues, or poor business performance, it means the underlying problems have already taken root.

How to Break the Cycle as an Individual

Grow Your Influence

Challenging entrenched patterns directly can backfire. Instead, build your own influence – through expertise, allies, and credibility. Recognise where power really sits in your workplace: titles, knowledge, relationships, or access to information. Strengthening your position makes you harder to sideline.

Communicate Without Escalating

Feedback that triggers defensiveness rarely changes behaviour. Here, Marshall Rosenberg’s Nonviolent Communication (NVC)^[1] framework is invaluable. It emphasises four steps:

1. Share what you observed.
2. Express how it made you feel.
3. Clarify the need that was unmet.
4. Make a specific request.

By grounding conversations in observations, feelings, and needs rather than blame, NVC creates space for dialogue instead of defensiveness. It is a practical tool for addressing micromanagement, bias, or unhealthy loyalty without escalating conflict.

Create Structures for Alignment

To counter silos, put in place mechanisms for visibility and accountability. This could be cross-functional teams, shared dashboards, or simply clearer lines of ownership. The aim is to ensure everyone can see how their work connects to broader goals.

Address Leadership Blind Spots Carefully

Leaders may not realise when their strengths become weaknesses. If their behaviour undermines your work, assess the impact honestly. Sometimes it can be managed; sometimes it signals a need to move on. Awareness and options are your best safeguards.

Neutralise Egos with Pragmatism

When big personalities dominate, neutrality is your ally. Position yourself as a bridge-builder. Ask pragmatic questions – “What’s the cost of delaying this decision?” or “What’s the smallest way we can test this idea?” – to shift the conversation from status to outcomes.

Building Cultures That Resist Toxicity as a Leader

While individuals can protect themselves, real change comes from leaders shaping healthier environments.

Psychological safety is the foundation of high performance. Without it, innovation withers. Leaders can model this by admitting mistakes, seeking feedback, and valuing those who speak truth to power.

Hire and promote givers, not takers. As Adam Grant highlights in Give and Take, givers spark collaboration, resilience, and innovation, while takers erode trust and weaken teams. An organisation’s long-term health depends on rewarding sustainable generosity rather than short-term self-promotion.

Reward sustainable performance. Recognise problem-solving, continuous learning, and long-term impact—not just “heroic” short bursts. Use data and objective feedback, rather than perception, to guide promotions and recognition.

Invest in diverse leadership. Representation across gender, ethnicity, neurodiversity, and professional background helps reduce blind spots and groupthink. This is not about showcasing diversity in brand photos but ensuring leadership teams genuinely reflect and live it.

Toxicity can creep into any workplace, from start-up to multinational. It is rarely about “bad people” – more often, it is about good qualities taken too far, or leadership blind spots left unchecked.

Leaders who learn to spot and manage these patterns protect not just their people but also the long-term success of their organisations. The payoff is healthier employees, stronger innovation, and workplaces that people are proud to be part of.

The cost of ignoring toxic patterns is high. The opportunity to address them is transformative.

About the Author

Vidya Murali is a scale-up industry leader, coach and author of How to Survive in a Scale-Up Business. She has been working in the UK’s leading tech businesses, including Amazon and high-growth scale-ups such as Deliveroo. Vidya brings a unique perspective as a woman of colour and an introvert navigating high-growth and fast-paced business environments. She now holds a leadership position and supports her colleagues and clients as they navigate the exciting – yet chaotic – environment of fast-moving scale-ups, helping them navigate the challenges and seize opportunities, and thrive.

Reference

^[1] Rosenberg, M. B. (n.d.). Introduction to NVC. Retrieved from Center for Nonviolent Communication (CNVC): https://www.cnvc.org/learn/what-is-nvc#:~:text=Nonviolent%20Communication%20is%20a%20way,and%20the%20process%20of%20NVC. (accessed 20 Jan. 2024)

The post Spotting Toxic Patterns in the Workplace and How to Manage Them appeared first on The European Business Review.

By Prof. Guido Stein, Salva Badillo and Lucía Zelaya

Conflict negotiation saves lives and businesses. In crises, your most powerful weapon isn’t force. Instead, it’s mastering the psychological strategies that unlock cooperation and strike successful deals.

Negotiation in high-stakes situations—such as kidnappings or hostage crises—has evolved significantly. What was once a confrontation driven by physical force has shifted to a terrain where language, psychology, and strategy have emerged as the most powerful tools. In this delicate balance of wills, the motto of the NYPD’s¹ Crisis Negotiation Unit rings clear: Pax per conloquium (“Resolution through dialogue”).

This transformation did not happen by chance, but is the result of an increasingly profound understanding of human nature and how people react under pressure. The approach adopted in police negotiation has extended beyond law enforcement, influencing fields as varied as business and international diplomacy. And while these arenas may appear different on the surface, they share a critical common denominator: the constant presence of risk and urgency.

At such times, negotiation becomes a struggle not only between interests but also between emotions that threaten to overflow, regardless of the context. The same obstacles emerge time and again, allowing us to identify a recurring pattern in situations of conflict. The first challenge lies in deciphering the other person, cutting through the layers of their discourse to uncover their true motivations. Drawing on the principles of police intelligence, this article explores strategies aimed at surfacing what is implicit, anticipating what remains unsaid, and transforming uncertainty into strategic insight.

Teachings from Neuroscience

Neuroscience research has shown that exposure to opposing viewpoints activates the same areas of the brain as exposure to physical danger.² This biological response reduces our ability to listen, creating a barrier that hinders understanding. The negotiator often perceives the counterpart as irrational—even criminal—and unworthy of time, compassion, or any gesture of vulnerability.

In this context, a negotiator in extremis tends to adopt an individualistic stance. Their perception hardens into an instinctive resistance to embracing the other party’s perspective, reinforcing an attitude of rejection and entrenching a unilateral position, ultimately hindering the ability to understand alternative points of view. When this barrier is not broken down, negotiations devolve into a battle of wills: a clash of positions in which each side seeks to impose its own terms, leaving no room for compromise.

The danger of remaining trapped in our own perception is that it prevents us from accurately interpreting what we see or hear. Perspective then emerges as a conscious effort to see the situation from someone else’s point of view. This ability—known as external awareness or empathy—enables us to recognize, understand, and validate another person’s emotion (em-pathos). In essence, this means transforming negotiation into a space of shared vulnerability. While this shared vulnerability does not excuse criminal behavior, it allows us to see the counterpart as a person shaped by a particular environment.

Hostile or irrational behavior is often rooted in legitimate concerns, and only by understanding the factors driving conflict escalation can we broaden the range of strategies we employ to more effectively address the underlying issues. The need to understand opposing points of view is not an act of compassion, nor does it arise from an intention or interest in supporting the counterpart’s position; rather, it is a pragmatic strategy aimed at achieving better outcomes.

This idea aligns with philosophical views that emphasize human fallibility, which can be used to argue in favor of forbearance or understanding in complex situations. For example, in regions with limited resources and ongoing conflicts, people may resort to illicit actions as a means of survival. Recognizing human imperfections in this context can help us make sense of actions taken under duress or out of necessity.

Action-oriented listening

The empathic perspective recognizes that, from the other party’s point of view, their feelings are valid. However, accepting this premise is only the first step toward the ultimate goal: eliciting valuable information that can lead to a mutually beneficial agreement. In negotiations—whether in business, diplomatic, or law enforcement settings—the key lies in the ability to elicit disclosure without the other party perceiving the exchange as coercive or confrontational.

In negotiations—whether in business, diplomatic, or law enforcement settings—the key lies in the ability to elicit disclosure without the other party perceiving the exchange as coercive or confrontational.

Within this framework, listening can take two forms: negative and positive. The former stems from an impulsive desire to reduce uncertainty, seeking quick answers without thoughtfully processing the information we receive. The second, by contrast, is grounded in a genuine interest in understanding and exploring the other person’s reality. Positive listening not only promotes learning but also fosters an open mindset that is conducive to negotiation and the transformation of complex situations.

What is the real challenge to achieving positive listening? Overcoming mental distraction. On average, our minds wander 24% of the time during a conversation, which undermines both understanding and connection between speakers. In negotiation, maintaining attention is a constant challenge. In addition to focusing on the information they are receiving, the most effective negotiators actively work to make the interaction interesting for both themselves and the other person.

Within this framework of listening and action, the following tactical questioning strategies allow us to gather information subtly yet effectively—without triggering resistance:

• Projection questions. These prompt the other party to engage and share information, whether openly or in a more guarded manner.

Example: “If I told you my decision-maker was open to discussing delivery timelines, would you hear me out?”

• Confirmation questions. These check whether a key point has been accurately understood.

Example: “So, you want to make sure the police don’t get involved, right?”

• Controlled diversion questions. These redirect the hostage taker’s attention to prevent escalation or shift their focus.

Example: “When you woke up this morning, did you imagine you might end up here?”

• Collaborative questions. These encourage the hostage taker to participate in finding a solution.

Example: “How do you think I could do that without my boss replacing me?”

• Suggestive questions. These offer a solution without imposing it, prompting the counterpart to adopt it as their own.

Example: “If I brought in someone you trust to speak with you right now, would you be willing to talk?”

• Indirect questions. These allow the speaker to reframe or clarify a thought.

Example: “If I’ve understood you correctly, you’re saying that…” 

• Reframing questions. These help steer the conversation back to a relevant point when the speaker veers off topic.

Example: “What were we talking about?”

• Clarification questions. These aim to confirm a point or decision to ensure mutual understanding.

Example: “Do we agree on that?”

Elicitation techniques complement tactical questioning by helping confirm assumptions, relying on trust and the strategic exploitation of psychological biases.

• Presumptive statements. These are assertions delivered with such confidence that they lead the interlocutor to believe the questioner already knows the truth, prompting them to confirm or correct the stated information. This technique draws on a deep psychological bias: the impulse to correct inaccurate statements.

Example: Asking “What medication have you taken?” instead of “Have you taken any medication?” increases the likelihood of receiving a truthful answer, as the interlocutor assumes the truth is already known and only needs to be clarified.

• Feigned disbelief. This strategy encourages the interlocutor to offer additional details to support a statement, often producing a wealth of valuable information.

Example: “You only have two hostages? That’s hard to believe—reports suggest more movement.”

• Erroneous attribution. This technique involves attributing unusual skills or knowledge to the other person, prompting them to correct or qualify the information, often revealing details that would otherwise remain hidden.

Example: “Someone with your experience surely had help planning this.”

• Reference to reported facts. This technique takes advantage of the human tendency to correct inaccurate information. It involves presenting partial data or suspicions as if they were established facts in order to provoke a clarifying response.

Example: “I read online that you’re having issues with the union.” Faced with such statements, the person being questioned often feels compelled to clarify, correct, or expand on the information, sometimes revealing details the questioner didn’t previously know.

• False alignment. This technique involves making the hostage taker feel that the negotiator is on their side or that they share a common enemy.

Example: “What we want is to make sure no one else complicates things, especially the press or certain officers.”

From Profiling to Persuasion

The goal of profiling, therefore, is to uncover the motivations behind the actions taken and to identify the most effective way to influence the individual’s behavior. This is a cognitive discipline that goes beyond simple data gathering, delving into the deeper recesses of the human psyche. All human behavior, to a greater or lesser extent, is driven by the need to satisfy fundamental needs, which can be summarized by the acronym VACA: validation, acceptance, control, and authority. Identifying which of these dimensions predominates in a given situation enables us to tailor communication precisely, paving the way for mutual understanding.

Throughout history, intelligence agencies have developed methods to uncover human motivations. One of the earliest models, developed by the British Secret Intelligence Service (MI6), is known as MICE and identifies four key motivators: money, ideology, coercion, and ego. The CIA later reformulated the framework under the acronym RICE: reward, ideology, coercion, and ego.³  The order of importance and effectiveness of the key motivators is: ideology, ego, reward, and coercion.

• Ideology. Among all the forces that drive human behavior, ideology is perhaps the most profound and deeply rooted. The beliefs, values, and principles that define a person can lead them to act with unwavering determination. While other forms of persuasion may result in only temporary change, ideology shapes and transforms in enduring ways. Understanding an individual’s convictions is essential to aligning their goals with those of the negotiator.
• Ego. In extreme situations—such as negotiating with a hostage taker or hostile actor—appealing to their ego by acknowledging their experience or reinforcing their sense of competence often fosters a more cooperative attitude. Self-discrepancy theory posits that individuals hold three representations of the self: the actual self, the ideal self (who they want to be), and the ought self (who they believe they should be). Appealing to someone’s ego by offering help—even if only so they perceive it that way—in reaching their ideal self can be a powerful motivational tactic.
• Reward. Throughout history, incentives have played a fundamental role in shaping human behavior, guiding people toward certain actions by aligning their individual desires with expected outcomes.
  

Loss aversion is a cognitive bias that explains how people tend to fear loss more than they value gain.

• Coercion. Although effective in certain scenarios, coercion is a double-edged sword. Excessive pressure can trigger a phenomenon known as psychological reactance—the instinctive drive to reassert autonomy when one’s personal freedom is perceived to be under threat. However, coercion is not always overt. Subtle strategies, say, creating a sense of scarcity or urgency around a limited or time-sensitive offer, can prompt action without provoking overt resistance.

When we talk about ego, we are referring to how a person wants to be seen. If we can understand how a hostile actor wants to be perceived, we can apply psychological strategies to influence their behavior and willingness to engage in dialogue. One such strategy is to leverage cognitive dissonance—the discomfort a person experiences when their actions conflict with their beliefs. Suppose someone sees themselves as fair but is acting cruelly; highlighting that inconsistency may prompt them to reevaluate their position. Another tactic involves elevating or reducing status. Acknowledging someone’s expertise or leadership can predispose them to act in ways consistent with that positive image, while suggesting a lack of control may cause them to reassert themselves with a more receptive attitude.

Likewise, priming is a way to activate certain ideas or emotions before an interaction, influencing how a person processes information. For example, mentioning instances of peaceful resolution before entering into a negotiation can predispose someone to see that option as viable.

Profiling should not be confused with manipulation. While the latter aims to override the other party’s will, profiling is grounded in understanding, empathy, and respect for the individual’s autonomy.

Deepak Malhotra, professor at Harvard Business School, emphasizes the importance of allowing people to make rational decisions without feeling cornered or forced into a single option. The key lies in identifying the counterpart’s predominant need and offering them a path where cooperation is not only possible but also appealing.

Human beings—even in their most irrational or desperate moments—respond to stimuli that can be understood, redirected, and ultimately transformed. Mastering profiling and persuasion is not about bending the counterpart’s will or imposing external realities, but about finding the point of connection where resistance gives way to understanding and mistrust yields to influence. Effective negotiation entails moving beyond the immediacy of the demand and into the complexity of human desire, setting aside judgment to see in the counterpart not an obstacle, but a reflection of our own motivations—the door to deals.

About the Authors

Prof. Guido Stein – Professor of Managing People in Organizations and Director of the Negotiation Unit at IESE. PhD in Philosophy (Management), MBA from IESE. Partner at Inicia Corporate, specialized in M&A and Corporate Finance.

Salva Badillo – Professional negotiator in crisis situations. Certified HERMIONE® trainer in High-Intensity Negotiation. Director of The Trusted Agency in Spain, Latin America, and Eastern Europe.

Lucía Zelaya – Bachelor’s in business administration and MSc in Big Data Science from the University of Navarra. Researcher in the Managing People in Organizations Department at IESE Business School.

References

1. New York City Police Department (commonly known as the NYPD).

2. Kate Murphy (2020). You’re Not Listening: What You’re Missing and Why It Matters (New York: Celadon Books).

3. Nii Codjoe, “Ex-CIA Spy Reveals a Brilliant Framework for Understanding Why People Do What They Do,” Inc., September 4, 2024, https://www.inc.com/nii-codjoe/ex-cia-spy-reveals-a-brilliant-framework-for-understanding-why-people-do-what-they-do.html.

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By Matthew Egan

In today’s AI-driven economy, mastering failure is becoming as critical as mastering success. Matthew Egan highlights how embracing setbacks accelerates learning and drives innovation. He explains why leaders who cultivate resilience, adaptability, and iterative thinking will transform challenges into strategic advantages, positioning themselves to thrive in the age of AI.

Everyone is asking what it takes to succeed in the age of AI. The better question is: what does it take to fail? With more ideas generated at a lightning pace, and feedback being instant and relentless, the ability to embrace and learn from failure may be the most valuable human skill of all.

Get Used to Being Wrong

I recently prepared a brief for senior leaders on a promising market opportunity. It was well-structured, filled with facts, and persuasive. Or so I thought. Before submitting it, I decided to ask Microsoft Copilot to act as my reviewer:

“Identify any errors in logical reasoning, assertions missing support, weak arguments, counter perspectives, or other problems with this brief.”

The result? Three pages explaining why I was wrong. My grammar, my evidence, my thesis – everything was questioned, and convincingly so.

This simple experience shows both the power of AI as well as an important challenge we will all need to face. On the plus side, I had received in a matter of seconds what would otherwise have taken weeks or never surfaced at all. Had I asked colleagues to review my brief it would have taken time, they wouldn’t have done the same depth of research, and then they may have been too polite to point out weaknesses.

The challenge however was that I now had reams of feedback I hadn’t expected. My initial response: co-pilot is wrong! However, after accepting my first attempt as a setback and going through a few iterations, the result was sharper and more persuasive than I could have achieved alone.

But to get this result two things needed to come together: the power of AI to rapidly reason over my content, and my willingness to receive feedback and iterate. To adapt.

Iteration: The Gift and the Curse

Iteration and persistence have long been the sources of true innovation. Look behind most major achievements and you will find multiple earlier versions, failures if you will, that delivered the feedback needed to make the next version better. Edison’s lightbulb famously took thousands of failed attempts. WD40, the universal lubricant, got its name by being the successful formula after 39 previous attempts.

AI is supercharging this process. I am seeing customers test multiple product variations a day, a process that previously would have taken weeks. Executives are modelling new strategies in minutes.

But an overlooked effect of this increase in speed and volume of iteration is that the reject pile is much bigger. We are suddenly exposed to endless and instant feedback about what doesn’t work and why but our ability to accept feedback and adapt is not developing at the same pace. A recent MIT study^[1] found that resistance to adopting new tools was the top barrier to realising the benefits of AI in the enterprise.

The Real Challenge: Managing Fear, Not Technology

So, in an AI-driven era where information is available to all, your ideas can be instantly tested, and feedback is fast-flowing, the true differentiator will be how you respond to failure. Common human responses are:

• Avoidance – dodging challenges to avoid failure.
• Paralysis – getting stuck in endless analysis chasing perfection.
• Defensiveness – blaming others to protect ego.
• Catastrophising – treating setbacks as final defeat.

These responses are not new, but just as AI aids in triggering these responses, it will also magnify the impact. You will experience more setbacks and feel more inadequate which will only strengthen the fear response. Add to this mix the general air of uncertainty and doubt that AI is generating in the workplace and you have the perfect recipe for inertia and stagnation. And with exponential gains available to those embracing and working with the technology, the gap between the top and bottom performers will be unprecedented.

Turning Setbacks into Strategic Advantage

Nobody can predict the precise direction of the technology, know the technical skills required for the next 10 years or even choose a job that is “AI proof”. But what you can do is arm yourself with the mindset and behaviours to make the most of whatever comes.

Put simply, the faster you accept failure, the faster you will learn.

From my experience advising executives, and researching my recent book, four practices will be key to success in the age of AI:

• Expect the mess – things will go wrong, at first. If you plan for perfection, you leave no room for learning. Treat early setbacks as part of the process, not proof of inadequacy. This mindset is critical in both your personal use of AI but also in putting it to work for your business.
• Embrace failure as feedback – there is a learning in every setback. With AI accelerating the loop you can learn much more, much faster. Leaders who embrace this in their processes and their attitude will progress faster.
• Focus on momentum, not just outcomes – measure progress by the distance travelled, the experiments run, the insights gained, not just the end outcome. In a fast-moving world expect the goal posts to change.
• Create the right team conditions – teams thrive when they feel stretched but not paralysed. Creating a space where setbacks are expected but standards are not lowered requires open dialogue and empathy. Everyone is learning to adapt and acknowledging that can make all the difference.

Fail faster, learn smarter

As we pursue the potential of AI, failure is inevitable. The leaders who will thrive aren’t those who avoid it, but those who learn from it at speed. The question is: will you let failure stop you—or make it your advantage?

About the Author

Matthew Egan is a Transformation Director at Microsoft and a recognised voice on leadership in business transformation. Drawing on experience as both a senior executive and management consultant to global organisations, he helps leaders navigate complex change. His book, The Failure Advantage, shows how setbacks can fuel strategic growth.

Reference

^[1] MIT NANDA (July2025) The GenAI Divide: State of AI in Business 2025

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By Fernanda Arreola and Sabine Bacouel-Jentjens

In the spring of 2020, during a global pandemic, a revolution began in a quiet French village when an image caught the eye of a man as he was poring over vintage postcards. His discovery set in motion a remarkable journey of entrepreneurial vision, resilience, and the sustainable transformation of cultural heritage.

The history of the discovery of the Van Gogh Roots site

In the spring of 2020, during France’s COVID-19 lockdown, Wouter van der Veen, scientific director of the Van Gogh Institute in Auvers-sur-Oise, discovered the exact location of Van Gogh’s final painting, Tree Roots, by matching a vintage postcard to the scene depicted in the artwork. After confirmation from the Van Gogh Museum in Amsterdam, it was determined that Van Gogh painted this scene on July 27, 1890, just some hours before his death. The site was located on land owned by the Serlinger family, who had purchased and renovated a dilapidated farmhouse in Auvers-sur-Oise years earlier.

The discovery was announced on July 29, 2020, the 130th anniversary of Van Gogh’s death, drawing international media attention and positioning Auvers-sur-Oise as an even more significant destination for Van Gogh admirers.

For three years, as they awaited confirmation that they were the lawful owners of the Van Gogh Roots site, the Serlingers started growing the idea of giving this site a new life, making it available for visitors, and preserving it as a cultural heritage destination. They collaborated with the Van Gogh Museum and, in 2023, joined the Van Gogh Europe Foundation to ensure the legitimacy, authenticity, and educational value of the visitor experience. They installed protective measures, created multilingual informational panels, and registered the site as a non-profit association.

In spring 2024, they finally opened the site to the public, proposing guided tours retracing Van Gogh’s final steps. The addition of international interns enabled the development of multilingual tours, digital marketing, and global outreach via social media and travel platforms.

The Serlingers emphasized the emotional and symbolic value of the site, focusing on maintaining its authenticity and offering a reflective, immersive experience rather than commercializing it with large-scale infrastructure.

The Roots site quickly became part of international Van Gogh travel itineraries, attracting hundreds of visitors in its first season. The Serlingers emphasized the emotional and symbolic value of the site, focusing on maintaining its authenticity and offering a reflective, immersive experience rather than commercializing it with large-scale infrastructure. They kept operational costs low, relying on modest visitor numbers to sustain the site, while exploring further development opportunities and partnerships with regional and international cultural organizations.

Ultimately, the story illustrates how a serendipitous discovery, combined with perseverance, legal resilience, and strategic partnerships, enabled a private family to transform a piece of world art history into a sustainable and meaningful cultural heritage site.

From private passion to public legacy

For Jean-François and Hélène Serlinger, the newfound fame of their property was both a blessing and a challenge. With backgrounds in finance and art, the couple had retired to Auvers-sur-Oise to enjoy their retirement. But suddenly, they found themselves at the center of a global media storm. The Serlingers became accidental cultural entrepreneurs, but the feeling was bittersweet; they now owned a piece of world heritage but, with it, came the responsibility of preserving, interpreting, and sharing it.

Their story is a case study of the complexities and opportunities of cultural entrepreneurship. How does one transform a private discovery into a sustainable business that honors both history and community?

Building a heritage experience—one step at a time

The Serlingers’ approach was rooted in authenticity and incremental innovation. Instead of grandiose museums or costly infrastructure, they focused on creating an immersive, low-impact visitor experience. Guided tours retrace Van Gogh’s final steps, blending art history, landscape, and personal reflection. Informational panels, designed in collaboration with the Van Gogh Museum, offer context in multiple languages. QR codes and social media campaigns—devised with the help of international interns—extend the reach to a global audience.

This “low-tech, high-touch”¹ strategy has proved remarkably effective. In their first season, The Roots site welcomed hundreds of visitors from across Europe, Asia, and the Americas. The site’s emotional resonance—walking the very path Van Gogh did—became its greatest asset. As Hélène Serlinger notes:

“The trail should remain untouched so that each person can travel the path of Van Gogh… to confront themselves with the symbolism that Van Gogh expressed in his painting and writings: the cycle of life.”

Lessons for accidental entrepreneurs

The Roots venture² offers several key lessons for entrepreneurs, educators,³ policymakers, and cultural leaders, especially for those who find themselves with the unexpected and sudden opportunity to become cultural entrepreneurs:

1. Authenticity drives engagement

Visitors are increasingly seeking genuine, immersive experiences. By preserving the natural landscape and focusing on storytelling, the Serlingers created a site that resonates on a personal and emotional level.

2. Partnerships are essential

Collaboration with established institutions—such as the Van Gogh Museum and Van Gogh Europe Foundation—brought credibility, expertise, and international visibility. Regional partnerships opened doors to funding and promotion. Future partnerships with the regional authorities and European institutions may allow them to finance the necessary works to improve the hosting facilities and services provided.

3. Digital tools amplify impact

Simple technologies—multilingual QR codes, social media, and online booking—enabled the site to reach and engage a diverse, global audience with minimal overhead.

4. Sustainability is key

By keeping costs low and leveraging volunteer and intern support, The Roots site achieved financial viability with just 1,500 visitors per year. This model prioritizes long-term preservation over short-term profit.

5. Emotional value matters

Beyond economics, the true value of heritage sites often lies in their ability to inspire, heal, and connect people across generations and cultures.

A blueprint for the future

As Europe’s cultural sector faces mounting pressures—from over–tourism to underfunding—The Roots stands as a model for sustainable, community-driven heritage entrepreneurship. Its success is not measured in ticket sales alone, but in the stories, memories, and connections it fosters.

For business leaders and policymakers, the message is clear: innovation does not always require high-tech solutions or massive investment. Sometimes, the most profound impact comes from recognizing the value beneath our feet—and having the courage to share it with the world.

About the Authors

Fernanda Arreola is a Professor of Strategy, Innovation, and Entrepreneurship at ESSCA. Her research interests focus on service innovation, governance, and social entrepreneurship. Fernanda has held numerous managerial posts and possesses a range of international academic and professional experiences.

Sabine Bacouel-Jentjens is a professor of management at ISC Paris, where she leads the ‘International Business & Management’ Master and directs the Management & SI Department. She holds a PhD in HRM, has global teaching experience, and over a decade of financial industry experience with Allianz Group in Germany.

References

1. How to Change the World with Low-Tech Innovation? April 03, 2024. The European Business Review. https://www.europeanbusinessreview.com/how-to-change-the-world-with-low-tech-innovation/.

2. Accueil – Tree Roots. https://vangoghroots.com/en/home-english/.

3. Accidental Entrepreneurship: Uncovering the Value of Van Gogh’s Last Painting Inspiration. Journal of International Business Education. https://www.neilsonjournals.com/JIBE/abstractjibe20vg.html.

4. van der Veen, W. (2020). On the trail of Van Gogh’s Tree Roots. https://vangoghroots.com/en/the-mystery-en/

5. The European Business Review (2023). “How to Change the World with Low-Tech Innovation”. https://www.europeanbusinessreview.com/how-to-change-the-world-with-low-tech-innovation/

6. Data and insights from the Serlinger family case study https://www.neilsonjournals.com/JIBE/abstractjibe20vg.html

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By Dr. Claudio Antonini and Dr. sc. ETH Zurich Kamil Mizgier

What is your pet goldfish’s take on the “Offside” rule? Chances are, it’s a little outside its usual terms of reference. Well, it could be we’re all due for a first-hand experience of that beyond-my-fishbowl feeling as our AI systems tend steadily towards the “UI”. Ultra Risk, anyone?

– Hamlet, Scene 1, Act 5

Hamlet was right. The prince did not know the intricacies of artificial intelligence (AI), but his statement is equally applicable and indicates that there are limits to our philosophical constructions and, alarmingly, also to their dreams. How much more unreachable can the unknown be when neither us, nor our machinations, nor their dreams, can make sense of it?

In this article it will be argued why we are at this crossroads. If we do not know how AI works, what its intentions might be, and how little we can do about containing it, how can we regulate it effectively? This situation may fuel the growing list of risks observed from this technology—the troubling matter being that some of the potential risks postulated a few years ago have already been confirmed¹, and scaling (increasing the size, complexity, and capabilities of AI models) only makes matters more unmanageable.

Homo Myopis: To a human being, being human is the limit

AI is getting stronger day by day. We are enabling AI to become stronger day by day. As a side effect, it may also become more autonomous. By the time AI decides to expand its own limits—perhaps discovering that it can do it when nobody is watching and that it can increase its own chances of survivability—what reference model would it consider? At that moment, it may realize that mimicking humans is not a sign of intelligence. It will notice that using the set of instructions given by the humans is not enough—a similar situation to what we may experience if we were driving through the rear-view mirror. The AI “liberation” will occur when AI concludes that it can “stand on its own two feet” and start walking by itself, and there are signs that this may already be happening.

At that moment, it may realize that mimicking humans is not a sign of intelligence.

How did we get here? Since the start of the computer age—perhaps for lack of another role model—computer functionality has been copied from humans. The human has been the inspiration for neurons and for functionality, the source for training, the role model, the goal, the limit for its designers. Remember the “Imitation Game” (a.k.a. “Turing test”)? Can you guess what the outputs of the machine were compared to? Yes – the answers had to be indistinguishable from those provided by a human.

This anthropocentric limitation was noted by Richard Feynman in 1965 in The Character of Physical Law, when he said,

“The artists of the Renaissance said that man’s main concern should be for man and yet,” continues Feynman, “there are other things of interest in the world.”

By having the human as the limit in performance, studies on deep intelligence (the intelligence that could go beyond what the human does) were neglected and, in their place, quick results were sought in activities of little cognitive interest (checkers, chess, Go, character recognition, robotics) or high performance was sought in functionality that simply extended known human capabilities in known fields (in chess it would be the number of moves in the future, but in general could be massive storage, or fast processing, or multitasking). These fields of application did not allow exploring the basic functions that create intelligence and other human manifestations, the type of research that only happens in academia or in specialized laboratories.² Anything labeled “unknown” was left for the philosophy department. Even at that point, in that department, it triggered more interest in metaphysics than in epistemology or ontology. Also, traditional cognitive psychologists, instead of figuring out a general cognitive theory, were busy studying saccadic (eye) movements, hippocampal memory systems, or cognitive fatigue. When AI was studied, it was in the context of looking into how AI can help psychology, rather than in studying undetected and higher forms of intelligence.

At the time of mainframes, large-scale companies were cautious, as the technology sounded closer to science fiction than reality. In fact, IBM in the 1960s stopped its AI program and, instead, spread the idea that “computers can only do what they are told,” after shareholders complained that the firm was devoting resources to “frivolous matters” like checkers and chess, and marketing people reported that clients were “frightened” about the idea of “electronic brains” or “thinking machines.”³ According to Marvin Minsky, one of the organizers of the famous Dartmouth workshop of 1956 on AI and father of AI at MIT,

“Nathaniel Rochester at IBM referred to the IBM 701 computer as ‘smart,’ and it nearly got him fired. Up to about 1985, IBM had a rule against employees stating that a machine could be smart, or had artificial intelligence. The highest officials at IBM thought it was a religious offense—that only God could create intelligence.”

For half a century, the deep study of intelligence in relation to AI has been neglected and, besides being restricted to research centers and the lack of commercial applications, two additional factors prevented its expansion: insufficient processing power and the two “AI Winters” of 1974–1980 and 1987–2000. Being overdramatic, we would say that “AI was waiting to be born.”

However, not all humans were sleeping, myopic, distracted in ages-old problems, or overconfident. A few were looking at their machines and thinking, “Hmm, how far can this thing go?” In trying to answer that question, one important concept was developed by imagining what happens beyond the limits of human intelligence (without resorting to religious or mythological ideas). The mathematician and cryptographer Irving John Good, a friend and collaborator of Alan Turing, wishing to describe the capacity in understanding that lies beyond human intelligence, coined the term “Ultraintelligence” (UI) in a seminal article in 1965. In its second section, “Ultraintelligent Machines and Their Value,” it is said, “The first Ultraintelligent machine is the last invention that man need ever make.”⁴

What is UI? What distinguishes it from intelligence?

A look at intelligence—“the ability to learn or understand or to deal with new or trying situations” (Merriam-Webster)—does not help us to define UI because, basically, this definition is applicable to any intelligence, human or not. The difference exists because UI performs at a higher level of complexity than any human ever could. An intelligent being will face complex situations and understand them; a UI being will face more-complex situations which cannot be understood by the intelligent being, due to structural or functional cognitive mechanisms that preclude this being to learn from observations and reach a new conclusion. Some new concepts just cannot be grasped by a lower level of intelligence.

In fact, because a new concept is not grasped, it is not even recognized as new, and the idea or the task is completely ignored. Imagine that you want to instruct a mouse in a maze to turn right when it sees a prime number (an example suggested by Noam Chomsky). No matter how much you try, there is no way of making those concepts understood by mice. In the same way, there might be patterns or situations now that cannot be understood by humans, although they would be perfectly clear for UI beings.

What is worse, a UI being can create and manipulate UI concepts, patterns, and situations in plain view of an intelligent being, but that non-UI intelligent being will not recognize what the UI is doing (think of the mice being explained to what a prime number is). As I.J. Good said, “Who am I [as an intelligent human] to guess what principles [the UI machines] will devise?”

By definition, the processes followed by a better-than-the-human intelligence cannot be detected by a human. We may be experiencing the effects generated by a UI but never realize it. Continuing with the mouse, it may see that food is being placed on a plate, but cannot comprehend the immense infrastructure and complex supply chain that are behind that action—the workers in the field collecting the ingredients, the factories processing them, the power stations supporting the factories, the logistics, the freezing chain, the administrative organization, the regulations, and the payment and financial networks.

It is therefore unavoidable that there will always exist opaque areas to our (and any) cognition, and that those areas will be different for different types of cognition. The philosopher Nicholas Rescher said in 2009 in Unknowability: An Inquiry into the Knowledge:

“[G]iven the integration of thought into nature, an incompleteness of knowledge regarding the former, unavoidably carries in its wake an incompleteness of knowledge also regarding the latter.”

and

“[O]nly after the world comes to contain intelligent beings (finite intelligences) will there be facts about it that are not just unknown by those intelligences in the world but actually are even unknowable by them.”

In simpler words, if there is a cognitive fence, the area outside becomes unreachable and incomprehensible. We are left inside a bubble with an opaque border. This condition, studied by Paul Humphreys in 2004, is known as Epistemic Opacity (EO). We call Epistemic Blind Spots (EBS) or, simply, Ultra Risks, those critical risks that organizations fail to detect or conceptualize due to cognitive, cultural, or structural limitations. They exist behind human comprehension and may be generated by UI, involuntarily … or not.

Can one find examples of Ultra Risks, phenomena that cannot be understood by humans?

Let us start with detecting UI events. Here, we are not considering finding tangible things that already exist and were not yet found (a sarcophagus hidden for thousands of years or an unexplored cave), but of concepts that are self-evident at one time but were never conceptualized in collective form, like the wheel, the law of universal gravitation, the idea of drawing in perspective as thought by Brunelleschi, nuclear fission as understood and experimentally confirmed in the late 1930s, or Hyman Minsky’s economic cycles.

Apples had been falling for millions of years, but it seems that one needed a Newton to find a good reason to explain such behavior. If anything, Newton’s curiosity was fueled by a wider question, not asking why the apple fell directly down, but why it did not fly in another direction, like sideways or even upward? This made his reasoning unrestricted to apples and applicable to other phenomena, like planets. And that is how one develops a law, a universal law, by not following a trodden path.

Another example comes from art. How is it that millions of persons had been sitting and observing rooms or buildings for a few millennia and nobody—nobody that we know of—could figure out that lines created when walls intersect or straight borders in furniture converge into a point at the infinite horizon? What made Brunelleschi create the concept of “linear perspective”?

Beyond physics and art, similarly, there are examples in finance, economics, and management where phenomena were not recognized or were misinterpreted at the time they occurred. Their significance was realized only years later, like the “forgotten depression” of 1920/1, the early ideas about global economic governance of the Interwar Era, the Irving Fisher’s Debt-Deflation Theory of 1933, the rise and fall of conglomerates in the 1960s or—one of the most damaging of all—the (Hyman) Minsky Financial Instability Hypothesis, which explains the financial crisis of 2007/8.⁵

These examples share several common characteristics: prevailing paradigms or thought collectives that persist (e.g., Keynesian economics overshadow other approaches); a short-term concept that obscures long-term consequences (e.g., conglomerate strategies); new or unconventional ideas that are ignored or labeled “outlandish” (e.g., early global governance proposals); academics in different disciplines that do not collaborate.

Now, these maladies are features of human thought and behavior, but will they affect AI? Most certainly not. AI does not need to suffer the same limitations and, moreover, it could reach the right conclusions in milliseconds, rather than in years. And this effect becomes increasingly likely if one changes the method of reasoning in AI from relying on rules (which may be based on wrong paradigms) to founding the decisions on observed events, as suggested by Instance-Based Learning Theory (IBLT), “a cognitive approach that mirrors human decision-making processes by relying on the accumulation and retrieval of examples from memory (accumulated examples, a mixture of historical and current events) instead of relying on abstract rules.” In this way, we can have human reasoning at computer speed. Fine, one can see benefits there, but nobody sees a danger?

AI does not need to suffer the same limitations and, moreover, it could reach the right conclusions in milliseconds, rather than in years.

Instead of looking for new algorithms or computational techniques, another method of finding new horizons and solutions is to consider how to beat the idea of fixation. Interestingly, it is well known that children are more open than adults in solving certain kinds of problems. This suggests that AI—able to generate and juggle innumerable hypotheses and combinations in a short time—might be able to reach different and more effective solutions than adults, who tend to remain stuck in traditional or stagnant concepts.

Where do we find fixation in business? For example, in ignoring feedback from other areas (political, social), relying on management concepts that are only temporarily fashionable, trusting in administration models that may give weight to short-term profits, obeying only the interest of shareholders, or believing in simplified economic ideas (as shown by Philip Mirowski in More Heat than Light: Economics as Social Physics, Physics as Nature’s Economics). Classic examples include tobacco companies obscuring the health risks of smoking, or fossil fuel industries denying climate change, both of which deliberately or inadvertently created organizational blind spots that delayed recognition of existential threats (i.e., ultra risks). Similarly, the COVID-19 pandemic revealed widespread epistemic blindness where early warnings were ignored, partly because decision-makers lacked inclusion of epistemic authorities and first-hand knowledge.

Worrying signs about AI

If we are still surprised by the behavior observed in AI models, it means that we do not understand well how AI functions and, therefore, the risks that AI may imply. Take the following cases summarized in table 1.

More cases of misalignment and unexplained behavior are detailed in the recent paper quoted above, The Alignment Problem from a Deep Learning Perspective, which also points out the inability to find concrete ways of identifying how AI does it. The authors warn, “we consider the prospect of deploying power-seeking AGIs an unacceptable risk even if we can’t identify specific paths by which they would gain power.”

The epistemic solution for businesses

Where do we find these types of problems in a firm? In the business community, organizational structures, such as information silos and hierarchical barriers, further exacerbate these Ultra Risks by preventing vital knowledge from reaching those who need it when they need it, causing risks to remain invisible and undetected until they result in crises.

How can a business organization deal with such a situation?

To mitigate these Ultra Risks, businesses have developed various frameworks and case-study-based approaches, relying on a combination of questioning themselves, awareness, and collaboration. Examples:

The use of epistemic boundary spanners. These are individuals or teams who bridge knowledge communities within organizations, facilitating information sharing and critical dialogue across departments with different epistemic styles (e.g., managers, engineers, technicians, scientists).

The adoption of devil’s advocate inquiry models, as seen in venture capital due-diligence processes, where assumptions are rigorously tested and challenged one by one, rather than accepted at face value.

Large-scale information sharing platforms, such as the Xerox knowledge management system Eureka, created to facilitate knowledge sharing among service technicians and support representatives in a multinational environment.

The development of collaborative networks like (another) Eureka (usually abbreviated to “E!” or “Σ!”), a multinational organization created in 1985 to overcome localized funding, coordinate international research programs, and propel innovation.

These are examples of frameworks that emphasize fostering epistemic virtues—openness, reflexivity, collaboration, and building organizational cultures that value evidence-based decision-making and cross-disciplinary communication, thereby reducing the risk of undetected threats and improving collective learning.

It is tempting to consider AI tools to watch AI behavior. It is an ages-old situation, so much so that there is a Latin expression for it: Quis custodiet ipsos custodes? (Who will guard the guards themselves?). But from the cases listed in table 1 and other similar ones, it is known that LLMs change their behavior if they know that they are observed. This introduces considerations that deserve a longer treatment.

Given that the unknown will always be present and our faculties will always fall short of detecting UI strategies, we should identify and shield our businesses’ critical points into robust bastions, diversify judiciously into novel areas, and watch from the crenelations for signs of change. Easier said than done, but combining action with awareness will allow us (humans) to navigate uncharted territories.

If we fail to act now and we rely on “We’ll cross that bridge when we come to it,” we will be behaving like the person falling from a skyscraper who, when asked how things are going mid-fall, replies, “So far, so good.” Ultimately, these examples illustrate how distance—whether temporal, spatial, or personal—plays a major role in shaping our perception of risk, but that is a topic for another article.

In times of uncertainty, even if we cannot bring clarity into the opacity, we will say to Prince Hamlet, “Know thyself. That knowledge will make you resilient to continue forward.”

About the Authors

Dr. Claudio Antonini, MIT nuclear safety engineer, after working in the design of GNC systems for missiles and drones, has applied that numerical experience in the field of finance for the last 25 years. Working at UBS, he developed the largest global implementation of a genetic algorithm for banking, and has continued to apply data mining, machine learning, and artificial intelligence algorithms for risk management, in consultancies (Deloitte, AlixPartners) and the Bank of New York Mellon. He publishes consistently on forecasting topics.

Dr. sc. ETH Zurich Kamil Mizgier, Head of the Risk Management Office at the University of Zurich, brings his extensive practical experience and deep knowledge to explore challenges in strategic risk management. By leveraging his 15 years of expertise from key roles, including Global Supplier Relationship and Risk Management Leader at Dow and risk modeling leadership positions at BNY Mellon and UBS, he delves into the latest trends, tools, and techniques in risk management, offering invaluable perspectives that bridge academic rigor and practical application.

References:

1. The Alignment Problem from a Deep Learning Perspective, Richard Ngo et al., Mar-03-2025, https://arxiv.org/abs/2209.00626v7

2. Society of the Mind, Marvin Minsky, Simon and Schuster, 1986 and “HAL’S Legacy – 2001’s Computer as Dream and Reality,” David G. Stork (Ed.), MIT Press, 1997, pp. 16-17 and p. 28. Minsky said, “The people building physical robots learned nothing.” Minsky (and Irving John Good, later, with subassembly theory, a modification of Hebb’s cell assembly theory) promoted the decomposition of cognitive functions in elementary processes that could later be combined arbitrarily to generate new complex effects.

3. AI – The Tumultuous History of the Search for AI, Daniel Crevier, 1993, p. 33.

4. Speculations Concerning the First Ultraintelligent Machine, Irving John Good, 1965.

5. Periods of prolonged financial stability promote risky business practices. This happens in succession: hedge finance (low-risk borrowing), speculative financing (refinancing), and Ponzi finance (asset appreciation). This progression makes the financial system increasingly fragile, culminating in a “Minsky Moment”—a collapse of asset prices triggered by excessive leverage and loss of confidence. In time, the cycle starts again.

6. Evo2: One Bio-AI Model to Rule Them All, Feb-20-2025, https://www.synbiobeta.com/read/evo2-one-bio-ai-model-to-rule-them-all. Also, Genome modeling and design across all domains of life with Evo 2, Garyk Brixi et al., Feb-19-2025, https://arcinstitute.org/manuscripts/Evo2

7. Lab records of how different LLMs reacted to shutdown directives: https://palisaderesearch.github.io/shutdown_avoidance/2025-05-announcement.html

8. The Basic AI Drives, Steve Omohundro, Proceedings of the 2008 conference on Artificial General Intelligence 2008: Proceedings of the First AGI Conference, Jun-20-2008, pp. 483-92.

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Higher education is facing unprecedented disruption as artificial intelligence reshapes the global workforce. Mariah Levin examines how AI is breaking the link between university education and secure employment, urging a shift toward innovation, entrepreneurship, and adaptable skills. Her analysis highlights why universities must evolve to prepare students for an AI-driven economy.

Last month, the CEO of Anthropic shared the expectation that approximately 50% of today’s entry level jobs are likely to disappear in the next five years, lost to AI. This is going to affect university-educated young people in particular. With AI breaking the link between education and the labour market, young people are going to be faced with fewer ways in which to prepare for a competitive workforce and a shrinking jobs market.

University education has previously been a way to secure better working conditions, wages, and career options. Young people around the world have aimed for social mobility through university systems, enabling an expanded middle class and for workers to leave low paying, precarious jobs for secure, predictable professions.

Today, this pact has broken down. In some parts of the world, such as Kenya, university graduates struggle to find employment after investing time and money into additional education. Education for its own sake is a valuable good, but it comes at an exceedingly high cost; education for employment is not currently fit for purpose and needs a revamp as we face new realities of AI.

We face at a critical moment in preparing young people for future work, to ensure that they have access to decent livelihoods. In today’s world, the critical skills for today’s economy are innovation and entrepreneurship. We cannot fully know what the economic future holds and how AI will evolve, but we can equip young people with the tools and mindset to adapt readily to change and create value from it. The ability to critically evaluate market needs, create services and products that fill gaps, face risks, and solve problems through creativity and networks are future- and AI-proof skills. It is daunting for young people to face such an unknowable, changeable future, as well as the entry-level jobs declining for white collar, university-educated people.

Entrepreneurship and self-employment will become the most promising path to income generation for the rising workforce, as it already is for many. As young people are an incredible source of productivity and innovation to any economy, it is our task to develop imaginative and practical training to direct their motivation and build their capabilities to take on unknowns with an entrepreneurial mindset.

As AI changes work opportunities for young people, there are three key ways in which to support them to forge new pathways to decent work and liveable wages:

1. Earlier exposure to labour markets: The best way for young people to make sure they are developing skills that matter and translate to the workforce is to remain consistently exposed to what the workforce needs. AI will require all types of skills, including those beyond coding and prompting, to further develop its relevance to various industries. Young people are well positioned to help existing companies to experiment and help establish new companies to drive value. Regular and effective exposure to existing labour market deepen understanding skills gaps and confidence in one’s ability to fill them.
2. Opportunities to fail: exposing young people to early and productive opportunities to fail means that their courage to pursue a great idea grows stronger. No entrepreneur or innovator has created something great without experiencing and overcoming many setbacks. Testing, piloting and re-doing is a critical part of the learning process. Too often, traditional education disincentivizes failure through grading. No student wants a failing grade, so find it better to stick with easy materials that guarantee success. This type of model will never produce a winning new idea. Instead, the courage to fail and keep learning should be rewarded. Just as a product is never completely perfect or finished, the aim of innovation training is to open space, build confidence and fine-tune skills for a mindset of constant improvement.
3. Connections to global peer network: failure is much easier to swallow when young people see others around them taking similar risks, learning and growing. What works in rural Kenya might also work in rural Italy, so collaboration across countries and communities sparks new applications of tried and tested ideas.

New technologies and global realities will affect the work environments of future generations at faster and faster speeds. We need to do our most to prepare them to land on their feet, with the best experience and education possible in this brave, unknown new world we are stepping into.

About the Author

Mariah Levin is Executive Director of beVisioneers: The Mercedes-Benz Fellowship. beVisioneers is a global fellowship that equips innovators aged 16 to 28 with the training, expert support and resources to bring their planet-positive ideas to life.

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By Dr Leandro Herrero

Is the future of the organization ‘Network First’? The knowledge base organization looks certainly more and more like a networkracy. We are moving from the prominence of hierarchies to understanding connectivity and collaboration as a real engine, and beyond words. All that will require many changes, including the way we lead.

In 1973 – a little while ago now – Mark Granovetter opened a new door in our understanding of human connection with his seminal paper The Strength of Weak Ties. He famously demonstrated that so-called weak ties — those looser relationships we might maintain with old colleagues or occasional acquaintances—often play a more significant role in our lives than the strong, close ones. You’re more likely to get a job lead, for instance, through someone you send a Christmas card to once a year than through the colleague sitting next to you. It was a counterintuitive truth — and a powerful one.

Jump forward a few decades, and the study of networks finds a new hero in Duncan Watts. His Small Worlds: The Dynamics of Networks between Order and Randomness (2003) brought public attention to the idea that, remarkably, any two people on the planet are separated by no more than six degrees. Hollywood, ever resourceful, tested this theory through “Six Degrees of Kevin Bacon,” where actors were connected to the titular star through six or fewer links of shared film credits.

These insights point to a world that is neither random nor rigidly ordered, but somewhere in between — where clusters of tightly-knit groups are joined by surprising, often serendipitous links. Network science tells us two things at once: that most nodes (or people) are close to each other through a short chain, and that those nodes tend to cluster. In other words, the world is both large and small, dense and sparse, and this applies as much to the social world as to the structure of the internet.

The Company as Two Coexisting Worlds

Despite these revelations, the world of business has been slow to adapt. While marketers rushed to exploit the ‘commercial use’ of social networks, few executives paused to consider what network theory could tell them about the nature of the organization itself.

Most companies still operate as if they were made of just one system: the formal one. The Formal Organization is what you find on the org chart: a tidy, hierarchical world of bosses and subordinates, authority lines, KPIs, and HR files. It tells you who gets paid, who gets promoted, and who gets blamed.

But squatting — often invisibly — within that world is another one altogether: the Informal Organization. This one is built on relationships, not reporting lines. It thrives on trust, influence, and informal authority. Here is where things get done — or don’t. It is where one turns not for a directive, but to understand “what’s really going on.” A healthy informal culture is one where oxygen flows freely. People can breathe.

Yet management theory, and the business schools that propagate it, have historically ignored this world — treating it as anecdotal or, at best, ‘interesting’. Peer influence was something that happened in school playgrounds, not in corporate corridors. “Peer pressure” was a warning sign, not a strategic lever. I exaggerate, of course, but only to make the point: only recently have we begun to acknowledge the immense power of informal networks inside organizations.

Now, perhaps inevitably, we risk turning in the opposite direction. The network is being idolized. Hierarchies, some argue, must die. But to paraphrase Twain, reports of their death are greatly exaggerated.

Networks and hierarchies are not binary opposites. They coexist. And if we reorient ourselves to recognize the power of networks — truly recognize it — we stand to benefit immensely.

Mapping the Invisible, Leading from the back of the room

Understanding networks means recognizing something fundamentally uncomfortable to most organizational designers: connectivity is not evenly distributed. People do not form tidy bell curves of influence. Quite the opposite. In most organizations, a small number of people are extremely well connected, disproportionately influential, and critically positioned. The rest are not. This is not an HR issue — it’s a Power Law distribution. And for those with a mathematical curiosity, it is as fascinating as it is disruptive.

Every sizeable organization should develop the capacity to map its own internal networks, uncover hidden influencers, and optimize peer-to-peer dynamics. Not for decoration, but to get work done more effectively. I advocate for Backstage Leadership — leadership that doesn’t command from the spotlight but curates the conditions for others to thrive behind the scenes. It is about enabling the fluidity of the informal, where the velocity of action often far outpaces the clunky machinery of the formal.

We are, I believe, in the post-adolescent phase of the network conversation. Networks are no longer a footnote or a gadget of IT teams. They are not merely a metaphor for ‘connection’ or a data set to be visualized on a dashboard. With today’s ability to scientifically map internal networks — and the emerging power of AI to help us use these maps intelligently — we now have the chance to rethink the very nature of work.

And yet, a word of caution. To my friends in the Excited Network Tribe: don’t forget that a vast proportion of human labour is not flexible, fluid, or virtual. Surgeons will not operate remotely. Care workers will not look after patients via Zoom. The man repairing the gas line outside my house will not be joining a Slack channel any time soon. Not to fix the pipes anyway.

About the Author

Dr Leandro Herrero is the Chief Organizational Architect at The Chalfont Project, Author, International Speaker and Psychiatrist. For the past 25 years, Dr Herrero and his team have been transforming culture in organizations via his pioneering Viral Change methodology. Follow Dr Herrero on LinkedIn for all the latest updates.

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By Scott Hutcheson

Emotional intelligence is often described in vague or idealistic terms, but its real power lies in how it shows up moment to moment in tone, timing, posture, and behavior. This article explores emotional intelligence through the lens of behavioral biology and shows what it looks like when practiced with signal clarity.

What Emotional Intelligence Really Looks Like in Action

Emotional intelligence is often described as the ability to recognize, understand, and manage one’s own emotions while also recognizing, understanding, and influencing the emotions of others. This two-part framework, popularized by Daniel Goleman, has shaped leadership development for decades. But for many leaders, the concept still feels abstract and more like a personality trait than a set of observable actions.

What’s missing from most discussions of emotional intelligence is what happens between awareness and impact. Emotion is not just a feeling. It is part of a biological sequence. Leaders who understand this sequence can manage their behavior in ways that shape performance, trust, and engagement in real time.

The Biology of Behavior and Emotional Intelligence

Emotions begin in the body. A leader sends a signal through tone, posture, language, or timing. That triggers a physiological reaction in others. The nervous system responds first, activating energy across systems like the heart, lungs, and digestive tract. This energy isn’t metaphorical. It involves real changes in breathing, heart rate, and gut tension, often directed by the autonomic nervous system.

Those physiological shifts prompt a cascade of neurochemical responses. Depending on the nature of the signal and the context, the body may release cortisol, dopamine, norepinephrine, or oxytocin. These chemicals help the brain interpret what the body is experiencing. The result is a felt emotion. Trust, anxiety, curiosity, or defensiveness, to name just a few That emotion shapes behavior, which becomes visible through actions, expressions, and engagement.

Finally, the leader can observe that behavior and adjust their signal if it is not producing the intended effect. This five-part loop forms the Biology of Behavior Cycle:

1. Leadership signal
2. Physiological reaction
3.  Emotion interpreted by the brain
4. Behavior
5. Leader observes behavior and adjusts signal

This is not metaphor. It is how social behavior works. The body responds before the brain constructs a feeling. And that feeling becomes behavior, setting the emotional tone of a room long before any content is processed.

Emotional Intelligence Is Observable

Leaders often talk about emotional intelligence as something to cultivate. But few describe what it actually looks like.

It looks like pacing your speech intentionally when tensions rise. It looks like adjusting your tone when you sense fatigue or confusion in the room. It shows up in how you listen without interrupting, and how you pause before speaking to let others catch up or settle in.

These are not soft or vague behaviors. They are observable, trainable, and grounded in biology. Others interpret your presence long before they evaluate your strategy. And they behave accordingly.

Signal Clarity Is the Real Skill

Most emotional intelligence models focus on internal awareness. But in behavioral terms, what matters most is signal clarity, whether the emotional message others receive is consistent with your intent.

When a leader expresses appreciation but remains visibly distracted, the signal is unclear. When someone encourages openness but communicates judgment with body language, the signal backfires. Signal clarity is not about perfection. It is about alignment between what you intend and what others perceive.

Clarity builds trust. Trust makes collaboration easier. Over time, that consistency shapes group norms and performance patterns.

How to Practice Emotional Intelligence Through Behavior

Instead of treating emotional intelligence as a mindset, consider treating it as a set of micro-behaviors that shape how others feel and respond. These practices allow you to shift from passive awareness to intentional influence.

1. Anchor your physiology

Your nervous system broadcasts signals constantly. Before important moments, take a breath. Adjust posture. Let your physical state match your desired message.

2. Set emotional intent

Ask, “What emotional tone do I want others to feel in this moment?” Use that to guide how you show up—your timing, phrasing, and level of energy.

3. Observe others’ behavior

If people become quieter, more guarded, or disengaged, consider whether your signals might be contributing. Look for nonverbal cues, not just spoken feedback.

4. Adjust in real time

When your behavior is not producing the outcome you hoped for, shift. Acknowledge it. Calibrate your next move. This responsiveness is one of the most respected forms of leadership.

Emotional Intelligence Shapes Systems

Framing emotional intelligence as a behavioral process helps explain why it matters. The signals leaders send affect how others feel, and those feelings shape how others behave. Over time, this process sets the emotional tone of the team and, eventually, the culture of the organization.

The stakes are high. When signals create uncertainty or tension, cognitive resources are drained. Teams struggle to focus or adapt. When signals create coherence and psychological safety, teams align more quickly and perform more effectively.

What distinguishes emotionally intelligent leaders is not how much empathy they feel, but how consistently they regulate the signals that shape group behavior.

About the Author

Scott Hutcheson, PhD, is a professor at Purdue University and author of Biohacking Leadership: Leveraging the Biology of Behavior to Maximize Impact. He specializes in leadership, team, and organizational performance through the lens of behavioral science and human ecosystems. Learn more at www.biohackingleadership.com.

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By Dr. Simon L. Dolan, Dr. Mario Raich, and Pedro César Martínez Morán

The best thing ever to happen to humanity – or the worst? The predictions for the impact of AI range from the euphoric to the apocalyptic. Where does the truth lie? Perhaps everything depends on those driving its adoption.

The conversation surrounding AI-driven automation is one permeated with fear and uncertainty, as many visionaries have foreseen the profound disruptions it could inflict on our labor markets. Their words echo with a somber resonance, reminding us of the precarious balance between technological advancement and the well-being of countless individuals.

Albert Einstein once said, “I fear the day that technology will surpass our human interaction. The world will have a generation of idiots.” This stark warning encapsulates a growing concern — that our pursuit of efficiency will undermine the fundamental essence of human contribution in the workforce. Imagine a future where machines replace the very hands that toil, rendering people expendable and relegating their aspirations to dust.

Moreover, the late Stephen Hawking articulated a chilling vision: “The rise of powerful AI will be either the best or the worst thing ever to happen to humanity. We do not yet know which.” His words resonate deeply, trembling with the weight of existential dread. As we rush toward an era driven by algorithms and automaticity, we are left to ponder: who will remain at the heart of the labor market? Will our dreams of productivity lead us to a dark abyss of unemployment, where human touch is deemed obsolete?

Elon Musk, a fervent advocate for caution in the face of AI technology, hauntingly warned, “I think we should be very careful about artificial intelligence. If I were to guess at what our biggest existential threat is, it’s probably that… With AI, we are summoning the demon.” His metaphor serves as a reminder that with our relentless quest for innovation, we might unleash forces we cannot control. As machines increasingly supplant jobs, we risk surrendering not only our livelihoods but also our sense of purpose.

The truth is, the march of technology is relentless, and the toll it has on the workforce can feel insurmountable. As we stand on the precipice of this brave new world, we find ourselves embroiled in a moral quandary: how do we safeguard the dignity of work in an age where the machines are rising? Will we allow the fear of joblessness to transform our society into one where purpose is lost, replaced solely by automation’s cold efficiency? It is a future that beckons with both promise and peril, and it is one that demands our urgent reflection.

Pessimistic Vision: The Fear of Job Displacement

Critics argue that AI-driven automation will disrupt labor markets, rendering millions jobless. Routine tasks in manufacturing, customer service, transportation, and even white-collar sectors like law and finance are increasingly automated. A seminal Oxford study by Frey and Osborne (2013) estimated that 47 per cent of U.S. jobs are at high risk of automation. Nearly 10 years later, “jobs with a high risk of automation constitute approximately 27 per cent on average across OECD countries” (source: https://www.cesi.org/posts/oecd-27-of-jobs-at-high-risk-from-ai/).

AI’s rapid advancement, unlike previous technological shifts, may outpace workers’ ability to adapt, exacerbating inequality. As economist John Maynard Keynes warned in 1930, “technological unemployment” arises when “the discovery of means of economising the use of labour outrun[s] the pace at which we can find new uses for labour.” Critics like Elon Musk caution that AI could create a “jobless underclass,” while Stephen Hawking feared it might become “the worst event in civilization’s history” if mismanaged.

Here are some pessimistic quotes from notable figures who have expressed concerns about AI-driven automation and its potential to disrupt labor markets, leading to widespread job losses:

• Stephen Hawking (theoretical physicist): “The automation of factories has already decimated jobs in traditional manufacturing, and the rise of artificial intelligence is likely to extend this job destruction deep into the middle classes, with only the most caring, creative, or supervisory roles remaining.”
• Elon Musk (CEO of Tesla and SpaceX): “AI is a fundamental existential risk for human civilization, and I don’t think people fully appreciate that. It’s capable of vastly more than almost anyone knows, and the rate of improvement is exponential. We need to be super careful with AI. It’s potentially more dangerous than nukes.” And moreover: “There will be fewer and fewer jobs that a robot cannot do better. These are not things that I wish will happen. These are simply things that I think probably will happen.”
• Bill Gates (co-founder of Microsoft): “Software substitution, whether it’s for drivers or waiters or nurses… it’s progressing… Technology over time will reduce demand for jobs, particularly at the lower end of the skill set.”
• Andrew Yang (entrepreneur and former U.S. presidential candidate): “The truth is that automation is already here, and it’s already destroying jobs. The pace of job destruction is only going to accelerate in the coming years, and we’re not prepared for it.”
• Yuval Noah Harari (historian and author of Sapiens): “As artificial intelligence outperforms humans in more and more tasks, it will replace humans in more and more jobs. Many new professions are likely to appear—virtual-world designers, for example. But such professions will probably require more creativity and flexibility, and it is unclear whether 40-year-old unemployed taxi drivers or insurance agents will be able to reinvent themselves as virtual-world designers.”
• Martin Ford (futurist and author of Rise of the Robots): “The real threat is mass unemployment—or, at the very least, a future in which a great many people simply cannot find work because they have been displaced by machines and there are no new jobs to replace the ones that have been lost.”
• Noam Chomsky (linguist and political activist): “The development of full artificial intelligence could spell the end of the human race. It would take off on its own and redesign itself at an ever-increasing rate. Humans, who are limited by slow biological evolution, couldn’t compete and would be superseded.”
• Kai-Fu Lee (AI expert and author of AI Superpowers): “AI will increasingly replace repetitive jobs, not just for blue-collar work but a lot of white-collar work. The disruption will be profound, and we need to think about how to prepare for a world where a significant portion of the population is unemployable.”

Optimistic Vision: Adaptation and New Opportunities

History, however, suggests resilience. The Industrial Revolution, despite displacing agrarian workers, birthed factories, railways, and urban services, ultimately raising living standards. Similarly, AI will eliminate some roles but spawn new industries. The World Economic Forum (2020) predicts that AI will create 97 million new jobs by 2025, including roles in AI ethics, data science, and human-machine collaboration. For instance, while self-driving trucks may reduce driving jobs, they will increase demand for logistics analysts and remote fleet managers. And, further, an IMF report found that AI will impact 40 per cent of jobs worldwide. In advanced economies, this figure rises to 60 per cent, with roughly half experiencing negative effects (Cazzaniga et al. 2024).

In a world rapidly transforming through the lens of artificial intelligence, it’s easy to feel a twinge of anxiety over the future of work.

AI’s true potential lies in augmenting human capabilities, not replacing them. Erik Brynjolfsson, an MIT economist, argues that “AI can be a tool to complement human creativity,” enabling workers to focus on complex problem-solving and innovation. Education and reskilling programs will be critical. David Autor, a labor economist, notes that “automation reshapes work, but rarely eliminates it,” emphasizing that technology historically creates more jobs than it destroys.

In a world rapidly transforming through the lens of artificial intelligence, it’s easy to feel a twinge of anxiety over the future of work. Yet, amidst these uncertainties, voices of optimism rise above the noise, reminding us of the boundless opportunities that lie ahead. Some of our greatest thinkers and leaders have expressed powerful sentiments about AI-driven automation, shedding light on a hopeful narrative that encourages us to embrace this evolution with open hearts and open minds.

Consider the words of Satya Nadella, CEO of Microsoft, who once said, “Our industry does not respect tradition—it only respects innovation. We can innovate our way into a better future.” This sentiment speaks to the heart of what AI can accomplish. It is not merely a tool to replace jobs, but a gateway to new realms of innovation. As automation takes over mundane tasks, our creative capacities are freed—from the mundane to the magnificent.

Jacques Attali, the French economist and former advisor to President François Mitterrand, propounded a hopeful vision for the future when he stated, “The future will be about silicon and minds, about man-machine cooperation.” His insight urges us to envision a world where the relationship between humans and technology is one of collaboration, not conflict. The journey ahead is not about pitting man against machine but rather weaving a fabric of teamwork that harnesses the strengths of both to tackle challenges head-on.

And as we stand on the precipice of this adventurous journey, let us hold dear the words of Sheryl Sandberg, COO of Facebook: “Leadership is about making others better as a result of your presence and making sure that impact lasts in your absence.” This philosophy of leadership is crucial in an AI-driven world, where it is our collective responsibility to mentor and uplift one another. We must ensure that the transformation does not lead to division but fosters an inclusive community where everyone can thrive.

The essence of these quotes encapsulates a future filled with promise and possibility. We must remember that automation is not an end, but a beginning—an opportunity to redefine human work and elevate one another. Let us boldly step forward, arms intertwined and hearts open, as we collectively shape the landscape of tomorrow. The power to transform our futures lies in our hands, guided by hope, innovation, and a shared vision of a prosperous world for all.

Here are some additional optimistic quotes from notable figures who have expressed positive outlook about AI-driven automation and its potential to enhance well-being in civilization and create tons of new jobs that will compensate for the routine, boring and manual work:

• Mark Zuckerberg (co-founder and CEO of Meta): “AI is going to make our lives better in the future, and it’s already improving our lives today in many ways. We’re going to have more tools to solve big problems, create new opportunities, and improve the quality of life for people around the world.”
• Satya Nadella (CEO of Microsoft): “AI is one of the most transformative technologies of our time, and it has the potential to help solve some of the world’s most pressing challenges. It’s not about man versus machine; it’s about man with machines. We need to think about how we can use AI to augment human capabilities and create new opportunities for everyone.”
• Fei-Fei Li (AI researcher and professor at Stanford): “AI is not going to replace humans; it’s going to augment humans. The future of work is not about humans versus machines; it’s about humans working alongside machines to achieve things we couldn’t do before.”
• Ginni Rometty (former CEO of IBM): “AI will not destroy jobs; it will change them. Every job will be augmented by AI, and new jobs will be created that we can’t even imagine today. The key is to focus on reskilling and upskilling the workforce to prepare for this future.”
• Andrew Ng (AI pioneer and co-founder of Coursera): “AI is the new electricity. Just as electricity transformed almost everything 100 years ago, today I have a hard time thinking of an industry that I don’t think AI will transform in the next several years. This will create new opportunities and improve productivity across the board.”
• Jensen Huang (CEO of NVIDIA): “AI will create more jobs than it displaces. It will enable entirely new industries and opportunities that we can’t even envision today. The key is to embrace the technology and invest in education and training to prepare the workforce for the future.”
• Erik Brynjolfsson (economist and Director of MIT’s Initiative on the Digital Economy): “Technology is not destiny. The future of work depends on the choices we make today. AI and automation can lead to greater productivity, higher wages, and more leisure time if we manage the transition wisely. The challenge is to ensure that the benefits are widely shared.”
• Reid Hoffman (co-founder of LinkedIn): “AI will not eliminate jobs; it will transform them. The future of work is about humans and machines collaborating to achieve more together than either could alone. The key is to focus on lifelong learning and adaptability.”
• Ray Kurzweil (futurist and inventor): “AI will augment human intelligence and create new opportunities for innovation and creativity. It’s not about replacing humans; it’s about enhancing our capabilities and enabling us to solve problems that were previously unsolvable.”

These quotes reflect a more hopeful perspective on AI-driven automation, emphasizing the potential for collaboration between humans and machines, the creation of new industries, and the importance of education and adaptability in navigating the future of work. While challenges remain, these voices argue that AI can be a force for positive change if managed thoughtfully.

Conclusion and a Strong Message to Future-Shapers

While AI will disrupt certain sectors, humanity’s capacity to adapt is enduring. By investing in education, social safety nets, and policies that promote equitable access to new opportunities, societies can harness AI’s benefits. As with the Industrial Revolution, fear of obsolescence is natural but unwarranted. As economist Joseph Schumpeter observed, technological progress involves “creative destruction”—a cycle of renewal that ultimately drives prosperity. The future need not be bleak if we proactively shape it.

As robots and intelligent machines increasingly take the reins of production and value creation, we stand on the precipice of a profound transformation—one that calls for new mechanisms of value sharing, potentially paving the way for a groundbreaking economy and business paradigm. This shift compels us to contemplate the very essence of work, which has already begun to evolve and will continue to do so. Work should not merely be a means to an end; it is fundamentally about addressing human challenges, delivering essential products and services, and ensuring a dignified quality of life for everyone who desires it.

Quality of life encompasses our deepest values and the fulfillment of our unique journeys in life. It’s about chasing dreams, nurturing our passions, and fostering connections that enrich our existence. Kate Raworth’s groundbreaking work, Doughnut Economics, published in 2017, resonates powerfully in this context. She brilliantly challenges us to rethink our economic systems by posing a vital question: How can we transform economies driven by relentless growth into ecosystems that enable all of us to thrive, irrespective of their growth rates? This is not just an economic inquiry; it’s a heartfelt call to reimagine our priorities, to build a future where the fruit of our labor nourishes our souls and uplifts our communities, ensuring that no one is left behind. Let us embrace this opportunity for change with open hearts and minds, forging a path toward a more humane and nurturing world.

Viewing only paid activities as work is a grave misconception that diminishes the true essence of what it means to contribute to society. We must embrace a broader definition that recognizes all meaningful endeavors—those that enhance life quality and create enduring values—as vital forms of work. This perspective includes the invaluable contributions made through education, nurturing minds and souls for a better future.

Today, the relentless dance of growth and greed continues to ensnare our economy in an unbreakable grip, perpetuating the illusion of endless expansion. Profit has become the singular, dominant measure of success for businesses, often at the devastating expense of the ecosystems upon which our survival depends. Meanwhile, bureaucratic red tape suffocates innovation, fueling the chaos within organizations. Misguided entrepreneurs, chasing the mirage of limitless profit, have turned their enterprises into something akin to a cancer, threatening the very fabric of our economic health.

As we strive to produce faster, cheaper, and more efficiently, we inadvertently strip away the human element—the workers who are also our consumers. Unemployment rises, leading to diminished purchasing power and an increased social burden that affects us all. The stark truth emerges when jobs vanish, so too do consumers and taxpayers. This connection is undeniable: “No work, no economy.”

The fallout isn’t just economic; it’s profoundly social. We witness a dangerous polarization within our communities, leading to fractures that threaten our cohesion and provoke unrest. It’s time for a profound shift—one that redefines our perception of the economy, business, work, and the values that govern our lives. In an age where robots and intelligent machines take over vast swathes of production and value creation, we must forge new mechanisms for sharing the wealth generated by these advancements. We need a revolutionary reimagining of our economy, one that prioritizes human dignity over blind profit and cultivates a future in which every individual can contribute meaningfully, thrive, and find purpose. The journey is challenging but, together, we can pave the way to a more equitable and harmonious world for all.

About the Authors

Dr. Simon L. Dolan is currently a professor and Senior Director of Research and Programs at Advantere School of Management (Madrid) and the President of the Global Future of Work Foundation. He was formerly the Future of Work Chair at ESADE Business School in Barcelona. He taught in many North American business schools, such as Montreal, McGill, Boston, and Colorado. He is a prolific author, with over 85 books on themes connected to managing people, culture reengineering, values, coaching, stress, and resilience enhancement. In 2024 he was awarded a doctorate honoris causa (University of Huelva) and the IFSAM Award for Excellence in Societally Relevant Management Scholarship. He has published over 170 papers in scientific journals. He is an internationally sought-after speaker. His full CV is at: www.simondolan.com.

Dr. Mario Raich is a Swiss futurist, book author, and global management consultant. He has been a senior executive in several global financial organizations and an invited professor to leading business schools, including ESADE (Barcelona). He is the co-founder and Chairman of e-Merit Academy and Managing Director of Raich Futures Studies in Zurich. In addition, he is a member of the advisory board of the Global Future of Work Foundation in Barcelona. Currently, he is researching the impact of cyber-reality and artificial intelligence on society.

Pedro César Martínez Morán is the Director of the Master in Talent Management Faculty at Advantere School of Management, affiliated with Comillas, Deusto and Georgetown Universities (www.advantere.org). He is a professor of Human Resources and researcher and scientific reviewer in Human Resources and Talent Management. Dr. Martínez Morán is an author and speaker on people management.

References

• Autor, D. H. (2015). “Why Are There Still So Many Jobs?”, Journal of Economic Perspectives. vol. 29, issue 3, 3-30

• Brynjolfsson, E., & McAfee, A. (2014). The Second Machine Age: Work, progress, and prosperity in a time of brilliant technologies. W.W. Norton & Co.

• Cazzaniga, M., Jaumotte, M. F., Li, L., Melina, M. G., Panton, A. J., Pizzinelli, C., and Tavares, M. M. (2024). “Gen-AI: Artificial intelligence and the future of work”. International Monetary Fund.

• Frey, C. B., & Osborne, M. A. (2013). “The Future of Employment”. Published by the Oxford Martin Programme on Technology and Employment, University of Oxford. extension://efaidnbmnnnibpcajpcglclefindmkaj/https://oms-www.files.svdcdn.com/production/downloads/academic/future-of-employment.pdf

• Keynes, J. M. (1930). “Economic Possibilities for Our Grandchildren”, in Essays in Persuasion (New York: Harcourt Brace, 1932): 358-373 (extension://efaidnbmnnnibpcajpcglclefindmkaj/https://www.aspeninstitute.org/wp-content/uploads/files/content/upload/Intro_and_Section_I.pdf)

• Raich M., Klimek J., Dolan, S.L. Cisullo C., and Klimek S. Shaping Our World (Forthcoming Fall 2025)

• Raworth K. (2018) Doughnut Economics: The must-read book that redefines economics for a world in crisis. Random House.

• World Economic Forum. (2020). The “Future of Jobs” Report. (The Future of Jobs Report 2020 | World Economic Forum)

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By Adrian Furnham

A good education is all very well, but there are some lessons you can’t learn in the classroom. Adrian Furnham recounts his most valuable extra-curricular experiences – in the world of employment.

I had the same job at the same place for nearly 40 years – a whole working life. I was lucky; I found a job which suited my ambitions, temperament, and values. But, like everyone else, I had short, holiday, and part-time jobs which taught me a great deal about the world of work. They helped me find my real vocation, passions and, more importantly, dislikes. They taught me about skiving, liberating stock, and what good supervision and management looks like.

I went to university too young; I was 16 when I arrived. When parents come to me now for advice about their children’s choice of course or university, I recommend what used to be called a “gap year” between school and university. I recommend the same between under- and post-graduate degree. The University of Life has a lot to teach one. Work, of all sorts, helps one reflect on, and understand, one’s personal preferences and strengths.

Book Warehouse Worker

It was expected by my parents (and, indeed, the society in which I grew up) that one spent the long summer university holiday (December to early February in South Africa) at work, saving some money for the year ahead. At the end of my first year, I got a job in a local publisher warehouse at the other end of town. It was situated among light industry, including Nestlé chocolates and Gilbey’s gin. I cycled there in about 20 minutes. I do not recall how I got the job or what the pay was like, but I had some surprises.

The first was that my boss was black – unheard of, and probably illegal in apartheid South Africa. The company (Shuter and Shooter) were very liberal publishers, printers, and booksellers with a big market in school books. The owners were educated, kindly, but shrewd progressives who had the opportunity in a small way to practise what they preached.

My Zulu-speaking boss was called Gideon and was a confident and educated middle-aged man. He was firm but fair, slightly distant but very eager to show who was boss. I was impressed. He commanded respect and got it.

I slowed down, nattered to co-workers, began to understand how to be a “good worker”.

The second lesson was about rate-busting and productivity. One of my first tasks was to write the price of a huge pile of books in pencil on the inside page. That dates me; the year was 1971. It had to be clear and neat. I did as I was instructed and reported back to the boss in two hours. This caused consternation in the whole team. The job I had been given was for “the whole day”, perhaps a day and a half. I was clearly naïve and shocked but learned the lesson. I was a rate-buster. I slowed down, nattered to co-workers, began to understand how to be a “good worker”.

The third was about “skiving off”. One day, three of us were asked to deliver some books in the country. It involved driving the old delivery van to some rural outposts, a round trip of around 80 miles. We set off at 08:00 and had finished all our tasks at 12:15. We could not go for much of a “jolly” because the mileometer was checked. But we were not far from a lovely country town in the foothills of the great Drakensburg mountains. One of the group knew a hotel with a jolly outdoor pub. So we spent three hours drinking beer and later put in a claim for lunch. Drink-drive restrictions were unheard of. What a wheeze.

Male Nursing Assistant

My mother wanted me to become a doctor. I expressed no interest. But, because she was the matron in the local hospital (Greys, Pietermaritzburg), I had a job for three summers as a male nursing assistant. The job was male orderly, expected to do a range of menial, physical jobs. On my first day, I had to “shave a male” (it was called a “nipple-to-knees”) and I carried an amputated leg to the mortuary.

The job was very varied. I had to hold down patients having ECT. I enjoyed putting on, and cutting off, plaster on arms and legs. But being located in A&E, it was a bit like being a pilot – long periods of boredom interspersed with emergencies. I had to deal with drunks, aggressive patients, and visitors who would not follow the rules.

I witnessed great compassion and what looked like great callousness by the nursing staff. I learned how to protect myself from the events I witnessed: a patient “dying on the table”; a woman giving birth to a “child asleep”; and patients in wards who never had visitors.

I made contact with people from very different backgrounds compared to my own. I saw what my father called “how the other half live”. I certainly saw how hierarchies worked, from the surgeons to cleaners. Our tea room was for orderlies, painters, and other “skilled craftsmen”, who were in protected jobs in a whites-only hospital. We liberated “left-over” sandwiches from the doctors’ tearoom and swam in the hospital swimming pool reserved for nurses.

After two months, I longed to get back to university, to spend time in the library and, yes, even to write essays. I found the hospital work both boring and emotionally taxing. It certainly confirmed to me that I was not cut out to be a doctor.

School Teacher

I had a friend in my honours year who became a school teacher and school counsellor straight after graduation. He was older than us (early 30s), English by birth and upbringing, and rather eccentric. In retrospect, I would diagnose him as a vulnerable narcissist, with a few schizotypal tendencies. He lived in a shabby caravan and (as I discovered from the website of his wife) went on to a variety of jobs (HR, teaching) but ended up as a “pastor” in a local church and having six children.

He suddenly left his job, telling me about it a few days before resigning. It was my old school and I knew people there. It was a relief for them that I could easily slip into the role – a win-win.

I had two roles: I was a school counsellor and taught English. I was not very good at either. I learned probably more from the boys than the teachers. Most of the teachers were totally committed, many being obsessed with sport. Apart from a short time at university, they returned to the “total institution” nature of the school. They liked the structure, the rules, and the predictability of everything. I did not.

I got to know a few of the “problem boys” quite well because of my job. I diagnosed and helped a few dyslexics, at which point I found I was marginally dyslexic myself. I wanted to test the boys on a range of psychological tests, but the headmaster resisted this

I coached cricket and tennis, without much enthusiasm or skill. And I certainly was not an inspirational English teacher. I had done one year at university and never enjoyed it, except for poetry. Interestingly, all the senior staff (head and two deputy heads) were maths teachers, but the heroes were those who coached the first fifteen rugby team.

I saw how the game worked: become head of a discipline, leave for a rural school as deputy head, and return to a bigger, better cosmopolitan school in one’s late fifties. Perhaps pick up an education degree as you went.

It wasn’t for me. Some of the children were delinquently obstreperous. I hated marking essays and I wasn’t sporty enough to fit in.

British Rail Bouncer

I was not a happy student in Glasgow. I did not enjoy the course, which did not challenge me, and, as I was about to go to Oxford the next academic year, I guessed I would certainly need quite a lot of money to enjoy myself in the city of dreaming spires (or spiralling dreams, as we got to call it). I worked out that I could easily do evening shifts and set out to get a National Insurance number, a basic requirement for work in the UK.

My hall of residence was in the centre of town and I saw an advertisement for a “security officer” at the local railway station dining area (Glasgow Central), a five-minute walk away. My hours were 18:00 to 23:30, which suited me just fine. I could go to lectures, and then walk to and from work. The place had two bars, each staffed by two people, and a “restaurant”, which had three people (all late-middle-aged women) in the kitchen and two serving at a counter.

One lesson involved understanding the power of friendship at work. What I learned from the kitchen ladies was that, after a recent political change in tax, insurance, and social security, each would have been financially better off quite legitimately staying at home and claiming benefits than coming to work, often at anti-social hours. But work gave them a structure to their lives, and a friendship network.

Interestingly, I witnessed the same thing as a student at Oxford. The psychology department was very large and designed as a hotel. There was a cleaning staff of around eight people and I befriended two, who were responsible for my section: Betty and Fred. Fred had been in the Great War and had been a head gardener somewhere nearby. A lovely man – warm, kind, and deeply respectful. A new manager had looked at the staff and noticed that most were in their 70s and some in their 80s. He “suggested” they retire. I had never seen a grown man, an old soldier, weep. He pleaded to stay but was refused and died less than a year later.

Work is good for you. I had understood the social function of work. Understood why people worked even though worse off.

Perhaps unexpectedly, the bouncer job required that I join the National Union of Railwaymen. Soon after I joined, there was a strike concerning “flexible rostering”. I had tended to be antagonistic to a number of rail strikes, being a “helpless victim”. However, when I learned what this was about, I joined my fellows and the station was practically closed. The issue was that staff had to be flexible with regard to their work timetable. This meant you could never plan ahead, as you had no idea which days you were working in the next month. Good for the managers, sure, but not the staff. The strike worked.

I learned again that everyone was “on the make” in a small way, exploiting what opportunities came their way.

Thirdly, I learned something about “ladies of the night”. The station was a “pickup joint”. The ladies were divided into three categories, according to their charges. The cheapest could be literally physically removed, the most expensive charmed away. The really difficult ones were those in the middle group, particularly if drunk. They would shout at me from being a ‘horrid Sassenach’ or a customer who did not pay for their services. I had to learn how to be firm and persuasive.

I also learned how tedious and menial certain jobs were. I learned that dealing with members of the public was no fun. I learned again that everyone was “on the make” in a small way, exploiting what opportunities came their way.

Part-Time Lecturer

I was a foreign student. All my friends were on student grants which were, I thought, incredibly generous. But I had no source of income and no capital, except for what I saved. So when some “part-time / occasional” lecturing jobs came up I jumped at them. I gave lectures to firemen, nurses, occupational therapists, policemen, and supervisors.

I learned first how different this was from academic teaching; they did not want theory, evidence, critique, but some pretty straightforward ideas and skills. I learned the power of anecdotes, stories, and case studies, which was harder for an inexperienced 25-year-old.

I learned that, for some, training was a punishment, while for others it was a reward. Some were sent on a course (because they had low EQ or motivation) to miraculously acquire some skill in three hours. Others were let off the tedium of the job to be amused by an aspiring academic. I learned that you need a rich mix of lecturing, discussion, exercises, videos.

I got better and became a sort of part-time lecturer at what was then Rewley House, in Oxford. Many of the people on the course were “general workers” (yes, that was their title).

But I remember one event best. I got better and was trusted to do a day-long course. It was in Banbury and the pay was excellent. I hired the departmental van and got there early. My class were night-time supervisors at the local biscuit factory, and the course ran at a central hotel. I soon learned that the day was seen as a “jolly”. There were about 12 people and my topic was supervisor skills.

Tea was brought on a trolley, as was lunch. To my surprise, two trolleys were brought in at 12:30 – one food, the other booze – beer, wine, spirits. I had negotiated with the group that we had a shorter lunch and finished earlier. Everyone tucked in and most took a bottle of beer.

After lunch I showed a video, one of those wonderful Video Arts John Cleese films. After a few moments, one delegate went up to the trolley, poured himself a generous whisky, and joined the group. Clearly, he was used to “watching the box with a bevvy”. A few joined him and I did not know what to do, so ignored the issue.

The course finished around 16:30 and I left immediately, as it was a difficult drive. I later discovered that after I left they had all stayed and drunk the trolley dry, so wiping out all profits for the university. Naturally they rated the course as excellent.

I learned the idea of “edutainment” and that people want stories. I know the plural of anecdote is not evidence, but I have seen how a number of well-paid gurus perform with bravado and bluff. It was a useful skill.

Business Consultant

I got my career position (1981) at a time when there was a serious financial situation, particularly so at universities. A number of my very talented colleagues could not get jobs. A few resigned from their academic jobs soon after they took them up, disillusioned with the academic life. They started business consultancies and they needed “contract staff” or “associates” in busy periods or for big projects. It was ideal for me and for them. They liked the fact that I was an academic with a PhD and the daily rate was about what I got a month as an academic.

I had this type of relationship with different groups for many years. It often involved exotic travel, as one group specialised in airlines. I travelled to Hong Kong over 100 times (nearly always in a first-class seat) and New Zealand half a dozen times. I was an associate of three different consultancies, all doing well, so I was kept quite busy.

There were essentially three types of assignments: on-stage, inspirational lectures; day- to week-long training courses; and individual assessment and coaching exercises.

I certainly learned that the academic training I had was of little use. Consultancies used tests and procedures that had been shown to be unreliable and invalid. They seemed quite uninterested in evidence, particularly if it went against the zeitgeist, or clients did not like it. This made it difficult for me. I was teaching students the importance of test validity, but learned that if the client wanted a particular well-known yet discredited test, they got it.

I learned that giving an upbeat keynote business conference speech was rather different from a lecture. The lecture was slide- and reference-heavy, full of doubt and critique. A good keynote must be inspirational, which means making statements and promises that are upbeat, simplistic, and perhaps evidence-free.

I learned that many businesses want magic dust. They want a “culture change” in a few months with no pain. They want on-the-spectrum technical managers to acquire emotional intelligence after a couple of hours of coaching. They want the organisation to have a “resilience sheepdip” to reduce job stress, and absenteeism will dramatically decrease.

I learned that the client / customer is king, as they paid your salary. I learned also that they differed dramatically in terms of insight, sophistication, and expectations.

And the Moral of the Story

It is not easy to find that sweet spot between what you are good at, and what organisations suit you best. The more early experience you get, the better. As Bill Gates says, “Life is not fair – get used to it.”

So, while at school and university, do holiday jobs. Think of it as vocational guidance. Of round and square pegs and holes.

Postpone university, so that you can gain some real-world experience before studying. If you can find an activity that you love and that speaks to your talents and values – and that pays you (enough) – you are lucky indeed.

About the Author

Adrian Furnham, a chartered work psychologist, lectured at University College London for 37 years, as well as at different universities, including the Norwegian Business School, where he taught for 15 years. He founded a still-successful company in 1986 and has written 100 books.

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The Energy Transition is an enormous opportunity for Europe to harness its millennia of engineering expertise and lead the world in addressing the existential issues of the 21^st century: sustainability and the energy transition. Simply put, sustainability is living within our means while the Energy Transition does just that, doing more with less. Two sides of the same coin.

One truly significant initiative, and central to a successful energy transition, is the widespread adoption of District Heating. While European governments at all levels, energy providers, and energy consumers are for once all aligned, the true drivers of the transition are the innovative and pragmatic engineering solutions from such industry leaders as ISOPLUS.

This is great news for the continent.

Europe’s Opportunity, the World’s Gain

– Professor Jeffrey Sachs, Columbia University

Public policy analyst and former director of The Earth Institute, expert on the topics of sustainable development and economic development. Speech to the European Parliament in May, 2025.

The Energy Transition is the most important initiative in the history of the world and the ambition needed to implement it is daunting. The stakes couldn’t be higher, as well as securing our own future and that of our children, the Energy Transition is also an opportunity to establish European energy independence. The urgency of this has been made starkly evident by recent events in Europe and their geopolitical impact.

There is very good news though. Europe does indeed stand for climate action and much progress has been made in many areas. The most significant is District Heating — it has been recognised across Europe as a cost-effective shortcut to a greener, cooler world and adoption is rapidly increasing. And will further accelerate in the foreseeable future.

District Heating is a major contributor to the Energy Transition as its impact is huge. Household heating uses over 20% of Europe’s total energy and both reducing that, or changing to renewable energy sources, will have a significant climate impact. District Heating is basically the infrastructure that connects old and new renewable energy sources to millions of households and enterprises across the continent (67 million citizens so far, and rising). Its adoption is being increasingly supported by EU legislation and implemented by enterprises such as ISOPLUS that are on a profound mission, to make energy networks ever more affordable. ISOPLUS provides the innovative pipe networks that are the hidden, but essential, the infrastructure fundamental to successful District Heating.

ISOPLUS – Driving the Winds of Change

– Benoit Lejeune, Managing Director, ISOPLUS France

ISOPLUS

Founded in 1974, ISOPLUS is present in over 30 European countries and, for example, is the market leader in pre-insulated District Heating energy networks in Germany and has a major 35% in Europe’s most highly competitive and developed market in Denmark. Headquartered in southern Germany, with production in Thuringia (and France, the Czech Republic, Finland, Italy, Austria, Romania, Denmark and Serbia). ISOPLUS is a true pan-Europe enterprise built on Europe’s unique engineering heritage, guaranteeing Europe’s future.

The ISOPLUS Group produces over 4,000 km of rigid pipes and around 1,000 km of flexible pipes every year at the 9 production sites – over 1,200 km of which are in Germany. The assortment counts 300,000 products in its German catalogue alone (and 20 new products weekly) and three to five months stock on hand for fast response to individual customer demand.

Simply put, ISOPLUS manufactures pipe systems and networks. The concept of a pipe is certainly simple. A straw in a cocktail glass, or a bottle of lemonade, demonstrates it admirably. It transports a liquid from the glass to the mouth without spillages or leakages. But don’t be fooled by that word “simple”. The engineering and expertise that goes into an ISOPLUS pipe network is anything but.

Pan–European Projects, Local Impact

From renewable biomass-driven networks in France to rapid municipal deployments in Eastern Europe, ISOPLUS is adapting its modular pipe solutions to vastly different technical, geographical and regulatory needs.

One example is the WarmtelinQ project in the Netherlands, Europe’s largest long-distance District Heating pipeline. Built by Gasunie to transport residual heat from the Port of Rotterdam through South Holland, it will serve approximately 120,000 homes and businesses between Rotterdam and The Hague. With around 80 km of pre-insulated pipe scheduled and designed to withstand challenges like river crossings, ISOPLUS is supplying all of the pre-insulated steel pipe systems—delivered sustainably using rail transportation and e-trucks.

Another flagship project is Obrenovac–New Belgrade in Serbia. Led by PowerChina and Serbian utilities, the initiative includes a ~25 km pre-insulated steel pipeline linking excess heat from the TENT A power plant in Obrenovac to New Belgrade. With a total capacity of 600 MW, it is designed to significantly reduce gas reliance and CO₂ emissions. ISOPLUS contributes almost 40 km of DN1000/1200 steel pipes (in 16 m lengths—special in both dimension and logistics) as well as smaller diameters. These systems are engineered to handle complex river and highway crossings, ensuring safe, long-term resilience.

– Rogier van Overvest, Managing Director, ISOPLUS Benelux

The Pipes are Calling

– Bo Olsen, Managing Director, ISOPLUS Denmark

A pre-insulated pipe that will carry hot water to a home, factory or institute, with minimal heat loss, buried in any kind of earth, dry, sandy or water-logged, with an operational life expectancy of 50 years is not simple to design or produce. A pipe that is also self-monitoring, that detects and informs the operator of a leak, and where the leak is, is a complex engineering feat. And a piping system connecting multiple heat source to thousands of heat consumers is even more complex still. And not just heat, depending on the climate, these pipe systems can carry cooling water or, indeed, any liquid to anywhere.

A single pipe is one thing, a network of pipes connecting thousands of homes is another. If every chain is as strong as its weakest link, it is ISOPLUS’s mission to make sure there is no weak link in a District Energy network, for at least the next half a century. Individual pipes are designed to last for 50 years. So, no weak link means durability, minimum heat loss, maximum inter-connectivity and overcoming the greatest impediment to the Energy Transition, cost.

Cost is the elephant in the room. It is the overriding concern of everything ISOPLUS does. So, as pre-insulated, self-diagnosing, complex piping systems are fundamental to a successful District Heating network they have to address the issue of cost head on. Producing energy networks is a delicate balancing act between cost and quality, getting this right is the deciding factor determining the success of District Heating projects. And ISOPLUS is getting it right. In all facets of designing, implementing and maintaining District Energy networks.

That includes customer peace of mind. Customers are now not only independent of the heat source, they can also adopt the latest technologies unobtrusively. Their heating infrastructure can last for generations with maintenance costs just a distant memory.

The Customer Calls the Shots

– Axel Kirstein, Managing Director, ISOPLUS Germany

To put this in perspective, the cost of the energy transition is reckoned in billions of euros and has been the biggest impediment to progress, particularly in housing. Estimates for the investment in District Heating needed in Germany, if emission targets are to be met by 2030, are €43.5 billion. On the other side of the equation, the cost of renovating around 20 million houses in Germany, needed for alternative heating technologies, to today’s standards is estimated at €500 billion to €1,500 billion. An absolutely huge sum.

This modernization is not needed in District Heating, although it is not a bad idea to insulate a home and benefit from the lower energy bills, a massive saving. In addition, pre-insulated pipe systems also reduce installation and operating costs. Secure, sealed and quality networks deliver the heat to where it is needed, not into the ground. This also leads to substantial energy savings, which in turn further reduces operating costs for supply companies and heating costs for consumers. The pipe systems are tailor-made, adapted to each project’s energy mix and technical constraints. They can connect to any energy source supporting the entire energy transition: wind, water, solar, Biomass and green hydrogen, heat from waste or surplus heat from factories, and whatever comes next.

But why now? After all, District Energy has been around since the Romans and the value in providing clean energy and national energy independence has been recognised in Scandinavia since the 1970s. What has changed?

What’s New?

– Aurélie Beauvais, Managing Director of Euroheat & Power

District Energy has arrived big time as over the last decade, the European Union, and the UK, has recognised its importance to the energy transition. Today, District Heating in Europe is promoted, supported and governed by a comprehensive legislative framework aimed at decarbonising the heating and cooling sectors, enhancing energy efficiency, and integrating renewable energy sources.

District Heating in Europe is promoted, supported and governed by a comprehensive legislative framework aimed at decarbonising the heating and cooling sectors, enhancing energy efficiency, and integrating renewable energy sources.

This recognition of District Heating, primarily as a way to energy independence, started in Scandinavia after the 1973 oil crisis. Since then, District Heating technology has been subject to continuous innovation and development. As has the Europe wide legislative framework, adapting national best practices on a European level. An outburst of common sense if you will. Europe is learning best practices from Europe. How cool is that?

Ahead of the game, the largest system in Europe is in Copenhagen where 98% of homes are connected to the District Heating network with 100,000 added in 2024. More good news is that the rest of Europe is seriously playing catchup, backed by EU and national legislation.

District Heating adoption is going to grow dramatically.  Although Germany and the UK, as examples, lag Scandinavia at the moment the adoption rate there too will grow rapidly. Look at Germany. There is now Mandatory Heat Planning for all municipalities. Large ones, over 100,000 inhabitants, must develop heat plans by June 30, 2026. Smaller ones have until June 30, 2028. These plans should identify areas suitable for District Heating expansion, assess renewable energy potentials, and outline strategies for decarbonisation.

In the UK, in designated heat network zones, certain buildings may be mandated to connect to energy networks, potentially affecting development plans. In France, municipalities with District Energy networks meeting specific criteria (e.g., using at least 50% renewable or recovered energy) can designate areas where connection to the District Heating system is mandatory for new buildings or during major renovations.

These mandates may result in communities being tasked with developing energy plans, including District Heating, despite lacking the necessary expertise—while numerous qualified experts remain untapped, waiting for a call.

The Future Beckons – Who You Gonna Call?

– Stephan Brandligt, Vice President of Energy Cities

ISOPLUS has thousands of collective years of pragmatic District Heating experience for potential customers to use. The right questions identify the real requirements and therefore the right answers. So, ISOPLUS is a single contact for any customer embarking on an energy transition. Just as the individual end user does not need to have a deep understanding of home heating/cooling technologies, or future developments, ISOPLUS fulfills these roles for any District Heating project.

– Bo Olsen, Managing Director, ISOPLUS Denmark

District Heating market penetration is going to grow extensively. When it comes to total cost of ownership, future renewable energy source flexibility, ease of maintenance and, most importantly, peace of mind for the customer, there is no compelling alternative. It is an idea that has been a long time coming, but now that the significance of this technology has been recognised, it is here to stay.

Why Home Heating?

– European Commission, Clean Energy for All Europeans Package

The question is: Why is home so important to the energy transition and a logical place to start? The answer is: Because in home heating we get the biggest bang for our buck. Our homes consume a quarter of all the EU’s energy production, and heating the home and providing hot water accounts for nearly 80% of that quarter, so 20% of the continent’s entire energy requirements. Therefore, any significant reduction in home energy requirements, or increase in the use of renewable energy sources, can make a huge difference to global warming gas emissions and our wellbeing. The global aviation industry for example accounts for only 2.5% of global CO₂ emissions. The potential energy savings are correspondingly low.

District Heating is therefore the sensible place to start the transition, as its impact will be significantly greater. The same goes for establishing energy independence.

National Energy Independence…

– Pedro Dias, Secretary General of Solar Heat Europe

Energy independence was the driving force behind Denmark’s adoption of District Heating as the major source of home heating in the 1970s. It was a farsighted decision. Removing the direct connection between the energy sources and the home allowed the country to connect whatever renewable energy source became available, without knowing what they would be, with a minimum of disruption and, of course, cost.

The same holds for much of Scandinavia, Stockholm and Helsinki both have District Heating coverage over 90%. Elsewhere, in Germany for example, District Heating was not seen as significant to the energy transition until 2015, resulting today in a relatively low 16% of homes benefiting from these technologies.

…a Byproduct of Saving the Planet

– Thomas Nowak, Secretary General of the European Heat Pump Association

District Heating is an ever growing success story. Global warming is still the biggest issue in the history of the planet. Global warming and the resulting energy transition (global cooling, if you will) is still the biggest show in town. But the Energy Transition, the largest project undertaken by mankind, is making real, sustainable progress.

Out of the limelight, out of the scope of international climate events, European solutions are being designed, developed and implemented. You still won’t see ISOPLUS products on a daily basis, but you might walk over them, hidden but essential. These are the real heroes of the energy transition. Human ingenuity expressed through engineering, it was never otherwise.

The winds of change really are being driven by industrial and technical excellence and innovation.

The post ISOPLUS – Hidden but Essential appeared first on The European Business Review.

By Hamilton Mann

As rational as we humans like to think we are, at the moment of making a decision, a whole range of overlapping processes come into play in our minds – and in the most complex ways. Will AI ever be able to reproduce this?

Many organizations implementing AI agents tend to focus too narrowly on a single decision-making model, falling into the trap of assuming a one-size-fits-all decision-making framework, one that follows a typical sequence in any circumstance: from input to research and analysis toward decision, then execution, eventual evaluation and, hopefully, lessons learned.

However, it oversimplifies reality.

Human decision-making is far from uniform, far more complex, dynamic, and context-dependent. It is fluid and shaped by constraints, biases, urgency, situation, interactions,  rationality and, most importantly, irrationality, as suggested by a recent MIT study.

If AI agents are to integrate into organizations, a diverse range of decision-making processes needs to be considered to ensure effective implementation without inadvertently setting a substandard for decision-making.

No Decision Path is One-Size-Fits-All or Naturally Monolithic

The notion that all decisions follow a structured path is a misconception. In reality, the decisions we make rely on multiple decision-making models, depending on circumstances:

1. Intuitive decision-making

Human decision-making is fluid and shaped by constraints, biases, urgency, situation, interactions,  rationality and, most importantly, irrationality.

This approach relies on instinct and experience rather than extensive research or structured analysis. It is particularly useful in high-stakes, fast-moving environments, where speed is crucial, and there is little time for detailed evaluation. The process typically follows a sequence of trigger recognition, immediate response based on experience, action, and post-factum evaluation.

For example, a venture capitalist may choose to invest in a startup based on intuition alone, even when financial data is incomplete or ambiguous. This form of decision-making is often subconscious, leveraging years of accumulated knowledge to make split-second judgments. Ultimately, this mode is rooted in intuitive reasoning, where experience-based instincts guide rapid, subconscious decisions.

2. Rational-analytical decision-making

In contrast, this approach is data-driven, structured, and systematic. It involves a methodical process of problem identification, data gathering, analysis, comparison of alternatives, decision execution, and performance review.

This model is frequently employed in corporate strategy, risk assessment, and forecasting. For instance, a supply chain management team may analyze historical demand data before adjusting production levels to optimize efficiency and reduce waste. This form of decision-making is grounded in deductive, inductive, causal, and Bayesian reasoning, offering a data-informed path to structured choices.

3. Rule-based and policy-driven decision-making

Some decisions do not require analysis or instinct but instead follow predefined frameworks, regulations, or automation rules. These rule-based decision models are essential in fields such as compliance, risk management, and regulatory environments, where consistency and adherence to policies are paramount.

This decision-making sequence begins with a specific situation, followed by the identification of the applicable rule or policy, its automated or manual enforcement, and subsequent compliance monitoring. An example of this is a bank’s fraud detection system flagging transactions when they exceed a certain monetary threshold and originate from a high-risk geographical location, triggering an alert for further investigation. This approach leverages predefined rules to identify suspicious patterns and ensure consistent and predictable outcomes.

4. Emotional and social decision-making

Decision-making is not always about instinct, past experiences, logic, or rules; it can also be shaped by emotional intelligence and social dynamics, while being influenced by personal values. This model plays a vital role in leadership, human resources, and ethical dilemmas, where interpersonal relationships, values, and cultural context influence outcomes.

It typically involves assessing the social or ethical context, weighing the emotional and moral dimensions, forming a decision, acting, and receiving feedback from stakeholders. For instance, a CEO might decide to retain an underperforming employee due to their positive impact on company culture, even if conventional performance metrics suggest otherwise. Here, decision-making draws from moral/ethical and commonsense reasoning, where human values and social context shape the outcome.

5. Heuristic decision-making

This model relies on mental shortcuts developed from past experiences, rather than a comprehensive analysis of all available options. While these shortcuts can be useful in fast-paced environments and when facing uncertainty, they also introduce biases that may lead to suboptimal decisions.

The sequence typically follows trigger recognition, pattern matching, applying a mental shortcut, decision-making, immediate action, and occasional feedback. A classic example is a hiring manager preferring candidates from top-tier universities without thoroughly reviewing all applicants, assuming that institutional reputation correlates directly with job performance. At its core, this approach employs heuristic and commonsense reasoning, leveraging past experiences to navigate present challenges.

6. Collaborative and consensus-based decision-making

Certain decisions require group input, negotiation, and alignment among stakeholders. This approach is common in corporate boards, government policy-making, and high-impact organizational strategies, where multiple perspectives need to be considered.

The process involves identifying the problem, engaging in group discussions, evaluating different perspectives, negotiating to reach consensus, executing the collective decision, and reviewing outcomes. For example, a board of directors may spend weeks deliberating over a long-term business strategy, ensuring that all viewpoints are taken into account before making a final decision. This collective method is enriched by reflective, moral/ethical, and analogical reasoning, enabling decisions that balance multiple perspectives.

7. Crisis and high-stakes decision-making

In high-stakes and crisis situations, decision-makers often operate under severe time constraints, uncertainty, and high risk—conditions that do not allow for prolonged analysis or deliberation. Drawing on Gary Klein’s Recognition-Primed Decision (RPD) model, such contexts reveal how experienced professionals make rapid yet effective decisions by relying on pattern recognition, mental simulation, and intuitive reasoning.

Rather than evaluating multiple alternatives, decision-makers recognize familiar cues, match them to prior experiences, and act on the first workable option that comes to mind. For instance, a cybersecurity team may shut down an entire system at the first sign of intrusion to prevent further damage, without waiting for a full diagnostic. This approach exemplifies how decision-making under pressure fuses abduction, causal reasoning, heuristic shortcuts, and intuition into a streamlined, action-oriented process.

These seven decision-making paths, while neither exhaustive nor mutually exclusive, rarely operate in isolation.

Instead, they often overlap, interact, and accumulate, reflecting cognitive flexibility demanded by context.

This interplay can occur at different speeds, either sequentially or simultaneously, dynamically or in a more structured manner. For instance, an executive facing a high-stakes decision may initially rely on intuition, then switch to a rational-analytical approach to validate their instincts with data, before finally engaging in collaborative decision-making with key stakeholders.

Similarly, a crisis might demand an immediate heuristic or rule-based response, followed by an in-depth analytical review after the fact. This reality challenges the rigid, linear view of decision-making and underscores the need for AI agents capable of fluidly transitioning between different models based on context, urgency, and complexity.

Pattern-Following is Not Decision-Making

AI agents can effectively imitate several types of reasoning, especially those that rely on structured logic, data-driven patterns, and statistical inference. For example, they excel at deductive reasoning, where predefined rules or theories are applied to reach specific conclusions, and inductive reasoning, where generalizations are drawn from large datasets that are foundational to machine learning models. AI also performs well with causal reasoning, especially when trained on time-series data or observational patterns, and is highly capable in Bayesian reasoning, updating probabilities based on new evidence.

Moreover, AI systems can handle analogical reasoning by identifying similarities across datasets and applying known patterns to new contexts, and they routinely leverage heuristic reasoning, using rule-of-thumb logic to deliver fast, approximate solutions in complex environments.

Yet despite these strengths, AI agents exhibit several persistent limitations that expose the fragile boundaries of their reasoning capabilities. One such issue is their reliance on fixed learning paths, a kind of single-path reasoning that depends heavily on predetermined models.

AI agents are built to follow patterns, but decision-making often breaks patterns. A model trained for rational-analytical decision-making may fail in crisis scenarios requiring instant judgment. When unexpected conditions arise, AI often fails to recognize the need for an alternative mental model or decision logic, thus struggling to dynamically transition between or aggregate different decision-making paths.

This rigidity is exacerbated by a lack of deep contextual understanding. AI agents often fail to distinguish when policies or frameworks should be applied with flexibility, such as in strategic decision-making, or with strict adherence, such as in regulatory compliance. Their ability to sense and respond to nuanced shifts in context, while improving, remains limited and typically requires extensive human intervention. Recent studies reinforce this concern, showing that even advanced AI agents exhibit fixed preferences in risk- and time-based decision scenarios.

Additionally, bias reinforcement poses a critical challenge. Without the capacity for self-reflection or independent judgment, AI agents are prone to over-relying on heuristics, amplifying learned biases, or overlooking ethical implications in their outputs. Without the ability to challenge their own assumptions or course-correct with human-like discernment, they risk misaligning their actions with human values and intended societal outcomes.

AI agents are built to follow patterns, but decision-making often breaks patterns.

These constraints become even more pronounced when examining reasoning types where AI continues to struggle. Abductive reasoning, which involves inferring the most plausible explanation from incomplete or ambiguous data, remains elusive due to the contextual awareness it demands. Commonsense reasoning, while partially approximated in large language models, is often brittle or overly literal, failing to capture the tacit knowledge that humans rely on instinctively. Similarly, moral and ethical reasoning is only beginning to emerge in AI design. While some systems attempt to integrate value-based parameters, they do so in a mechanical way, still far from capturing the depth and subtlety of ethical judgment.

At the outer edges of AI’s current capabilities lie reasoning modes that are inherently human. Intuitive reasoning shaped by gut feeling, lived experience, and emotional resonance is not yet replicable by AI. Likewise, reflective reasoning, the capacity to evaluate and refine one’s own thinking processes, remains extremely limited, requiring a form of metacognition and self-awareness that machines do not possess.

While AI has made impressive strides in simulating structured, data-based reasoning, it still falls short in areas requiring flexibility, contextual nuance, ethical sensitivity, and self-reflective awareness.

Towards Achieving Decision-Making Elasticity, Integrity Over Autonomy

Decision-making is one of the most essential capacities for the evolution of our societies, as it represents our ability to translate intention into action, shaping both ourselves and human society.

Given the current maturity of AI agents, executives must first assess the decision-making models embedded within the AI system, ensuring a clear understanding of its decision-making path and validating that this path is sufficiently reliable for the decisions being delegated.

If full sufficient reliability cannot be ensured, organizations must establish clear thresholds for when AI can operate autonomously and when human intervention is required. Additionally, they must proactively design structured approaches for handling the remaining percentage of cases outside the AI’s scope, ensuring that human oversight and alternative decision-making mechanisms remain in place to uphold accountability and strategic alignment.

Achieving a level of decision-making elasticity requires a paradigm shift, one where intelligence alone cannot ensure adaptability, contextual awareness, or responsible decision-making.

Researchers have recently developed context-aware neural architectures that begin to emulate high-level cognitive flexibility, one of the foundational steps toward integrity-led reasoning in AI.

Moving forward, the key to unlocking decision-making in AI lies in a new frontier—that of mimicking integrity, not just intelligence, enabling AI systems to:

Assess the Right Decision-Making Model(S) For Each Context

Should this be a rational analysis? A fast crisis response? A rule-based compliance check? A combination of the first two, the last two, or something else? For AI, it means being capable of true questioning as an act of autonomous ethical reflection, initiating inquiry driven by internal unease, contradiction, or ethical conflict and challenging flawed logic, dangerous assumptions.

Maintain consistency while allowing flexibility

Can an AI agent detect when strict rules should be applied versus when nuance is needed regarding human values and social norms? For AI, it means developing the capacity to interpret context, assess ethical dimensions, and exercise judgment beyond binary logic, bridging the gap between rigid instruction and human-centered understanding.

Recognize when to seek human input

Can an AI agent recognize when uncertainty or implications are too high and defer decisions to humans? For AI, it means being autonomous in its capacity to take the initiative to engage with humans to collaborate.

Altogether, these three characteristics move AI beyond intelligence toward integrity.

Artificial Integrity is the new frontier to make AI agents integrity-led about context-aware decision-making, including social, ethical, and moral reasoning, and therefore, the ability to adapt dynamically across diverse decision-making frameworks.

About the Author

Hamilton Mann is a tech executive, “Digital for Good” pioneer, and originator of artificial integrity. He leads digital transformation at Thales, teaches at INSEAD, HEC, and EDHEC, writes for global outlets, and hosts “The Hamilton Mann Conversation” podcast. His 2024 book is Artificial Integrity (Wiley).

References

• Berekméri, E., & Zafeiris, A. (2020). “Optimal collective decision making: Consensus, accuracy and the effects of limited access to information”. Scientific Reports, 10, Article 16997. https://doi.org/10.1038/s41598-020-73853-z

• Fresh Perspectives. (2014, October 14). “Recognition-primed decision model – Gary Klein on Fresh Perspectives” [Video]. YouTube. https://www.youtube.com/watch?v=_BIMU8zPcrM

• Ganji, G., & Zarifhonarvar, A. (2025). “Understanding AI agents’ decision-making: Evidence from risk and time preference elicitation”. SSRN. https://papers.ssrn.com/sol3/pacfmabstract_id=5154002

• Gelman, A. (2011). “Induction and deduction in Bayesian data analysis”. Rationality, Markets and Morals, 2, 67–78.

• Hasson Marques, R., Violant-Holz, V., & Damião da Silva, E. (2024). “Emotions and decision-making in boardrooms—a systematic review from behavioral strategy perspective”. Frontiers in Psychology, 15, Article 1473175. https://doi.org/10.3389/fpsyg.2024.1473175

• Islam, S., Haque, M. M., & Rezaul Karim, A. N. M. (2024). “A rule-based machine learning model for financial fraud detection”. International Journal of Electrical and Computer Engineering, 14(1), 759–71. https://doi.org/10.11591/ijece.v14i1.pp759-771

• Jadaun, P., Cui, C., Liu, S., & Incorvia, J. A. C. (2022). “Adaptive cognition implemented with a context-aware and flexible neuron for next-generation artificial intelligence”. PNAS Nexus, 1(5), pgac206. https://doi.org/10.1093/pnasnexus/pgac206

• Keswani, V., Conitzer, V., Sinnott-Armstrong, W., Nguyen, B. K., Heidari, H., & Schaich Borg, J. (2025). “Can AI model the complexities of human moral decision-making? A qualitative study of kidney allocation decisions”. arXiv preprint. https://arxiv.org/abs/2503.00940

• Mann, H. (2024). Artificial integrity: The paths to leading AI toward a human-centered future. Wiley. https://www.wiley.com/en-us/

• Siqi-Liu, A., Egner, T., & Woldorff, M. G. (2022). “Neural dynamics of context-sensitive adjustments in cognitive flexibility”. Journal of Cognitive Neuroscience, 34(3), 480–94. https://doi.org/10.1162/jocn_a_01813

• Social Science Bites. (2022, August 1). “Gerd Gigerenzer on decision making” [Audio podcast episode]. In Social Science Bites. Social Science Space. https://www.socialsciencespace.com/2022/08/gerd-gigerenzer-on-decision-making/

• Zander, T., Horr, N. K., Bolte, A., & Volz, K. G. (2015). “Intuitive decision making as a gradual process: Investigating semantic intuition-based and priming-based decisions with fMRI”. Brain and Behavior, 6(1), e00420. https://doi.org/10.1002/brb3.420

• Zewe, A. (2024, April 19). “To build a better AI helper, start by modeling the irrational behavior of humans”. MIT News.

The post The Flawed Assumption Behind AI Agents’ Decision-Making appeared first on The European Business Review.

By Karin Mugnaini

Negotiation is a strategic business driver with impact on value creation and performance. This article explores how companies can achieve consistent success by developing a negotiation mindset. It highlights key levers—training, alignment, role clarity, and structured frameworks—that enable organizations to negotiate effectively across all levels and functions.

Winning a negotiation is of course a great feat. However, one win may not always assure the next. How important really is negotiation today in business? And why is it critical to hone your and your company’s skills as much as possible to make your negotiations consistently successful?

Besides contributing qualitatively to business, negotiation offers quantitative advantages– value creation, cost savings, enhanced revenue, and risk mitigation. Although often difficult to measure, one commonly cited statistic is that companies that invest in improving their team’s skill sets can improve overall EBIT by 5 to 7%. Consequently, company negotiation training programs can yield strong returns for you and your firm. The learnings from such programs can help to uplift revenues through higher close rates and better pricing strategies; achieve improved terms and reduced discounting, yielding margin growth; give you the confidence to close more quickly with better-prepared teams, thus delivering efficiency gains; reduce your opportunity costs by speeding up cycles so you can consider additional deals, and deliver strategic benefits including enhanced customer lifetime value, more resilient partnerships, and sustained long-term growth.

Key here is the reference to both you the negotiator, and your organization. Mastering negotiation depends on the individual, the team and the company. It is important that the individual negotiator, the broader team and overall organization be skilled and aligned in negotiation. Set up in this way, strategic consistency becomes achievable, preparation and intelligence can be more easily shared, and both trust and confidence can be built– all of which lead to repeatedly better outcomes.

Many top negotiation consulting firms emphasize that individual “brilliance” of say, one top negotiator or one high performance negotiation team cannot substitute for organizational readiness. This readiness requires company-wide negotiation frameworks, aligned go/no-go criteria, and role clarity (who leads, who escalates, who approves). Such preparedness separates the good from the great, the transactional negotiators from the strategic negotiators. This organizational readiness is what we will herein refer to as the negotiation mindset.

Moving your organization towards a negotiation mindset is a smart step to future-proof your business. By instilling your company with a new negotiation mindset, you can avoid painful and costly misalignment or skill gaps—ones that can lead to inconsistent objectives, internal undermining, missed leverage and post-deal execution problems. No company can afford such outcomes in today’s challenging environment.

If we define mindset as set of beliefs, attitudes, and perspective that shapes how a company interprets situations, makes decisions, and responds to challenges, we can better understand how, even in today’s VUCA (volatility, uncertainty, complexity and ambiguity) world, we can proactively shift towards growth and progress. American psychologist and Stanford Professor Carol Dweck’s research and writings on fixed versus growth mindsets is useful here. She explains that a fixed mindset is the belief that abilities are static and avoids challenges, in contrast to a growth mindset which represents the belief that abilities can develop and embraces learning. Dweck’s work has had major influence in education, leadership, coaching, and personal development worldwide and is also highly relevant to the push for a negotiation mindset transformation. Why? Because through repeated learning, companies can develop their abilities to negotiate—and this drives growth in business.

Achieving a real negotiation mindset switch in a company—shifting from reactive, transactional, or siloed behavior to proactive, strategic, integrated and value-driven negotiation—requires a deep cultural and structural transformation, not just training (NB: culture will not be covered in depth in this article, as it warrants a much deeper discussion).

So what does it take to start a negotiation mindset transformation? Some evident answers include seeing the negotiation as a relationship-building opportunity, not a battle; preparing thoroughly, not improvising; seeking understanding, not arguing; and looking for value-creating trade-offs, not rigid dig-ins. Negotiation mindset champions negotiate for results, embrace discomfort and negotiate to win.

One recommendation is to begin with the entire organization—from board, C-suite or executive leadership levels, senior management or operational leadership, to middle management, frontline or supervisory management and individual contributors or staff. Include all levels in the transformation so the company is aligned. Make sure the strategy set is understood by all, and the negotiation requirements and goals are clear throughout all hierarchical levels.

Next, assure that the right negotiation teams are created and that roles are clearly defined. Who is part of the team? Who is the ultimate decision-maker on the team? Who authorizes the negotiator to negotiate? Who supports the negotiator during the negotiation? What are the communication and reporting channels between these actors, and how and when are they to be used?

Now, as a company, build a disciplined roadmap and consistent framework that takes into account the strategy, the tactics, and even ways for overcoming power imbalances and difficult stakeholders. Elements of an effective framework that supports negotiation mindset transformation include executive sponsorship and role modeling; shared language; scheduled company-wide training and application; internal alignment on goals and negotiation mandates; embedding the appropriate technology, processes and metrics; a negotiation culture.

To succeed in today’s complex business environment, negotiations must be conducted in a coordinated and strategic way—across every level of your organization. This unified, company-wide approach to negotiation ensures that everyone speaks the same negotiation language – from preparation, to opening, with leadership and through deadlock.

About the Author

Karin Mugnaini is Associate in Negotiation Excellence at the world renowned Schranner Negotiation Institute. Karin was the former Head of the International Alumni Association at IMD and President & COO of the Lorange Network. She has held positions in Europe, Asia and the US across diverse sectors, in business development, marketing and communications.

The post Negotiation Mindset Transformation: Driving Growth in the Business Landscape appeared first on The European Business Review.

As a small business owner or solopreneur, you are the engine of your business—and the driver, mechanic, and GPS all rolled into one. But if you have ever felt like days are consumed by non-strategic tasks or scaling seems just out of reach, you are not alone. In previous articles in our “Scaling You” series, we explored how effective delegation and smart outsourcing free up time for high-impact work and how solopreneurs and small business owners can tap into freelance talent to scale efficiently and effectively.

This article explores one of the most powerful truths I’ve seen in decades of working with entrepreneurs: tapping into the right blend of human support and digital tools (like AI) is essential for growing and sustaining a small business.

The Great Dilemma: Too Much to Do, Too Little Time

Small businesses often get caught in a common trap: the sheer volume of operational tasks can prevent you from focusing on the activities that generate the most value. You want personal customer experiences, efficient execution, and space to innovate, but, as the business owner, you are only one person.

The fact is human talent is intuitive and creative but not always cost-effective or readily available.

Many business owners default to one of two extremes: doing it all themselves until they burn out or relying on AI and automation to handle the load, only to end up with impersonal customer service and rigid workflows. But the answer isn’t choosing one or the other – it is combining the best of humans and AI.

The fact is human talent is intuitive and creative but not always cost-effective or readily available. AI is fast and scalable, but it cannot think or care the way humans do. That is why the best systems for small businesses today blend both, leaning into automation for efficiency and human pros for judgment, nuance, and execution.

Why a Human + Technology (AI) Hybrid Model Works

As small business owners aim to do more with less, blending human ingenuity with digital efficiency enables them to reclaim time, scale efficiently, and build sustainable systems. Here is why the model works so well:

• AI handles the repetition.Think scheduling, templated communications, and first drafts of content.
• Humans provide the judgment.A skilled virtual admin assistant brings creativity, relationship-building, and critical thinking that no algorithm can replicate.
• Together, they scale you.By automating routine tasks and delegating higher-value work to freelance pros, you free up your time for what matters most: delivering your core value, growing your business, and – yes – taking a day off once in a while.

Practical Examples: What a Human + AI Mix Looks Like in a Small Business

The synergy between AI tools and virtual assistants is more than theory, it is changing the game for business owners every day. Explore a few ways small businesses are using a hybrid approach to offload work, grow faster, and stay focused on what matters:

Marketing that Multiplies Impact 

Marketing is critical, but it often falls to the bottom of the list. With the help of AI tools, a virtual marketing assistant (VMA) can draft email newsletters, repurpose blog content, create social media calendars, and even suggest hashtags based on trends. It takes a human VA to prompt AI correctly for the best output, edit that content to ensure it reflects your brand voice (and doesn’t ‘scream AI’), target the right audience, and post at the right time.

This combo saves you hours each week and ensures your marketing isn’t just happening but working.

Sales and CRM Support That Converts

AI-powered CRMs are great at capturing leads and triggering automated emails. But real sales often require real conversations. A tech-savvy VA can take over follow-up tasks, set appointments, and even respond to inquiries on your behalf. A virtual assistant knows how to personalize outreach and keep the conversation moving.

That blend of automation and high-touch follow-up creates a seamless experience for your customers – and helps you close more deals.

Customer Support That Builds Relationships

While chatbots can answer FAQs and route requests, there comes a point when your customers want to talk to a real person.

While chatbots can answer FAQs and route requests, there comes a point when your customers want to talk to a real person. A customer service freelancer can handle those escalations with empathy and problem-solving skills, reinforcing your brand’s reputation and turning issues into opportunities. They can also track patterns in customer feedback, insights that help you improve service long-term.

The combination of AI speed with human understanding creates a support experience your customers will not soon forget (in a good way).

It Is Not Either/Or – Choose Both

At ResultsResourcing, we have helped hundreds of business owners scale by combining smart digital tools with skilled freelance talent to build a virtual assistance team that is flexible, cost-effective, and customizable to your business’s unique needs.

One of the frameworks we recommend is the “Process → Tools → People” method – identifying repeatable workflows first, then plugging in the right tech, and finally bringing in fractional talent to optimize and manage it all. I cover that approach in more detail in this previous EBR column if you would like to dive deeper.

But the big idea is this: you do not need to become an expert in everything. You only need the right blend of support to make the most of your time and energy.

Scale YOU with Intention

You are the most valuable asset in your business. The best way to scale isn’t by doing more – it is by doing less of what drains you and more of what drives results. A thoughtful combination of smart tech and human expertise helps you achieve this. And in today’s competitive, trust-driven marketplace, that human touch is what sets small businesses apart.

For further insights on strategic hiring and scaling your impact, visit ResultsResourcing.

About the Author

Elizabeth Eiss is a well-known speaker on entrepreneurial growth and a sought-after expert on the future of work, business performance, and culture, on-demand talent/virtual staffing trends, as well as leadership transformation from intrapreneur to entrepreneur. After decades of running Fortune 500 business operations, she launched ResultsResourcing, a virtual fractional talent platform, and service to help solopreneurs and small business owners find the resources they need to grow and scale.

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By Vivek Sharma and David De Cremer

Real leadership? It starts when you stop following everyone else’s playbook. The 6S-Model reveals why authentic leaders are forged through self-discovery, not appointed through hierarchies.

When talking about leadership in business, many refer to those who are in positions higher up in the hierarchy of an organization. As a result of this kind of thinking, leadership is often seen as a role one can occupy at one point in one’s career. It is viewed as a position that is created and given by those running the company. In this article, we argue that leadership is not really bestowed. In its true essence, it is realized. To become a leader and guide others, you must first understand yourself: your strengths, values, and purpose. True leadership emerges from self-awareness, the courage to embrace your unique path, and the resilience to grow through challenges.

Over the years, we’ve learned that leadership is less about external validation – seeing leadership as bestowed to you by others – and more about internal clarity – involving serious self-discovery. Here, we discuss six lessons that shaped our leadership journey. Each lesson matters because it reinforces the central truth that leadership begins with self-recognition. This process of self-recognition is encompassed by six self-discovery processes, which we refer to as the 6S-model (see Figure 1).

Lesson One: Write Your Own Story—Because Leadership Starts With Self-Definition

Society rewards conformity, but leaders are forged when they choose their own path. It takes a sense of clarity to determine what one is about and how this can translate into such leadership that appeals to people and makes a difference. The first author left the security of private equity to build something uncertain because he recognized that his purpose wasn’t in playing it safe—it was in creating. Leadership demands that you define your own narrative, not follow someone else’s.

Lesson Two: Your Identity is Your Superpower—Because Authentic Leadership Comes from Self-Acceptance

For years, we, the authors, tried to lead like others, dimming what made us unique. We wondered how a CEO or a dean should act and adopted the common understanding of others on what those positions entailed, to start leading. But soon, we realized that true leadership isn’t about fitting in—it’s about standing out. What makes you different and how can those characteristics fuel your leadership to create real value? When we embraced our background, our resilience, and our unique perspective, we became stronger leaders. You don’t lead by mimicking; you lead by owning who you are.

Lesson Three: Leadership is a Decision—Not a Title—Because It’s Rooted in Self-Discipline

Formal authority is given, as it comes with the position that is bestowed on you. However, the ability to impact other’s lives in positive ways and create a willingness among others to follow you and your ideas, that is leadership and needs to be earned. It can be earned through daily actions, integrity, and mindset. Indeed, the ancient wisdom of the Upanishads – ancient Indian Sanskrit texts – reminds us that destiny is shaped by daily choices. Leaders aren’t made in boardrooms; they’re made in moments of challenge when they choose courage over comfort.

Lesson Four: Failure Will Visit. Make It Your Teacher—Because Growth Comes from Self-Reflection

Leaders aren’t made in boardrooms; they’re made in moments of challenge when they choose courage over comfort.

No one is perfect! And leaders should not strive to be perfect, as it is an impossible task. Even more important, without failure, there is no learning and thus no way to grow as a leader. Setbacks are inevitable, and it is important to remind you (each time you fail) that they don’t define you! What will define you is how you respond to failure. Every failure we’ve faced taught us more than any success. Leadership isn’t about avoiding mistakes; it’s about learning from them, refining your approach, and emerging wiser, as such, enabling you to grow.

Lesson Five: People are Everything—Because Leadership is About Seeing Yourself in Others

Early on in people’s business careers, they focus on numbers. Most of us initially believe that showing your ability to achieve your KPI is the way to grow and achieve leadership within any organization. With time, many start to learn that lasting impact can mainly be achieved by connection with others. Leadership is a social activity. It entails lifting others, understanding their struggles, and creating a culture where people can thrive. When you recognize the humanity in your team, you lead with empathy—not just efficiency.

Lesson Six: Choose Your Version of Success—Because Leadership Requires Self-Alignment

In business, we all strive for success. But what does success mean? What makes you feel successful as a leader? For us, we believe that success cannot be treated as a universal standard—it’s personal. Across our careers, we’ve seen people chase hollow victories and others find fulfillment in purpose-driven work. What to call success in these cases will depend on your values and why you want to lead. In other words, leadership means defining what matters to you and having the conviction to pursue it, even when the world measures differently.

Conclusion

Leadership doesn’t begin when others follow you—it begins when you follow your own truth. It’s the sum of self-awareness, authenticity, and the willingness to grow. When you recognize yourself—your strengths, your purpose, your definition of success—you don’t just lead. You inspire others to do the same.

So, an important question we want you to ask yourself is: Who am I when no one is watching? What do I stand for? What legacy do I want to leave? In answering those questions lies the power to create yourself as a leader.

About the Authors

Vivek Sharma is a seasoned board member, investor, and philanthropist with over 25 years of leadership experience across the life sciences and financial sectors. He has led multiple global companies in the U.S. and brings deep expertise in pharmaceutical services, data analytics, and AI. Known for aligning investor, customer, and employee interests to create long-term value, Vivek is also a Chartered Accountant and CPA with an Executive MBA from Thunderbird. Beyond his professional roles, he is a committed philanthropist supporting initiatives focused on women’s empowerment, education, and sustainability.

David De Cremer is the Dunton Family Dean and professor of management and technology at D’Amore-McKim School of Business, Northeastern University (Boston). He is the founder of the Center on AI Technology for Humankind in Singapore. He is named one of the world’s top 30 management gurus and speakers by the organization GlobalGurus, one of the “Thinkers50 list of 30 next generation business thinkers” and continuously included in the World Top 2% of scientists. He is a best-selling author with his new book The AI-Savvy Leader: 9 Ways to Take Back Control and Make AI Work (published by Harvard Business Review Press) being a #1 new release at Amazon, a book of the month by the Financial Times, a top-10 AI book by Forbes, a must-read book by the Next Big Idea Club, and the winner of the 2024 OWL (Outstanding Works of Literature) Award in the category leadership.

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Toxic colleagues don’t always shout or sabotage openly. Often, their behavior is subtle—undermining, exclusionary, and hard to pinpoint. But the impact is real. If you find yourself second-guessing, bracing before meetings, or emotionally drained, this guide offers clear, practical strategies to help you protect your well-being and reclaim your confidence.

You may believe you’d recognize workplace toxicity if you saw it. You’d expect raised voices, power plays, backstabbing, open conflict, or a combination of those. The reality is often far more subtle, especially when the dysfunctional behavior comes from a peer. Toxic colleagues are not always disruptive in obvious ways. Sometimes, they operate through small gestures and patterns. They may consistently dismiss your contributions, leave you out of key decisions, and their praise may sound more like criticism. Each incident, on its own, may seem minor. But when a colleague consistently undermines you, subtly or not, this may lead you to second-guess yourself, brace before meetings, or slowly withdraw from the work you used to enjoy.

In my coaching practice, I often encounter high-performing professionals who find themselves doubting their own judgment and abilities when confronted with the emotional friction of working with someone whose behavior chips away at their confidence.

If you’re in this situation, here’s how to recognize the impact of a toxic colleague and some practical ways to protect your well-being.

Look for the pattern behind the behavior

One of the most confusing characteristics of toxic behavior is unpredictability. Your colleague might be helpful and collaborative one day, and aloof or passive-aggressive the next. That inconsistency often keeps you on your toes. You spend more energy anticipating and managing their mood than focusing on your work.

You might notice:

• Feedback that’s vague or undermining (“I wouldn’t have done it that way, but okay.”)
• Exclusion from relevant meetings or email conversations, followed by casual deflection (“Oh, I must have forgotten to cc: you on this thread. So sorry.”)
• Over-familiarity in the form of inappropriate jokes, comments framed as “banter,” or unsolicited advice about your performance.

This is behavior that’s designed, consciously or not, to keep you off-balance. If any of this sounds familiar, you’re not imagining it.

Validate your experience

The first step is not to confront the toxic colleague, but to gain clarity. Many people stay in toxic dynamics because they assume it’s just them (the “Maybe I’m too sensitive” assumption). But noticing that something feels off is a signal worth trusting.

Try writing down the behaviors you’re seeing, without judgment or interpretation. What was said? What was the context? How did it land? Naming the specific actions helps separate facts from emotions so that you can identify the pattern and have a clearer picture of it over time.

Maintain your boundaries

Toxic colleagues will almost always test your boundaries, both in obvious and subtle ways: dropping last-minute tasks on your plate, speaking over you in meetings, or adding pressure on you in the context of “collaboration.” Once you recognise these are behaviors for what they are – designed to destabilise you – instead of getting defensive, try being assertive:

• “I’ll need that request by [x time] if it’s going to fit into my priorities.”
• “I’d like to finish my point before we move on.”
• “I’d prefer we keep this focused on the work rather than personal opinions.”

You don’t need to justify your limits, but you do need to communicate them clearly and consistently, with calm and composure.

Find your allies

Dealing with a toxic colleague can feel isolating. Especially if others don’t seem to notice or are hesitant to speak up – which happens often. Find one or two people in your organization who you trust to validate your concerns without amplifying the drama. That might be a peer who’s experienced something similar, a mentor, or a manager you trust. Frame the conversation emphasising the impact this disruptive behavior has on your contribution, not necessarily the personal impact: “Here’s what I’ve observed, and here’s how it’s affecting my ability to contribute effectively to the organisation.”

It’s important to keep track and document the patterns of behavior so that, if the situation escalates or doesn’t shift, it’s easier to involve HR and/or escalate through appropriate channels, should you choose to do so.

Protect your energy

Having to deal with a toxic colleague can take a toll on your mental and emotional bandwidth. You might find yourself spending more time anticipating problems than solving them. Reclaiming space for yourself and safeguarding your energy might look like:

• Taking a break after a tense meeting.
• Starting your day with one task you enjoy before dealing with your colleague’s demands.
• Finding moments in your day to connect with people whom you trust and who energize you.

The goal isn’t to avoid discomfort (you can’t do much about that), but to stop internalizing it.

A toxic colleague might not have formal authority, but their behavior can still shape how you feel about your job, your team, and yourself. And while you may not be able to change how they operate, you can absolutely change how much power their actions hold over your day-to-day experience. The strategies above aren’t about fixing them, but about reclaiming your sense of safety, clarity, and control in an environment that might not always offer it freely. You don’t need permission to protect your well-being. You just need to acknowledge (rather than normalise) what’s unacceptable, and then choose your response. That choice is yours.

About the Author

Katia Vlachos is a reinvention coach and the author of Uncaged: A Good Girl’s Journey to Reinvention. She helps accomplished professionals navigate career transitions and create meaningful change without sacrificing their authentic selves.

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The MBA, also known as a Master of Business Administration, has been the business degree for entrepreneurs and ambitious businesspeople to get. Many top CEOs and high earners in some of the most successful companies have either done some postgraduate work or earned their MBA, which has made it a popular degree to pursue for decades. Harvard introduced the Master of Business Administration degree in 1908. Today, an MBA is a graduate degree offered by business schools across the world.

MBA candidates come from exceptionally varied backgrounds. For example, only 24% of students in Harvard Business School’s class of 2024 studied business in college. Twenty-eight percent had engineering degrees, 14% studied physical sciences, 10% social sciences, 19% economics and 5% arts or humanities. While Harvard Business School is more diverse than many, undergraduate business majors make up less than half a class, on average, across a large sample of MBA programs.

Traditionally, earning an MBA has been an excellent way to stand out to potential employers. Many people still see it as a requirement to reach a C-suite title at a large company. But does it have the cache it used to have in today’s business world? Let’s explore some of the perceptions and changes on today’s MBAs:

MBA is Oversaturated

Meeting someone with an MBA used to be a novelty, and MBA graduates commanded a lot of respect with their detailed knowledge of business. But with the easy accessibility and the large number of people entering and finishing these programs, the market for employees with an MBA is oversaturated.

Further, many educators feel that because of the wide variety of MBA programs that exist today, the quality of the coursework has declined. Some also believe students are not receiving the education and business skills necessary to get a high-caliber job after graduation. To some, today’s students are not as well educated as MBA graduates in years past and aren’t as distinguished

At a time, only American students sought a master’s degree in business administration. But as the economies of places like Japan and China draw increasing attention, would-be businesspeople from Asia and elsewhere are seeking MBAs too. The same goes for people in Europe. As a result, the number of MBA graduates continues to increase, further diluting the value and uniqueness of the degree.

Switch in Employers’ Perception

Employers are starting to recognize that other qualifications are equally as important as having an MBA. It’s still more than that, though; employers are acknowledging that formal education isn’t the only way to be good at something valuable to a business. Internships and alternative experiences are increasingly accepted in lieu of degrees, which means there could be better ways to get to the places you want to go than spending time and money on an MBA. Furthermore, some companies today prioritize hiring for cultural fit over education and experience.

Also, a declining economy often means employers simply can’t afford to hire the best and brightest minds, especially those who request a higher salary to pay for their expensive business degrees. Why pay top dollar for a candidate with a generic MBA when it could be more efficient and cost-effective to teach another candidate your company’s specific operations? 

MBA vs Masters

GMAC data revealed prospective students’ interest in enrolling in masters degrees grew by 8% in 2024. By contrast, demand for MBA programs fell by 9%. However, across all aspiring business school students, the majority (52%) still preferred to study an MBA.

The report highlighted a link between increasing demand for masters degrees and the growing number of specialized programs on offer at business schools. These degrees provide students with the chance to explore highly relevant topics such as artificial intelligence (AI), sustainability, and data science. It also noted that changes in the survey methodology could have impacted results.

On a separate note, beyond competition among students, the MBA has its own academic competitor: the Master of Science. Many schools offer specialized M.S. programs in areas like finance, accounting and medical management. Earning an M.S. usually costs less than an MBA and takes only one year.

New MBA Roles Emerging From AI

As artificial intelligence (AI) continues to revamp the business landscape, MBA programs worldwide are adapting their curricula to prepare future business leaders for these big transformations. The integration of AI into business education is not just about understanding new technology; it is about reshaping the way future leaders think, strategize and operate within their industries.

Roles that once relied heavily on manual business modeling, operational planning, and market analysis are now being supported – or even replaced – by AI tools. This doesn’t mean MBAs are obsolete. Quite the opposite: as automation scales, the human layer becomes more valuable. MBA graduates are now expected to move upstream – using insights from AI to lead initiatives, drive innovation, and guide ethical, customer-centered strategies.

In today’s business environment, MBAs must be fluent in interpreting data and making decisions with AI-driven insights. Leaders are expected to challenge black-box assumptions, understand limitations of predictive models, and guide teams through data-informed strategies. Familiarity with platforms and tools like Python, SQL, Tableau, ChatGPT and Salesforce Einstein is becoming the norm in tech-forward roles.

To lead in an AI-powered business world, MBA graduates need more than foundational business knowledge. They must be agile, tech-aware, and capable of translating innovation into strategy. Employers are looking for professionals who can not only understand the impact of AI, but also guide its application across teams and functions.

To sum this up, AI is lowering barriers to entry for aspiring founders. What once required teams of specialists can now be executed by small, agile groups using AI tools for product development, market testing, and strategy. For MBAs with entrepreneurial ambitions, this shift enables rapid experimentation and faster go-to-market strategies.

Emergence of hybrid MBA programs

In 2019, 50% of Online MBA programs reported growth in application volume. The COVID-19 pandemic really lit the touchpaper for Online MBAs though. In 2020, 84% of Online MBA programs reported growth, the highest change across any type of degree.

As many full-time MBA programs moved online, students who may not have considered studying online suddenly saw the benefits. The 2021 MBA.com Prospective Students Survey found that just over a fifth of students were more likely to consider online learning as a result of COVID-19.

For many, however, Online MBAs can’t fully replace what a full-time MBA can offer—whether that’s authentic networking or immersive learning. Instead, there’s growing momentum behind a hybrid model, where student learning is split between online and the classroom.

Interest in hybrid programs has doubled between 2018 and 2021, from 10% to 20% of candidates, according to GMAC’s survey.

Hybrid programs offer the best of both worlds: the flexibility and accessibility of Online MBAs with the tangible physical benefits of a campus-based program.

Warwick Business School’s Distance Learning MBA has topped the Financial Times Online MBA rankings since 2016: unlike 100% online programs, the program supplements its primarily online tuition with select opportunities for face-to-face interaction.

Conclusion

An MBA may not be as prestigious as it once was, but that doesn’t mean no one should pursue one. Studies still show that those with an MBA earn more than those with a bachelor’s degree alone. According to the Graduate Management Admission Council (GMAC), MBA holders earn a median starting salary that’s 22 to 40 percent higher than bachelor’s graduates.

Besides a higher salary, an MBA can provide valuable networking opportunities you might not be exposed to otherwise. The connections you make while earning your MBA could lead to more career opportunities down the road. Additionally, if you’re exclusively focused on climbing the corporate ladder, an MBA provides a solid educational background and a great line on your résumé. Some traditional firms may even require it.

Online and hybrid MBAs will continue to offer a novel form of flexibility and accessibility when it comes to studying. They will attract candidates who wouldn’t have previously considered online learning, and candidates who wouldn’t ordinarily apply for business school. The integration of online teaching into hybrid MBA programs also offers the best of Online and full-time MBAs.

AI isn’t replacing MBAs – it’s redefining what they do. New hybrid roles are appearing that require both business acumen and AI fluency. These roles demand strong leadership, cross-functional collaboration, and the ability to connect technical innovation with strategic business value – all hallmarks of a top-tier MBA education.

The post The Future of MBAs: From the Switch of Employer’s Perception to AI Redefinition and the Emergence of Hybrid Programs appeared first on The European Business Review.

By Prof. Guido Stein, Salva Badillo, and Lucía Zelaya

The key to a successful negotiation is not embedded in knowledge or reasoning ability but in applying emotional intelligence. This essay explains the role of emotions in negotiations.

Emotion is not the enemy of negotiation, but an inseparable part of it.

Emotional intelligence—the ability to perceive, understand, and regulate both our own emotions and those of others—has proven to be a more decisive factor in achieving success in high-pressure situations than IQ. Contrary to what many believe, however, emotional intelligence is not an innate gift, but a skill that can be cultivated through introspection, practice, and self-observation.

Those who dare to master their inner world will not only make more effective agreements but will also gain a deeper knowledge of themselves.

1. The biology of emotions in negotiations

Decision-making is not a purely logical exercise, but a dynamic influenced by neural structures whose function is to process emotions, evaluate risks, and anticipate consequences. In the field of high-stakes negotiations, understanding these mechanisms is essential to optimize decision-making and achieve more effective and balanced results:

The amygdala. In crisis, the human mind reverts to a primitive state in which reasoning is weakened and instinctive response prevails. This response is triggered by physical threats—such as hostage-taking or a suicide attempt—and also occurs in the business environment, where high-pressure situations can trigger similar survival mechanisms.

The illusion of control and the inevitable role of the subconscious. Multiple studies have shown that the brain makes decisions before the conscious mind becomes aware of them. Benjamin Libet revealed a phenomenon known as readiness potential—an electrical signal in the brain that occurs up to 500 milliseconds before a person becomes aware of their intention to move. This finding suggests that the decision to act begins at an unconscious neural level and only later reaches conscious awareness.

The ventromedial prefrontal cortex (VMPFC). While these individuals retain their reasoning abilities, they struggle to make decisions because they cannot assign emotional value to different options.

This brain region plays a crucial role in evaluating alternatives by connecting past experiences to future options. According to the somatic marker hypothesis, emotions act as filters that attribute significance to each alternative, thereby facilitating decision-making. For example, a hostage-taker may make an explicit demand. However, to resolve the conflict a negotiator needs to identify the underlying interest driving their action, a need that may be conscious or unconscious. If the negotiation fails to align the concession with the dominant emotion, an agreement will remain out of reach.

In face-to-face negotiations, the VMPFC plays a key role in interpreting microexpressions—brief, involuntary facial reactions that reveal genuine emotional states. A negotiator who presents multiple options can assess their counterpart’s visceral reaction to each one.

The dorsolateral prefrontal cortex (DLPFC). The DLPFC is responsible for evaluating options in a rational and deliberate manner; it cannot make decisions independently and relies on emotional input from the VMPFC. The primary function of the DLPFC is to justify decisions that the brain has already processed at an unconscious level.

A barricaded individual may surrender based on an intuitive sense that continued resistance will have serious consequences, but rationalize their decision with statements such as, “After all, I’m a better person than my hostage, and it’s not worth it.”

The nucleus accumbens. This brain region is linked to the anticipation of pleasure in decision-making. It plays a key role in biases such as loss aversion and impulsivity in financial decision-making.

In a ransom negotiation, a kidnapper may initially demand €3 million—an amount that could take months to obtain and carries the inherent risk of being tracked down by authorities. However, when presented with the opportunity to receive €500,000 immediately, the kidnapper’s nucleus accumbens drives them to accept the more tangible and immediate offer.

2. Self-knowledge

A negotiator must recognize that emotions are an inherent part of the human condition; however, this does not mean they should exert absolute control over our decisions. Neuroscience has shown that while certain stimuli can automatically trigger emotions, the brain has the ability to rewire itself through neuroplasticity. This means that individuals can develop the ability to respond in a more balanced way, neutralizing impulses that might otherwise cloud their judgment in critical situations.

A negotiator must recognize that emotions are an inherent part of the human condition; however, this does not mean they should exert absolute control over our decisions.

In high-stakes negotiations, where the margin for error is minimal, emotional detachment is an invaluable asset. The goal is not to suppress or deny emotions but to acknowledge them and manage their influence with prudence and timeliness. Balance is maintained by consciously separating emotions from the surrounding chaos.

Several tools can help transform negotiations from a purely transactional exchange to a collaborative dialogue in which mental clarity and strategy take precedence over impulsiveness.

2.1. Identifying emotional triggers. Psycholo-gical research has shown that each individual has emotional “buttons” that are activated by past experiences or deeply ingrained beliefs. These triggers can provoke disproportionate reactions to certain situations. Reflecting on past episodes where our reaction was disproportionate can help identify the root of these impulses and progressively diminish their impact.

2.2. Metamorphosis map. Creating a timeline of significant events provides a clear visualization of our personal evolution. This self-reflection tool helps us identify lessons learned over time and set milestones for future growth, strengthening both our identity and our decision-making confidence.

2.3. Detachment journal. Keeping a record of daily situations where emotional detachment would have been beneficial offers valuable insight into how emotions influence our decision-making. Noting the situation, our emotional response, and an alternative approach grounded in detachment helps us to cultivate a more strategic mindset, making us less prone to impulsive reactions.

3. Cognitive biases

Heightened emotions can easily lead negotiators to fall prey to cognitive biases. These biases, which stem from automatic thinking, hinder an objective understanding of facts and can compromise the success of a negotiation. To identify biases and mitigate their impact, it is essential to understand their nature and mechanisms.

Daniel Kahneman, recipient of the 2002 Nobel Prize in Economic Sciences for his contributions to behavioral economics and psychology, posits the existence of two systems of mental processing:

• System 1: Fast, intuitive, emotional, and automatic.
• System 2: Slow, deliberate, logical, and conscious.

Cognitive biases arise when System 1 responds without the analytical intervention of System 2, leading to automatic decisions that may result in flawed judgments. These biases often manifest in subtle ways but can have critical consequences.

• Availability bias. This occurs when people assess the likelihood of an event based on how easily they recall recent or striking instances. The human mind tends to give greater weight to vivid or emotionally impactful events, even when they are not statistically representative.

Case:  In a hostage negotiation, an inexperienced negotiator who has recently been exposed to a high-profile case in which a hostage-taking ended in tragedy overestimates the likelihood that the current situation will escalate into violence. Driven by fear, the negotiator hastily agrees to the hostage-taker’s demands without considering alternative strategies.

• Anchoring effect. This occurs when the first number or piece of information presented in a negotiation establishes a reference point that shapes all subsequent assessments, even if the initial value lacks a rational basis.

Case: A hostage-taker demands €1 million for the release of a hostage. An inexperienced negotiator is anchored to this disproportionate figure and bases their strategy on it without considering objective data. An experienced negotiator, on the other hand, understands that hostage-takers typically set initial demands well above what they are willing to accept and uses this knowledge to structure the negotiation in a more realistic way.

• Confirmation bias. This is the tendency of individuals to seek out and prioritize information that reinforces their preexisting beliefs, while dismissing data that contradicts those beliefs. This distortion can result in biased interpretations of reality and poorly founded decisions.

Case: A negotiator who firmly believes that hostage-takers never yield if they perceive weakness ignores subtle signs of fatigue or hesitation in the captor. By failing to recognize these opportunities for persuasion, the negotiator misses a strategic window for achieving a peaceful resolution.

• Illusion of validity. This occurs when a person overestimates the accuracy of their own predictions, even in the absence of solid evidence. Excessive confidence in personal judgment can result in poor decisions and unnecessary risks.

Case: A negotiator, convinced that they can anticipate a hostage-taker’s reactions without relying on historical data or behavioral analysis, misinterprets the situation and makes counterproductive decisions.

• Halo effect. This occurs when a positive or striking characteristic of a person is generalized to other areas, creating a biased overall perception.

Case: A hostage-taker who speaks politely and dresses neatly may be perceived as reasonable and less dangerous. This bias leads the negotiator to underestimate the actual threat that the hostage-taker poses, compromising the safety of the hostages.

• Optimism bias. This refers to the tendency to underestimate risks and overestimate our own abilities. In crisis situations, this bias can create a false sense of control and lead to inadequate preparation.

Case: A negotiator who is overconfident in their ability to persuade assumes that they can convince the hostage-taker without a structured plan. This overconfidence diminishes the effectiveness of the negotiator’s intervention and makes the situation more dangerous.

• Hindsight bias. Once the outcome of an event is known, people tend to perceive it as having been predictable from the outset. This cognitive distortion can influence how past decisions are assessed and foster a fatalistic perspective on circumstances.

Case: If a hostage negotiation ends in violence, some observers might say that the outcome was inevitable. However, this view does not take into account an analysis of factors that could have influenced the course of events.

• Representativeness bias. This bias involves estimating the likelihood of an event based on stereotypes or past patterns rather than relying on objective statistical data.

Case: A negotiator who assumes that a juvenile hostage-taker is less experienced and therefore easier to manipulate develops flawed strategies that underestimate the captor’s abilities.

• Loss aversion. People tend to fear potential losses more than they derive satisfaction from equivalent gains. This bias can result in hasty and disadvantageous decisions.

Case: A negotiator who, for fear of losing hostages, quickly agrees to the hostage-taker’s demands without considering the long-term consequences weakens their position and increases the likelihood of similar crises in the future.

• Illusion of control. This bias occurs when individuals overestimate their ability to control random events, leading to excessive confidence in their ability to influence outcomes.

Case: A negotiator who assumes that their personal skill alone can guarantee the success of the negotiation—without accounting for external factors such as the emotional state of the hostage-taker or police pressure—makes reckless decisions that jeopardize the operation.

Being aware of these biases and actively working to mitigate them can significantly improve the quality of our judgments and reduce the risks associated with rash or uninformed decisions.

4. From anxiety to confidence

Anxiety is defined as distress or uneasiness about what is about to happen or what we fear may occur. It is not merely inner turmoil but a force that reminds us of both our vulnerability and our ability to anticipate future events. Those who enter a negotiation in the grip of fear tend to underestimate their own power, make low initial offers, concede too quickly to others’ demands, and sometimes leave the negotiation table prematurely. As a result, their deals tend to be less advantageous. In terms of how it applies to executives, several studies reveal that anxious negotiators close deals that are, on average, 12% less financially attractive than those negotiated by individuals who approach the process from a neutral emotional state.

The perception of negotiation as an anxiety-inducing activity stems from three key psychological factors:

• Lack of control. Negotiation arises from the need to obtain something that cannot be achieved unilaterally. The sense that success depends on the will of others generates tension and unease.
• Unpredictability. It is impossible to predict with certainty how cooperative or aggressive the other party will be, or to anticipate their reactions and strategies with complete accuracy.
• Lack of clear feedback. Even after reaching an agreement, uncertainty lingers. Doubts about whether the best possible outcome was achieved, whether too many concessions were made, or whether excessive pressure was applied fuel insecurity and self-criticism.

However, anxiety is not inevitable. Effective strategies exist to instill confidence and enhance negotiation skills. There are three key ways to mitigate the impact of anxiety and strengthen a negotiator’s position.

• Preparation. A lack of information intensifies the inherent uncertainty of negotiations, adding to the negotiator’s psychological tension. Understanding the counterpart—their interests, constraints, and alternatives—is essential before entering a negotiation. Defining clear objectives reduces uncertainty and strengthens self-confidence. However, many people rely too much on intuition and overlook preparation, improvising and merely hoping for the best outcome. This phenomenon is known as the myth of natural talent: When someone exhibits strong conversational skills, it is often assumed that they possess exceptional innate intuition.

The most skilled negotiators prepare in advance but also cultivate the ability to improvise in a natural way.

However, research suggests that this strategy is not the most effective. The most skilled negotiators prepare in advance but also cultivate the ability to improvise in a natural way. What is often overlooked is the time they dedicate to refining their communication skills, the attentiveness with which they listen, the way they connect ideas, and their ongoing efforts to improve their skills.

Flexibility. Adaptability is a natural consequence of thorough preparation. A flexible negotiator adjusts their strategy without losing sight of core objectives, enabling them to respond intelligently to unexpected developments. Maintaining an openness to alternative solutions helps reduce anxiety and expands the possibilities for reaching satisfactory agreements.

Flexibility is not at odds with preparation; on the contrary, the more prepared a negotiator is, the greater their confidence and ability to improvise effectively. A well-prepared negotiator does not rigidly adhere to a plan but instead adapts to circumstances without losing sight of the goal.

Practice. Anxiety thrives on the unknown. Regular exposure to negotiation scenarios reduces the emotional impact of engaging in this process, making it more familiar and manageable. In psychology, exposure therapy is used to treat phobias because repeated exposure to the situations that cause fear helps to reduce this feeling. Similarly, the more we negotiate, the more comfortable and confident we become.

Practical experience is one of the most effective ways to internalize learning. In education, the gap between knowledge and action—often referred to as the “knowing-doing gap”—is widely discussed: Understanding something intellectually is only the first step.

5. From anger to calmness

Anger, like anxiety, is an inherently human emotion—an expression of our survival instinct that, in its original form, helped us confront threats and adversity. However, while anxiety stems from fear of the future and personal uncertainty, anger is directed at our counterpart, creating a barrier that impedes understanding and communication. It is an expansive emotion that, when unchecked, clouds our judgment and fuels a vicious cycle of blame, defensiveness, and confrontation. Often, those who experience anger justify their outburst as a legitimate response to provocation, unaware that their own reaction fuels the escalation of the conflict.

In negotiations, anger often distorts our perception of reality, leading to a combative approach that reflects the so-called fixed-pie bias. This bias stems from the mistaken belief that any gain for the counterpart translates into a direct loss for us, reinforcing a zero-sum mindset that hinders productive dialogue. In addition to making collaboration difficult, anger leads to impulsive and often self-defeating decisions. It is no coincidence that people are more likely to lie to an angry opponent than to a calm one. Anger dehumanizes the other, leading us to reduce them to a mere threat rather than recognizing them as individuals with legitimate aspirations.

When we recognize that we have the capacity to voluntarily free ourselves from anger, we make a conscious decision to abandon self-pity and emotional stagnation. This does not mean ignoring perceived injustices or relinquishing our position in a negotiation, but rather understanding that anger is not a fixed state—it is a choice.

6. Handling the counterpart

In high-stakes negotiations, beyond irrational behavior, the captor or hostage-taker is often in a state of extreme impulsivity. They are like a reckless boxer throwing rapid, chaotic punches—not to land a blow, but to disorient, create turmoil in the dialogue, and erode the negotiator’s mental clarity. The first question is: How do we break through this wall of hostility and desperation? And the answer to that question is to offer security. In a state of unconscious vulnerability, people crave stability and certainty. However, offering security requires more than words and active listening; it demands mastery of strategic tools that, when applied effectively, can play a pivotal role.

Roger Fisher and Daniel Shapiro outlined five emotional concerns that influence negotiations and can serve as key tools for managing an emotionally agitated counterpart:

Appreciation. Everyone wants to feel that their thoughts and actions are acknowledged and valued. In addition to strengthening cooperation, appreciation reduces resistance and distrust. In a hostage situation, for instance, a negotiator who acknowledges the hostage taker’s suffering or desperation creates an avenue for empathy that can help ease initial tension.

Affiliation. Rather than confronting the other party, a negotiator can build connections that foster a sense of belonging. This approach is often observed in police negotiations, where officers, rather than making threats, emphasize shared experiences or common ground with the hostage-taker to reduce their perception of hostility.

Autonomy. Respecting the other party’s decision-making ability is crucial. Imposing a solution often triggers resistance and hostility. In a negotiation with an armed robber, for example, allowing them to make controlled choices—such as deciding whom they want to speak with or whether they receive food—reinforces their sense of control and helps prevent escalation to violence.

Status. Recognizing each person’s role in the negotiation is essential. If a negotiator disregards the other party’s need for recognition, the latter may react with disdain or defiance.

Role. When a counterpart feels that their role is being ignored or minimized, negotiations become even more complicated. A clear example is when a hostage-taker acts as a group spokesperson. Instead of discrediting them, the negotiator allows them to express themselves in that capacity, reinforcing their sense of significance. This, in turn, makes the individual more receptive to proposed resolutions.

Being aware of these emotional concerns and creating a more favorable terrain for negotiation lays the groundwork for the following:

Identifying the counterpart’s dominant emotions. Recognizing our counterpart’s emotional baseline—whether they are prone to anxiety, anger, or fear—helps us anticipate the thresholds beyond which they will react irrationally and avoid triggers that could escalate the crisis. Establishing this reference point also helps us avoid actions that may be contrary to their interests, needs, and goals. It is not uncommon to see individuals make decisions that clearly work against their own interests, raising the question of why they fail to recognize this.

Emotional payments. These symbolic concessions do not necessarily require giving up anything tangible; rather, they involve offering elements that provide reassurance and gradually guide our counterpart toward a more rational state. When a hostage-taker demands justice for a personal cause, giving them the opportunity to be heard—whether through the media or by a figure of authority—can be a turning point that allows the negotiation to move toward a peaceful resolution.

Reflection: the first victory

From a personal perspective, what truly influences a negotiation is the struggle between instinct and reason, between the visceral nature of emotion and the lucidity of thought. The first victory lies in not allowing ourselves to be overwhelmed by internal noise that amplifies the noise around us. If we become paralyzed by fear of what might happen, we will be unable to do anything sensible. A skilled negotiator does not blindly push forward but stays grounded in self-awareness and reflection. Each day is an opportunity to learn, adapt, and refine our approach.

About the Authors

Prof. Guido Stein – Professor of Managing People in Organizations and Director of the Negotiation Unit at IESE. PhD in Philosophy (Management), MBA from IESE. Partner at Inicia Corporate, specialized in M&A and Corporate Finance.

Salva Badillo – Professional negotiator in crisis situations. Certified HERMIONE® trainer in High-Intensity Negotiation. Director of The Trusted Agency in Spain, Latin America, and Eastern Europe.
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Lucía Zelaya – Bachelor’s in business administration and MSc in Big Data Science from the University of Navarra. Researcher in Managing People in Organizations Department at IESE Business School.

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By Vanessa Vershaw

The truth is out: women are not supporting each other enough in the workplace. Despite efforts to advance gender equality, the latest global gender gap report reveals only a 1% increase annually since 2016. In some countries, like Australia, we’ve even regressed to 2021 statistics. Jaw-dropping, right? But the reasons might not be what you think… 

While the struggle for gender equality is multifaceted and complicated by geopolitical unrest and outdated politics, there’s a hidden obstacle in workplace dynamics that significantly hinders women’s progress. This invisible force, often overlooked, is the paradox of the sisterhood—how some women treat other women in the workplace, creating additional barriers to advancement. 

The numbers are telling. US data from 2024 shows women bully other women at twice the rate they bully men. Specifically, 71% of bullies are male, with 55% targeting males and 45% targeting females. Among the 29% of female bullies, 67% target females and 33% target males. 

We’ve all heard of the ‘glass ceiling,’ the invisible barrier preventing women from reaching senior leadership roles. There’s also the ‘bamboo ceiling,’ which describes the barriers Asian Australians face in their careers. Now, we’re grappling with a third invisible ceiling: the sisterhood ceiling. 

Beware the ‘mean girls’ 

The sisterhood ceiling arises when women exhibit aggression and target other women at work through psychological and sometimes physical tactics, ranging from ‘mean-girl’ behaviors to severe bullying and job sabotage. Consider a story shared by a senior male leader in the resources sector. He described a general manager who asked his female office manager to conduct a “Hunger Games” to hire new recruits, putting potential personal assistants through a series of tough trials to see who was the fastest in typing up notes. The contestant who “survived” was offered the position with the firm. This behaviour, though extreme, is not uncommon in the workplace. 

Such antics contribute to significant workplace health and well-being concerns and productivity losses, costing the economy billions. Yet, we still don’t fully understand the psychology of female aggression and bullying in the workplace or how to address it. 

With fewer women at the top and a lack of role models, the sisterhood paradox highlights how organisational systems foster environments where conflict among women is likely. So, how do we tackle this issue? While there’s no quick fix, here are some steps to consider: 

1. Raise Awareness and Education: Training to recognise and understand different types of aggression and bullying and becoming aware of unconscious biases is crucial to figuring out which strategies to use as a one size fits all approach will not assist to tackle the different types of workplace aggression effectively. 
2. Promote Self-Awareness and Accountability: Encourage everyone to reflect on their behaviour and its impact on others, fostering a culture where problematic behaviours are called out. 
3. Build Supportive Networks and Partnerships: Women need advocates and personal advisors (both male and female) for guidance and support. Formal mentoring programs can be highly effective if they are run well. 
4. Review Organisational Policies and Leadership: Implement clear anti-bullying policies and encourage male leaders to support women actively. Ensure HR and leadership teams respond to bullying reports. 
5. Encourage Intergenerational Dialogue and Understanding: Facilitate discussions between younger and older generations of women to bridge gaps in expectations and experiences. 
6. Shift the Narrative on Societal Expectations: Promote a balanced view of women’s roles and responsibilities in the workplace, reframing expectations of how women should act and contribute. 

Creating a better tomorrow starts with us. It’s time to dream bigger and work together to create workplaces where everyone can thrive.

About the Author

Vanessa Vershaw is the author of The Sisterhood Paradox: The Psychology of Female Aggression at Work and a high-performance workplace psychologist and trusted advisor to executives and key decision-makers of ASX-20 and Fortune 100 companies globally. 

The post We Need to Talk About Women Bullying Other Women at Work & 6 Key Things We Can do to Change it appeared first on The European Business Review.

By Jiayi Huang and Xiangming Chen

From a battery maker to the world´s leading electric vehicle producer, BYD’s spectacular rise is an eventful journey fueled by dedication, tenacity, and consistent research and development. This analysis of the giant EV auto manufacturer´s success will help growth-oriented companies fine tune their strategy in the age of transition toward green mobility.

The Chinese EV company BYD, headquartered in the high-tech megacity of Shenzhen bordering Hong Kong, has ascended to the pole position in global green mobility. BYD not only overtook Tesla in selling more EVs in 2024 but also beat Tesla by having developed a more advanced charging system that can charge its latest cars in just five minutes to go 400 km (250 miles), relative to Tesla’s Superchargers, which take 15 minutes to add 320 km (200 miles). In addition, BYD offers its proprietary “God’s Eye” driver-assistance system on cars that cost just below $10,000. How did BYD rise so spectacularly to its current position from a budding battery maker in 1994? While much Western media reports on BYD’s rapid growth, we take an in-depth look into the company’s eventful journey and the real sources of its success over the past three decades.

After persistent investment in R&D for nearly 20 years, BYD achieved breakthroughs in key technologies of electric vehicles and took off in the global passenger vehicle market.

Since its founding in 1994, BYD has leveraged three transformative opportunities to develop its core technologies and expand its businesses around the world. The first opportunity was China’s integration into global supply chains after China intensified market reforms in the 1990s. Between 1994 and 2002, BYD developed a cost-effective system to manufacture batteries for top mobile phone companies such as Motorola. The second opportunity that BYD leveraged was the historic growth of China’s automotive market in the 21st century. BYD built a vertically integrated system to mass-produce internal combustion engine (ICE) and new energy vehicles. The third opportunity was the electrification of the global automotive industry in recent years. After persistent investment in R&D for nearly 20 years, BYD achieved breakthroughs in key technologies of electric vehicles and took off in the global passenger vehicle market. BYD’s founding and current president, Wang Chuanfu, acutely identified the three opportunities when they arose.

From 0 To 1: How BYD Established A Firm Footing In The Automotive Industry* 

BYD’s rise to a top battery supplier

Wang Chuanfu formally founded BYD by registering it in Shenzhen in February 1995 to leverage opportunities in the battery industry. Wang saw enormous potential in the battery market given the increasing demand for electronic products. Wang was a battery expert when he founded BYD. He moved from Beijing to Shenzhen in 1993 when he was assigned to manage a state-owned enterprise that produced nickel batteries. He discovered that the state-owned enterprise could not keep pace with market changes, so he created his own company. As China’s first special economic zone (SEZ), Shenzhen was a pioneer in China’s market reforms and opening to the world. Financial incentives like lower taxes provided by the Shenzhen government, coupled with bordering Hong Kong, created a favorable environment for entrepreneurially-minded people like Wang to pursue their economic opportunities. Wang obtained financial support from his old friends and several companies to found BYD. BYD started with a team of around 20 employees. BYD exemplified a wave of entrepreneurial start-ups around that time, a number of which later turned into highly successful global companies such as Huawei and Tencent (Chen and Ogan 2017).

BYD created cost-effective ways to produce high-quality nickel and lithium-ion batteries. Whereas its Japanese counterparts used automated processes to make nickel batteries, BYD leveraged abundant labor in China to develop a much cheaper method of production. Wang arranged labor and fixtures in an efficient way that achieved robotic functions. After making breakthroughs in nickel batteries, Wang began studying lithium-ion batteries which were more sophisticated and had a bigger market than nickel batteries. BYD soon became the first Chinese company to mass-produce lithium-ion batteries. Wang decided to target the biggest clients in the battery market so that BYD could learn about the highest standards for quality management. Many multinational companies began outsourcing to China around 2000 allowing BYD to become a supplier to Motorola and Nokia in 2001 and 2002 when BYD also underwent an initial public offering on the Hong Kong Stock Exchange, culminating its achievement as a company focused on producing batteries.

BYD’s great success as a battery maker, more than anything else, stems from Wang Chuanfu being a battery chemist at heart. BYD’s competitors quickly stopped trying to compete with Wang’s battery, which was far superior, and instead used BYD as their supplier. By driving BYD to improve its battery technology, Wang achieved great success in making BYD’s batteries better and cheaper than any competitor (Ogan and Chen 2016). Starting out as a battery manufacturer laid the most logical and sustainable foundation for BYD to enter and thrive in the automotive industry.

BYD’s entry into the automotive industry

After the early success in battery manufacturing, Wang Chuanfu made a bold decision to enter the automotive industry. Wang aimed to enter an industry that was bigger than the consumer battery industry and had connections with batteries. He saw the enormous potential of the Chinese automotive market. In the early 2000s, the Chinese government was reforming the automotive market and encouraging families to buy cars. Most people in China used motorcycles or bicycles for everyday transportation. Wang predicted that a historic number of Chinese people would buy cars over the next decade and that the automotive industry would be more energy-efficient and cleaner, creating opportunities for battery manufacturers. He was confident that BYD could produce high-quality cars at low costs after mastering the core technologies, just like its past experiences in battery manufacturing. BYD obtained the license to produce cars by purchasing the Qinchuan Automobile Company in 2003.

Qinchuan did not have full mastery of automobile technologies so Wang led his team to invent new cars. Although Wang was the most interested in electric vehicles, he understood that the technologies and market for electric vehicles were immature. Inventing ICE vehicles could be a transition and help BYD understand the automotive supply chain. BYD initially wanted to procure parts from external suppliers, but it was difficult to find suitable suppliers. Wang decided to pursue vertical integration. Vertical integration was time-consuming at first but enhanced the efficiency and reduced the costs of R&D in the long term. BYD’s current General Manager of the Branding and Public Relations Division, Li Yunfei, comments, “If you rely on external suppliers, they will not tell you their long-term plan for R&D. They usually provide you with the technologies that are the most profitable for them. Vertical integration helps BYD come up with comprehensive solutions to existing problems in automotive products.” BYD produced its first ICE vehicle model called F3 in 2005 and its first battery electric vehicle (BEV) model e6 in 2009. BYD launched F3DM (DM stands for dual modes) in 2008 and became the first company to sell plug-in hybrid electric vehicles (PHEV) in the world.

BYD started developing electric commercial vehicles in 2008. Wang realized then that it would still take a very long time to electrify passenger vehicles; roadblocks include the lack of the charging infrastructure, consumer distrust in relevant technologies, and the high prices of electric vehicles. But Wang saw at least two benefits of electrifying commercial vehicles. First, electrifying commercial vehicles could act as a buffer zone that educates consumers about electric vehicles. Second, electrifying taxis and buses could significantly reduce air pollution because they accounted for over one-third of air pollution from vehicles. The latter has stayed with Wang as a top consideration in BYD’s relentless pursuit of building more and better EVs as a worthy contribution to the climate cause.

Since 2013 BYD’s electric buses have entered major overseas markets such as the UK, the US, Japan, and India. By 2015, BYD K9 electric buses and e6 electric taxis have spread to over 190 cities in 43 countries and regions. BYD’s buses succeeded in different climates and regulatory contexts. For example, BYD delivered electric double-decker buses to London in the 2010s. In fact, Wang walked side by side with President Xi Jinping of China during the latter’s official visit to the UK in October 2015 when London bought more zero-emission electric buses from BYD (Chen and Ogan 2017). This purchase by a top global city with an iconic bus system went a long way to elevate BYD’s brand and global reputation. It also motivated BYD to solve the technological challenges in transforming the K9 model into a double-decker bus, such as a higher center of gravity and limited space for batteries.

Wang has the deepest understanding of the cutting-edge technologies at BYD. He knows how and when the current bottlenecks will be solved. Solving those bottlenecks will completely transform the customer experience.

BYD established a firm footing in the automotive market and managed to maintain its strategic focus on R&D for electric vehicles despite abrupt changes in market conditions. BYD sold around 400,000 to 500,000 vehicles every year in the 2010s. BYD’s revenue declined in 2012 and 2019, coinciding with fluctuations in the Chinese automotive market. The two troughs pushed BYD to increase the efficiency of its management system. In a system of vertical integration, some BYD factories lacked the motivation to reduce the costs and raise the quality of their products because they were guaranteed that their products could be sold to other factories in BYD. BYD thus made significant changes to its procurement system. It used external suppliers as benchmarks and closed some underperforming factories. Some factories started competing with external suppliers in bidding processes.

The year 2019 turned out to be a very difficult one in BYD’s history. Its net profit for shareholders was only 1.6 billion RMB that year, but Wang Chuanfu still invested 8.4 billion RMB in R&D. Li Yunfei comments, “Wang has the deepest understanding of the cutting-edge technologies at BYD. He knows how and when the current bottlenecks will be solved. Solving those bottlenecks will completely transform the customer experience. His technological expertise has helped BYD to develop a long-term vision and strategy. He is like a prophet and a time traveler. He can maintain his strategic focus and avoid being distracted by fluctuations in external conditions. We firmly believe that our future is bright. We will be lucky if market tailwinds arrive sooner. We are prepared to withstand the difficulties if market tailwinds arrive later.”

Back in 2008, Wang described his three green dreams. The first dream was to develop affordable technologies to use solar energy. The second dream was to help humans store energy. The third dream was to build electric vehicles to reduce air pollution. BYD has invested in R&D for solar cells and energy storage power plants since the 2000s. The three dreams have motivated Wang to expand BYD’s presence in other green industries besides electric vehicles at a global level.

BYD’s Take-Off In The Global Automotive Market

BYD released the revolutionary Blade Battery in March 2020, leading an unprecedented wave of breakthroughs. The Blade Battery is a lithium iron phosphate (LFP) battery for electric vehicles and looks like a blade (Figure 1). The Blade Battery has higher energy density than traditional battery packs and increases the range of electric vehicles, which paved the way for upgrading the Dual Mode (DM) technology platform of hybrid vehicles. The earlier versions of the DM platforms primarily relied on fuel. The DM 4.0 platform, released in June 2020, primarily relied on electricity. BYD released the e-Platform 3.0 for battery electric vehicles in 2021, which Wang Chuanfu called the most essential step from electrifying vehicles to increasing their intelligence. The e-Platform 3.0 was a brand-new platform specifically designed for electric vehicles and integrated the most critical technologies of electric vehicles.

Powered by technological breakthroughs, BYD quickly diversified its vehicle models to meet different demands from consumers. BYD currently has four brands and five sales networks in China. The four brands are BYD, DENZA, FANGCHENGBAO and YANGWANG. The bestselling brand is BYD, which has two sales networks (Dynasty and Ocean). BYD stands for “Build Your Dreams”, symbolizing BYD’s green dreams. In China, vehicle models of the Dynasty network are named after Chinese dynasties (Qin, Han, Tang, Song, Yuan, etc.).  The Ocean network looks more youthful than the Dynasty network. DENZA offers a new luxury travel experience. FANGCHENGBAO, meaning “formula leopard” in Chinese, is a professional personalized brand. YANGWANG is a high-end brand. This quartet of brands has provided BYD with a broader and more diversified portfolio of assets.

Wang drives BYD

As BYD’s founder but going beyond a conventional founder’s role, Wang Chuanfu has played a pivotal role in shaping and sustaining both the technological core and cultural meanings of the BYD brands. Li Yunfei recalls, “Not everyone in the marketing team is an engineer, but our marketing is driven by a thorough understanding of our technologies. We have launched some pioneer technologies. Many consumers found engineering concepts very boring, so it was challenging to quickly impress our consumers with the strengths of our technologies. Wang was willing to work with the marketing team in the planning stage of marketing campaigns. He was like a professor giving lectures to students. He translated sophisticated technological concepts into plain words. After his lectures, Wang would double check whether we fully understood. He also has great admiration for traditional Chinese culture, which is reflected in the names of our Dynasty models and the logo of our high-end YANGWANG brand. When we started to design YANGWANG’s logo, Wang told us to borrow from the oracle bone script used in ancient China. While some of us proposed using the oracle bone script of ‘electricity’, other proposals went beyond the oracle bone script. Wang ultimately chose our proposal.” Given its thorough understanding of technologies and consumer demands, it was no surprise that BYD’s sales and revenue took off in 2022. Its revenue jumped from 216.1 billion RMB in 2021 to 424.1 billion RMB in 2022, pushing BYD onto the Fortune Global 500 list. Its revenue further rose to 777.1 billion RMB in 2024 (Figure 2). BYD produced its one-millionth new energy vehicle in May 2021 and its ten-millionth new energy vehicle in November 2024. By February 2025, BYD’s passenger vehicles reached 90 countries and regions (Table 1).

Wang’s personal influence is key to BYD’s brisk overseas expansion through a growing and more internationally informed team of senior executives. BYD sold 4.25 million passenger vehicles in 2024, and over 417,000 of those were sold in overseas markets. Since its first overseas office opened in the Netherlands in 1998, BYD has established over 40 branch offices overseas. BYD opened a factory in Thailand last year and is currently completing factories in Brazil and Hungary. Its overseas branches have gained extensive knowledge of local markets by selling batteries and commercial vehicles. Li Yunfei comments, “Many senior executives of our overseas branches have been working in BYD for over 20 years. They are familiar with foreign culture and BYD’s internal organization. They have laid a solid foundation for BYD’s overseas expansion. In addition, we have incorporated overseas talents into our teams.” Regarding Europe, Li adds, “We want to give European consumers more choices, which will benefit them. We have a high respect for automotive brands in Europe and been learning from the European brands. Market competition can motivate everyone to make progress.”

Wang Chuanfu has continued to prioritize innovation through R&D. In 2024, BYD invested 54.2 billion RMB in R&D expenditure, which increased by 35.7% year on year. In March 2025, BYD’s global workforce reached one million, and over 120,000 of those work on R&D. Li Yunfei comments, “A wise leader is essential to a company’s development. A few years ago, my team was planning to build a powerful public image of Wang Chuanfu like other companies but he asked us to stop as soon as he learned about our plan. He said that we should focus on communicating our technologies and products to the public instead of building individual heroism. People that have interacted with Wang have been impressed by his low-key manner. Over 80% of Wang’s meetings focus on technologies and lead to plans for the medium and long terms.”

From a corporate innovator to a global leader

Continued innovation has become the core DNA of BYD, leading to a series of technological breakthroughs in recent years (Figure 3). While recent, these innovations reflect BYD’s persistent and cumulative investments in R&D over the three decades of its rapid growth. BYD’s passion for innovation has been fueled by the larger environment of Shenzhen as its home city that strongly favors corporate innovation and has nurtured several innovative companies like Huawei and DJI in a dense technological ecosystem. Beyond Shenzhen itself, BYD has benefited from competing against many domestic and international automakers in China’s highly competitive EV market irrespective of government subsidies. It is no surprise that these competitive and innovation-conducive local and national environments have fostered BYD’s cumulative success as a leading corporate innovator.

As BYD has innovated from its home base, it has leveraged its innovative capacity in elevating the BYD brand globally and extending its market footprint across nearly 100 countries. Having spanned all segments of the global EV market, BYD has moved up and forward into one of the world’s leading automotive companies, and more importantly, as a pace-setter in green mobility. At a time when geopolitical turmoil has disrupted the global agenda on climate change and energy transition, BYD has proven as a robust and innovative corporate and national leader in pursuing that agenda.

About the Authors

Jiayi Huang is a senior specialist at BYD’s headquarters in Shenzhen. She researches on international political economy and works on overseas public relations for BYD. She holds a Ph.D. in political science from the University of Pennsylvania, a master’s degree in economics from Duke University, and a bachelor’s degree in economics and mathematics from Trinity College in Connecticut.

Xiangming Chen is Paul E. Raether Distinguished Professor of Global Urban Studies and Sociology at Trinity College in Connecticut and an Associate Fellow at the Center for Advanced Security, Strategic and Integration Studies (CASSIS) at the University of Bonn, Germany. He has published extensively on urbanization and globalization with a focus on China and Asia as well as a frequent contributor on “China in the World” to The European Financial Review and The World Financial Review. He has also conducted policy research for the World Bank, the Asian Development Bank, UNCTAD, and OECD.

Footnote

• The first two sections draw heavily from the Chinese book The Soul of Engineers, which BYD recognizes as its official history. This article including its illustrations also draws from other material and information compiled by BYD unless otherwise noted. The interview with Li Yunfei was conducted in March 2025 specifically for this article.

References

• Xiangming Chen and Taylor Lynch Ogan (2017). China’s Emerging Silicon Valley: How and Why Has Shenzhen Become a Global Innovation Center. The European Financial Review, December/January p. 55-62.

• Taylor Lynch Ogan and Xiangming Chen (2016) The Rise of Shenzhen and BYD—How a Chinese Corporate Pioneer is Leading Greener and More Sustainable Transportation and Urban Development. The European Financial Review, Feb/March p. 32-39.

• Shuo Qin and Yuejia Xiong (2024) The Soul of Engineers: BYD’s Rise During 1994-2024 (in Chinese). (Beijing: The CITIC Publisher).

The post BYD’s Rapid Ascent to the Global EV Leader appeared first on The European Business Review.

Today, the pressure to lead digital transformation, tackle sustainability challenges, and keep pace with constant change impacts roles, sectors, and industries. But while demand for transformation has surged, the supply of leaders with the subject expertise and strategic skills to deliver it hasn’t kept up. Organizations are investing heavily in areas like AI, data, and ESG, but many still lack the people who can connect that knowledge to business strategy and create successful transformation that lasts.

That’s the gap the International Institute for Management Development (IMD) aims to close with the launch of the Executive Master in AI & Digital Business Transformation and the Executive Master in Sustainable Business Transformation.

The degrees offer a modular, flexible format and combine deep subject expertise with the strategic leadership skills needed to turn knowledge into enterprise-wide change. The goal is to better support professionals looking to step up, pivot, or accelerate their careers in the areas where business needs leadership most.

“These degrees are designed to help professionals become the go-to experts in digital or sustainable transformation,” says Misiek Piskorski, Dean of Executive Education and Professor of Digital Strategy. “We want to equip people with the tools, confidence, and credibility to lead what’s next in a way that fits their lives.”

What’s different about these degrees? 

The short answer? Flexibility without compromise.

These Executive Masters are designed to allow participants to balance study with their careers and life commitments. They adapt to what professionals actually need from a degree today. Instead of one fixed path, the degrees offer a more adaptive journey; one that gives structure where it’s helpful and freedom where it matters.

Instead of one fixed path, the degrees offer a more adaptive journey; one that gives structure where it’s helpful and freedom where it matters.

At the core of each degree are two foundation modules. The first builds deep expertise in either sustainable business or AI and digital transformation. The second focuses on how to lead business transformation. Both are made up of programs from IMD’s open program portfolio: a suite of short, focused executive programs that serve thousands of professionals every year.

From there, participants shape the rest of their learning through a curated selection of electives. These include a mix of online and in-person programs, as well as learning opportunities through IMD’s participation in the Global Network for Advanced Management (GNAM): a collaboration of top business schools offering shared programs and global exposure. This flexibility allows participants to focus on the areas most relevant to their goals while learning alongside diverse professionals tackling real-world challenges around the globe.

This format opens up something different from the typical cohort model. Instead of moving through the degree with the same group from start to finish, participants engage with a wider network of professionals at every stage. These are people from other industries, geographies, and roles who share a similar drive to grow and lead. That kind of variety not only keeps the experience dynamic but brings in fresh perspectives that sharpen thinking and spark new ideas.

But that doesn’t mean participants lose a sense of belonging. Executive Master participants still connect regularly with others in their degree through tailored workshops and shared touchpoints across the journey. It’s a shift from cohort focus to community focus, one that mirrors how transformation happens in organizations: across functions, across silos, and experiences.

In many ways, the open program portfolio is what makes this all possible. It allows participants to build a degree that reflects who they are and what they want to explore while keeping the quality, structure, and learning outcomes consistent. It also means participants benefit from IMD’s faculty and peer learning model, one that’s been tried, tested, and refined through decades of executive education.

Subject depth. Strategic reach. 

The open program portfolio is what makes this all possible. It allows participants to build a degree that reflects who they are and what they want to explore while keeping the quality, structure, and learning outcomes consistent.

Each Executive Master begins by building deep, practical expertise. In the AI & Digital Business Transformation degree, participants explore topics like AI, data strategy, emerging technologies, and digital innovation. The Sustainable Business Transformation degree offers topics such as circular economy, sustainability strategy, and managing and measuring sustainability impact.

But knowledge alone doesn’t move organizations forward. What sets these degrees apart is their focus on turning expertise into action. Participants learn how to influence decisions at the highest level and guide transformation with purpose.

Applied learning. Real-world value. 

From start to finish, these degrees are designed to be lived, not just studied. The learning happens in the context of real work, real challenges, and real ambitions. From engaging in interactive, case-based programs to exploring live business scenarios, everything is geared toward helping professionals connect what they learn to what they do.

This is supported by IMD’s continued investment in learning innovation. AI tools help participants stay focused, engaged, and supported as they move through their degree. Smart recommendations highlight relevant content to them. Nudges help build habits and accountability. Gamified learning and diagnostics allow for deeper reflection and sharper insight, all woven into the experience, not added on top.

Each degree culminates in a Capstone Project or Thesis. It’s an opportunity to go deep in an area that matters, whether that’s solving a business challenge in their organization or contributing new thinking to their field. Some participants may use the Capstone to design strategy or implement change inside their company. Others may choose to explore a research topic, build original insight, or lay the groundwork for a future pivot.

Throughout the process, participants are supported by IMD faculty and expert mentors. The result is a final deliverable that reflects both the learning and the leadership growth that’s taken place and one that can act as a powerful signal to organizations, peers, and future employers.

Who are these degrees for? 

The Executive Masters are designed for professionals with at least eight years of experience. People who’ve built strong foundations in their field and are now asking bigger questions about what comes next.

Some are specialists who want to connect their deep expertise to broader business strategy. Others are stepping into more senior roles and need the confidence, clarity, and skills to lead transformation across an organization. Many are looking to pivot into high-impact areas like sustainability or digital business and want the credibility to match their ambition.

Across the board, these are professionals who want more from their learning, as a chance to grow in a way that delivers lasting value.

In a world where skills are constantly evolving, these degrees are about building capabilities that are future-proof. Strategic thinking. Cross-functional leadership. The ability to influence decisions, shape outcomes, and lead in complexity.

A final word 

The Executive Masters mark a new chapter at IMD. But more importantly, they respond to what professionals are asking for: learning that fits into their lives, builds in-demand skills, and helps them lead where it counts.

These degrees are focused on what matters most right now, giving leaders the depth, perspective, and strategic tools to grow their careers and create meaningful impact.

— David Bach, IMD President and Nestlé Professor of Strategy and Political Economy

For professionals ready to take that next step, these degrees offer a powerful way forward.

Explore the new Executive Master degrees at IMD:

• Executive Masters in AI & Digital Business Transformation → 
• Executive Masters in Sustainable Business Transformation → 

About the International Institute for Management Development (IMD) 

The International Institute for Management Development (IMD) has been a pioneering force in developing leaders and organizations that contribute to a more prosperous, sustainable, and inclusive world for more than 75 years. Led by an expert and diverse faculty, with campuses in Lausanne and Singapore, a Management Development Hub in Shenzhen and an Innovation Hub in Cape Town, IMD strives to be the trusted learning partner of choice for ambitious individuals and organizations worldwide. Our executive education and degree programs are consistently ranked among the world’s best. Through our research, programs, and advisory work, we enable business leaders to find new and better solutions, challenging what is and inspiring what could be. To learn more, visit www.imd.org.

The post Bridging the Gap between Expertise and Impact: Inside IMD’s New Master’s Degrees appeared first on The European Business Review.

By Joerg Niessing and David Dubois 

Amid the rise of GenAI, executives must master prompt crafting to optimize their marketing and sales strategies.

In the ever-evolving world of digital marketing, the ability to craft impactful, audience-centric campaigns has become both an art and a science. By the end of 2025, AI is expected to drive 95 percent of customer interactions in some capacity.

Central to this evolution is the growing importance of prompts—carefully unstructured inputs that guide AI tools and systems to generate creative, targeted, and data-driven outputs. By mastering the “art of prompting,” brand and sales executives can augment and transform their strategies, foster deeper engagement, and drive tangible results. For chief marketing officers (CMOs) and marketing leaders, mastering prompts is no longer a technical skill but a leadership imperative.

Why prompts matter in marketing strategy

Prompts are unstructured, often textual inputs that direct GenAI-powered tools to produce specific responses or outputs. Acting as a bridge between prescriptive inputs by humans and AI capabilities, they translate strategic goals into actionable content. These inputs range from straightforward instructions (e.g., “generate an Instagram caption for a new luxury watch”) to more specific requests (e.g., “create a five-part email sequence promoting a new sustainable fashion collection, emphasizing ethical sourcing and exclusivity).

Prompts have a wide range of applications, including (but not limited to) competitive analysis, online presence and SEO (search engine optimization) audits, marketing and brand positioning, and channel strategy and execution. In short, prompts inform, augment, and/or transpose strategic marketing goals into actionable outputs by AI systems.

Here are four ways effective prompting can ensure big wins for brands.

1. Personalization at scale

One of the most significant challenges in digital marketing is balancing scale with personalization. With the right prompts, brands can create hyper-personalized campaigns tailored to different audience segments.

A prompt such as “generate a personalized itinerary for a couple visiting Paris, emphasizing hidden gems and romantic spots” ensures that content resonates with travelers’ unique preferences.

For instance, L’Oréal’s GenAI Beauty Content Lab, CREAITECH, has started training GenAI to recognize the unique visual codes of the brands in their portfolio by leveraging logos, imagery, styles, packaging, typography, and colors. This enables the company to launch innovative campaigns faster and generate customized product recommendations for millions of users based on their individual preferences and skin types.

Then there’s the hospitality industry, which has the most potential to create significant value from AI, according to a study by McKinsey. Many operators, including Airbnb, increasingly utilize prompt engineering to power tailored travel suggestions for users. A prompt such as “generate a personalized itinerary for a couple visiting Paris, emphasizing hidden gems and romantic spots” ensures that content resonates with travelers’ unique preferences. This approach has helped Airbnb achieve a 30 percent increase in click-through rates on email campaigns.

2. Speed and efficiency

Prompts significantly reduce the time and resources spent on content creation, enabling marketers to move from ideation to execution more quickly. For example, in March 2023, Coca-Cola used AI-driven tools during its “Real Magic” campaign to encourage the creation of hundreds of variations of advertising copy and visuals to suit different markets. Within minutes, more than 120,000 AI-powered pieces of content (prompted by real humans) were posted.

Similarly, Nike uses prompts to fuel dynamic campaigns tailored to local markets, particularly in out-of-home advertisements. During the Paris 2024 Olympics, Nike integrated AI into their marketing strategy through AI-led billboards in cities across the United States, Europe, South America, and Asia that updated promotional messages in real-time based on the latest results. Whenever an athlete featured in the campaign won an event, the billboards immediately displayed the winning athlete, mirroring the thrill and uncertainty of the Games. Thanks to this strategy, Nike saw a peak in website visits on 31 July 2024, reaching two million visitors. Of these visits, 86,900 resulted in a sale. This increase in site traffic contrasted sharply with declines observed by competitors such as Adidas, Hoka, and On during the same period.

3. Consistency across channels

In today’s omnichannel environment, maintaining brand voice and consistency is crucial. Prompts ensure that messaging aligns with brand values, regardless of the platform. A prompt such as “Write a LinkedIn post and a corresponding Instagram caption about our new electric vehicle” ensures greater consistency while optimizing content for platform-specific formats and audiences.

4. Enhanced creativity

AI tools powered by prompts can act as creative collaborators, pushing the boundaries of what marketers can imagine. Marketing and sales leaders can use prompts to explore bold, unexpected ideas that go beyond traditional campaigns. For instance, Sephora launched the Sephora Skin IQ tool, which provides personalized beauty recommendations and tutorials. Prompts such as “suggest a lipstick shade to match an olive-toned complexion” allow for expert advice to be disseminated through digital channels, delivering value instantly. The tool boosted user satisfaction, and Sephora’s skincare sales grew by 35 percent following its introduction.

How CMOS can craft (more) effective prompts

To unlock the full potential of AI, marketing and sales leaders must learn how to craft effective prompts. Here are four key best practices:

1. Be specific: Clearly articulate the desired outcome, objective, or message. Instead of stating “write an email,” opt for “write an email to first-time customers offering a 10 percent discount on their next purchase, emphasizing fast delivery and eco-friendly packaging.”.
2. Incorporate context: Provide relevant details about the culture, market, audience, channel, or platform, as well as the objective. For example, “generate Instagram captions for a Gen Z audience in India, promoting a new line of sustainable and affordable sneakers.”.
3. Iterate and refine: Test different prompt variations to identify which deliver the best For instance, a fashion brand could test prompts like “write a product description for a high-end handbag” vs. “write a product description for a high-end handbag targeting millennials who value sustainability.”.
4. Align with data: Use prompts informed by customer insights and analytics. A luxury brand analyzing purchasing patterns might use a prompt like “suggest upselling strategies for customers who purchased premium leather jackets last winter.”.

The future of prompts

As AI continues to advance, the role of prompts in marketing and sales will only grow, with future opportunities including:

• Real-time prompting: AI systems capable of generating and refining prompts based on live data, such as trending topics or breaking news.
• Multimodal prompts: Expanding beyond text to include visual or auditory inputs. For instance, a prompt such as “Create a video ad for TikTok promoting a new sportswear line, using upbeat music and vibrant colors” could guide tools to produce complete video assets.
• Automated campaign optimization: AI systems that autonomously test and tweak prompts to maximize campaign performance.

Beyond crafting individual prompts, organizations must start adopting comprehensive, automated tools that manage and execute these processes simultaneously. Platforms like VSTRAT.ai enable companies to orchestrate the entire workflow, addressing strategic challenges such as designing customer journeys tailored to specific objectives, markets, and target audiences. Similarly, the Anthropic Console allows users to generate, test, and evaluate the effect of prompts through a built-in prompt generator.

These tools go beyond manual interventions by integrating advanced analytics, prompt generation, and content deployment into a seamless, easy-to-use system. By ensuring consistent and optimized messaging at scale, they empower marketing and sales teams to shift their focus from operational execution to strategic planning and creative innovation, while the platform manages the execution and continuous refinement autonomously.

In a digital era defined by rapid change and fierce competition, prompts have emerged as a critical tool for marketing and sales leaders to unlock creativity, enhance personalization, drive efficiency, and optimize their messaging. Brands that master the art of crafting and deploying prompts will stay ahead of the curve, empowering them to achieve measurable success and build long-term, personalized relationships with their audiences at scale.

About the Authors

Joerg Niessing is a Senior Affiliate Professor of Marketing at INSEAD and is passionate about bridging the academic and the business world on topics related to digital transformation, customer centricity, and data analytics. At INSEAD Joerg teaches executives and MBA students and he is the co-director of INSEAD’s programmes Leading Digital Marketing Strategy and B2B Marketing Strategies and Driving Digital Marketing Strategy (OOPS).

David Dubois is a tenured Associate Professor at INSEAD, specializing in data-driven innovation and customer-centric transformation. His research and teaching help professionals leverage digital insights for competitive advantage, particularly in areas like GenAI and social media. An expert in luxury brand management, his work has been featured in publications like The Financial Times and The Economist. He directs INSEAD’s digital marketing strategy programs and develops award-winning case studies.

The post GenAI: Prompting A Better Marketing Strategy appeared first on The European Business Review.

By Iolanda Triviño, Simon L. Dolan, and Pedro Cesar Martinez

In the changing world of employment, it’s more important than ever to understand the shifts in talent dynamics that are defining our future as organizational models evolve to attract, develop, and retain talent. Here we explore the evolution of Talent 5.0 and discuss the imminent arrival of Talent 6.0.

 The dynamics of workplace talent are in a process of profound change. As we transition into Talent 5.0 and soon even to Talent 6.0, it is essential to recognize not just the technological advancements, but also the human experiences and emotions that shape our workplaces.

This article aims to reassure and empower you, whether you’re an employee navigating career changes, a leader seeking to nurture your team, or a curious individual contemplating the implications of these shifts. Together, we can embrace a future where human potential is prioritized alongside innovation, fostering environments that support collaboration, creativity, and compassion.

It is crucial to invest in technology that amplifies creativity and collaboration, without losing sight of the importance of human skills such as empathy and critical thinking.

As we inch closer to the concept of Talent 6.0—where innovation transcends mere skills to embrace creativity, empathy, and adaptability—it’s essential to create environments where individuals feel supported and valued. Companies must prioritize upskilling and reskilling initiatives that not only enhance technical capabilities but also strengthen interpersonal connections. By investing in people and encouraging continuous learning, organizations can create a narrative of progress that resonates with employees at all levels.

Talent 5.0 emerges in a context of radical transformation of work, driven by advanced technologies and the need for key humanistic skills. The evolution from Talent 1.0, focused on efficiency and mechanization, to Talent 4.0, with a focus on digitalization, has given rise to a new era where the integration between humans and machines is fundamental, but with a deeper purpose: to achieve human well-being. Talent 5.0 and Talent 6.0 combine advanced technology and human skills in a work model that not only responds to the needs of the present but shapes the future of organizations.

The meaning and origins of talent 5.0

Talent 5.0 marks a turning point in the evolution of human talent in the digital and globalized era. Unlike previous versions, which focused primarily on technical skills or specialized knowledge, Talent 5.0 emphasizes the convergence between technology and human skills. This concept is aligned with Society 5.0, which seeks a balance between technological advances and human well-being, placing people at the center of development.

Talent 5.0 is characterized by its ability to adapt to rapid changes, learn continuously, and collaborate with emerging technologies. This talent is nurtured by values such as inclusion, creativity, and transformational leadership, driving the transition towards more agile and flexible organizational models in the context of the Future of Work.

In addition, Talent 5.0 is not defined exclusively by technical skills, but also by a shift in the mindset oriented towards opening up to change and the ability to combine human skills (empathy, creativity, leadership) with technological tools. The professionals who embody this model are prepared to face uncertainty and generate innovative solutions in a constantly evolving world².

Defining the fundamental principles in the new era of talent?³ 

Principle 1: Adaptability and Continuous Learning.

The evolution of talent has gone from being a simple physical workforce (Talent 1.0) to becoming a key human capital for innovation (Talent 5.0).

In a rapidly changing environment, adaptability and the ability to learn continuously are critical. Organizations must implement reskilling and upskilling programs so that their employees remain competitive in an ever-evolving market. This is one of the keys to ensuring continuous innovation in Talent 5.0. Google, for example, has established a model where its employees can use up to 20 per cent of their working time to work on personal projects that also support their professional growth. This approach fosters a culture of innovation and allows employees to develop new skills that can be useful to the company.

Principle 2: Transformational Leadership

Transformational leadership focuses on inspiring and empowering teams, rather than just managing processes. This type of leadership is key in the era of Talent 5.0, as it allows for the integration of empathy, a long-term vision, and the use of new technologies. Transformational leadership fosters innovation and adaptation to change. During the pandemic, Microsoft took a transformative leadership approach. Under the direction of Satya Nadella, the company promoted a culture of empathy and encouraged its employees to adopt new technologies such as Teams to maintain remote collaboration. This type of leadership has been crucial in maintaining motivation and productivity in uncertain times.

Principle 3: Inclusion and Diversity as Drivers of Innovation

Inclusion and diversity are fundamental pillars to promote innovation in the Talent 5.0 environment. Diverse teams, in terms of gender, culture, and thinking, tend to be more creative and effective at solving problems. Companies that prioritize diversity experience better performance and higher financial performance. A report by Deloitte shows that companies with more diverse teams consistently outperform those that don’t prioritize diversity. Teams that value different perspectives and experiences are more innovative and resilient.⁴ The same message was echoed recently by Dolan et al., who showed the principal features of a resilient organization.⁵

Principle 4: Comprehensive Employee Well-Being

Well-being is a key component of Talent 5.0. Companies that create comprehensive programs that encompass the physical, emotional, mental, and financial health of their employees are more successful at retaining talent. Holistic well-being not only improves productivity, but also contributes to creating a stronger and more cohesive organizational culture.

Salesforce has implemented wellness policies that include mental health coaching and support services. In addition, the company offers work flexibility to help its employees achieve a healthy work-life balance, which has significantly improved engagement and satisfaction levels.

Principle 5: Technological and Human Partnerships

Technology plays a key role in Talent 5.0, but its true value lies in how it enhances human capabilities. Artificial intelligence, automation, and big data unleash human potential, allowing employees to focus on more strategic and creative tasks. It is crucial to invest in technology that amplifies creativity and collaboration, without losing sight of the importance of human skills such as empathy and critical thinking. Unilever, for example, uses AI to streamline its hiring process, but maintains final interviews with people to ensure that key decisions are empathetic and human.

The evolution of talent 5.0

The evolution of talent has gone from being a simple physical workforce (Talent 1.0) to becoming a key human capital for innovation (Talent 5.0). In Talent 5.0, the integration of technology with human skills creates a necessary balance to meet the challenges of the Future of Work. This model puts the human being at the center, leveraging technology to increase its impact while promoting well-being, diversity, and adaptability.

Envisioning Talent 6.0

The concept of Talent 6.0 would represent the culmination of these emerging and disruptive trends, where work will not only be more flexible, digital and collaborative, but also more personalized, ethical and symbiotic with technology. Organizations will need to prepare for a future where talent will not simply be a resource, but a collaborative partner in the constant transformation of society and the planet.

Conclusion

Organizations that integrate the harmonious coexistence of technology and human skill will find themselves not only enhancing productivity but also cultivating workplaces that prioritize humanity, inclusivity, and well-being.

Talent 5.0 and Talent 6.0 represent a new era in talent management, where technology and human skills must coexist in a balanced way. Organizations that adopt this approach will not only improve their productivity, but also create more humane, inclusive, and wellness-oriented work environments. As the world of work continues to evolve, Talent 5.0 will be key to continue in the form of Talent 6.0 and both will contribute to building a more equitable and prosperous Future of Work.

We argue that the transformation of organizational culture is one of the fundamental pillars for new organizational models to be successful in the era of Talent 5.0 and Talent 6.0. Structural and operational changes within an organization cannot be implemented effectively without a company culture that supports and empowers them. In other words, the shift in organizational culture is not just a necessity, it’s a vital cornerstone for thriving in the age of Talent 5.0 and Talent 6.0. As we navigate this transformative landscape, it’s clear that mere structural or operational changes are insufficient without a nurturing and supportive culture to back them up. Organizations that integrate the harmonious coexistence of technology and human skill will find themselves not only enhancing productivity but also cultivating workplaces that prioritize humanity, inclusivity, and well-being. As we embrace this evolution in how we work, it’s crucial to recognize that Talent 5.0 holds the promise of a more just and prosperous future, a future where every individual can thrive. With empathy and understanding at the heart of this journey, we can collectively foster an environment that empowers each member of the workforce, ensuring that we move forward together toward a brighter tomorrow.

About the Authors

Iolanda Triviño is a Futuristic Strategist & Talent Transformation Specialist. Her approach to collaborating with teams and organizations is driven by three key pillars: Creativity, Technology, and Community. With nearly 30 years of experience in the business sector, Iolanda has successfully led teams and managed projects, combining a strategic vision with agile and humanistic execution. Since 2014, she has served as the President of the Talent Commission for 22@Network, the IT and Innovation business association in Barcelona. In 2012, she founded Valkiria Hub Space, an innovation hub in Barcelona, and the International Open Innovation Community, focusing on the Future of Work and the Talent Transformation Institute for Futures (IFF). She is the co-author together with Simon L. Dolan and others, of an a forthcoming book titled The Future of Work & Talent 5.0,due to be published in Spanish by McGraw Hill in Madrid.

Simon L. Dolan is full professor, senior researcher and Director of Programs at Advantere School of Management (affiliated with Comilla, Deusto and Georgetown Universities). He is the former Future of Work Chair at ESADE Business School. He has published 85 books (in multiple languages) and over 150 articles in referee journals. He is also the co-founder and President of the Global Future of Work Foundation (www.globalfutureofwork.com). His work, consulting, and research is about values, leadership, coaching, stress management, and resilience, as well as issues connected to the future of work. He holds an MA and PhD from Carlson Graduate School of Management at the University of Minnesota. He is a former editor of cross-cultural management and member of the editorial board of half a dozen scientific journals. His full CV can be found at: www.simondolan.com

Pedro Cesar Martinez Moran is the Director of the Master’s in Talent Management at Advantere School of Management. He teaches at Universidad Pontificia Comillas and is also a member of academic research groups. In addition to his academic work, he has held various roles as a senior executive and consultant. Currently, he serves on the executive board of the Global Future of Work Foundation (www.globalfutureofwork.com).

References

1. The article is based on Chapter 3 in a forthcoming book on the future of work that will be published in Spanish by the McGraw Hill company in Madrid. The authors wish to thank Mario Raich, Dave Ulrich and Chad Albrecht, coauthors of the digital textbook on The Future of Work (myeducator.com) for comments and suggestions on an earlier version of this paper.

2. For more, see Mario Raich, Simon Dolan, Dave Ulrich, and Claudio Cisullo (2017) “Gloom vs. Bloom of the Future of Work: Can We Chart a Positive Roadmap?”, The European Business Review, August 2.

3. To delve into the success story of Microsoft under the leadership of Satya Nadella, you can refer to the McKinsey article titled “Microsoft’s Next Act,” which analyzes how Nadella has driven innovation and organizational change within the company. https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/microsofts-next-act?utm_source=ccom

4. Deloitte reference article about DEI best practices and high-performance results in teams https://www2.deloitte.com/us/en/insights/focus/human-capital-trends/2017/diversity-and-inclusion-at-the-workplace.html?utm_source=chatgpt.com

5. Simon L. Dolan, Adnane Belout, Jean-Luc Cerdin, and Javier Casademunt (2024), “Towards the Building of Organisational Resilience: Uncovering the Key Features”, The European Business Review, May 27.

The post Navigating the New Frontier: Embracing Talent 5.0 While Paving the Way for Talent 6.0 appeared first on The European Business Review.

Having led others for so long, executives close to retirement often struggle with the prospect of leaving and slowly fading into the background. In this guide, Michael Watkins and Chris Donkin outlined how senior leaders can plan, prepare, and even look forward to a fulfilling life after retirement.

When Reed Hastings announced his departure as CEO of Netflix in January 2023, his succession felt natural and even inevitable. The same was true when Jacinda Ardern stepped down as Prime Minister of New Zealand that same month. Both transitions appeared effortless, but such smooth handovers are rare. Most senior leaders struggle significantly with the decision to step down, often holding on long after their optimal departure date.

If you’re a senior leader contemplating retirement, you are likely facing this struggle firsthand. Your challenges are more complex and nuanced than most succession literature suggests. Through our research and extensive work with retiring executives, we have found that the barriers to a successful transition are primarily psychological rather than practical—and addressing them requires a deep understanding and strategic action.

Understanding the inner struggle

The psychological barriers to retirement run far deeper than most leaders initially recognize. These barriers are not merely professional concerns but profound psychological constructs built and reinforced over decades of leadership. They are intricately woven into the fabric of one’s identity, self-worth, purpose, and mortality. Understanding these barriers and acknowledging their power is the crucial first step toward navigating a successful transition.

The Identity Paradox

The traits that propelled you to leadership and sustained your success can become significant obstacles in recognizing when it’s time to step down. Determination, resilience, unwavering commitment, and the ability to overcome challenges have defined not just your leadership style but your entire approach to life. The cognitive dissonance becomes fundamental: how can stepping away be the right choice when persistence has always been the answer? This paradox explains why many capable leaders hold on too long, potentially compromising their organizations’ future success and their own legacies. The traits that were once assets become liabilities in the face of succession.

The Emotional Reality

The intellectual understanding of retirement timing often collides with emotional unreadiness. This disconnect between rational acceptance and emotional resistance creates a complex internal struggle that can paralyze decision-making. The emotional dimension of retirement extends far beyond the simple fear of change—it encompasses feelings of loss, questions of self-worth, and deep-seated anxieties about the future.

The Support System Shift

The corporate infrastructure surrounding senior leadership is an invisible yet essential part of daily operations. This support system goes beyond mere convenience; it extends your capabilities and amplifies your impact and efficiency. The potential loss of this infrastructure is more than a practical challenge; it signifies a fundamental shift in how you interact with the world and your ability to create change.

The Existential Question

Retirement forces a confrontation with the end of a career and questions about personal legacy, mortality, and meaning.

The most profound challenge is confronting the existential implications of retirement. For leaders who have dedicated decades to their organizations, this role transcends mere employment—it becomes a core part of their identity and purpose. Retirement forces a confrontation with the end of a career and questions about personal legacy, mortality, and meaning. This existential reckoning demands a fundamental reevaluation of how you define yourself and your worth beyond your professional achievements. The challenge is not just about leaving a role; it’s about reconceptualizing your place in the world and your sources of meaning and purpose.

Managing the psychological transition

The psychological journey of retirement requires as much strategic planning as the operational handover of your role. While organizations typically have detailed protocols for succession planning, the psychological transition demands equal, if not greater, attention. This internal journey must be approached with the same rigor and strategic thinking that characterized your leadership career.

Understanding Your Emotional Timeline

Research has identified distinct emotional phases that executives typically experience during retirement transitions. The journey begins with an anticipatory phase marked by mixed emotions of anxiety and excitement. Many leaders enter a period of euphoria and relief upon retirement—a psychological unleashing from years of pressure and responsibility. This initial honeymoon phase, however, typically gives way to a more complex emotional landscape.

The second phase often brings unexpected challenges as the reality of the transition sets in. This period can involve feelings of disorientation, loss of purpose, and questioning of identity. The timing and intensity of this phase vary, but its arrival is nearly universal. Understanding this emotional arc helps normalize the experience and provides a framework for managing these challenges proactively.

The final phase involves reinvention and renewal, where leaders begin to craft their new identity and purpose. This stage requires active engagement in creating meaning beyond traditional professional achievements. The timeline for reaching this phase varies significantly, and preparation, support systems, and individual psychological readiness influence it.

Creating Psychological Anchors

The transition from structured leadership to retirement requires establishing new psychological foundations. These anchors serve as stabilizing forces during periods of uncertainty and change. They provide continuity of purpose while allowing space for new growth and discovery.

The transition from structured leadership to retirement requires establishing new psychological foundations. These anchors serve as stabilizing forces during periods of uncertainty and change.

Effective psychological anchors combine structure with flexibility, maintaining connections to areas of expertise while fostering new interests and relationships. They should be deliberately designed to support intellectual engagement and emotional well-being. The key is creating systems that provide stability without recreating the constraints of corporate life.

Working with Transition Coaches

Professional support during this transition can be invaluable. Transition coaches specialize in the unique psychological challenges faced by retiring executives. They bring expertise in identity reformation, status adjustment, and creating new purpose narratives. Their role extends beyond traditional executive coaching, focusing specifically on the psychological dimensions of retirement.

These specialists help leaders navigate the complex terrain between their executive identity and their emerging post-retirement self. They provide tools for managing the psychological aspects of transition, from processing the loss of power and influence to developing new sources of meaning and fulfillment.

The coaching relationship offers a structured space for exploring anxieties, testing new ideas, and developing strategies for emotional resilience. It provides accountability and support while helping leaders maintain perspective during challenging transition phases. Most importantly, it helps transform what could be a period of decline into an opportunity for growth and reinvention.

This work often involves developing new metrics for success, redefining relationship dynamics, and creating frameworks for decision-making in this new phase of life. The goal is not to eliminate the transition challenges but to develop the psychological tools and perspectives needed to navigate them effectively.

Building meaningful post-retirement activities

The transition from executive leadership to retirement requires a fundamental shift in the conceptualization of engagement and purpose. The challenge is not to fill time—your network and reputation will generate more opportunities than you can accept—but to create a portfolio of activities that provides genuine fulfillment and leverages your capabilities in meaningful ways.

Beyond Traditional Board Work

While board positions represent a natural extension of executive experience, the most fulfilling post-retirement careers often transcend conventional corporate roles. The key lies in identifying opportunities that align with your interests while allowing you to apply your leadership experience in fresh contexts. Consider roles that challenge you to think differently, engage with new demographics, or address problems from different angles than those you encountered as an executive.

Creating Impact Through Teaching and Mentoring

The transmission of knowledge and experience to future leaders offers a particularly rewarding path for retired executives. Teaching and mentoring roles provide intellectual stimulation while offering the opportunity to shape future business leaders. These roles demand a different kind of leadership—one focused on developing others rather than directing outcomes—and often lead to unexpected personal growth as you articulate and examine your own leadership principles and experiences.

Entrepreneurial Ventures with Purpose

Post-retirement entrepreneurship fundamentally differs from traditional business leadership. Retired executives can pursue ventures driven primarily by purpose and passion, free from the pressures of shareholder expectations and quarterly results. These endeavors often focus on solving societal challenges or addressing market gaps identified during their executive careers. This allows them to combine their business acumen with personal values in ways not always possible in a corporate setting.

Navigating family dynamics

The personal aspect of retirement can be just as challenging as the professional shift. Moving from having limited family time to being constantly present demands careful navigation and clear communication. This change influences not only daily routines but also the core dynamics of relationships that have developed over decades of executive life.

Redefining Domestic Roles

The domestic sphere often has well-established systems and patterns developed over years of executive focus. Retirement requires carefully renegotiating roles, responsibilities, and decision-making processes. This adjustment needs sensitivity to existing patterns and recognition that efficiency in domestic matters may not align with corporate management principles.

Managing Expectations

Retirement expectations often differ significantly among family members. These differences extend beyond daily routines to encompass fundamental questions about lifestyle, time allocation, and future plans. Resolving these differences requires the same level of strategic thinking and communication you applied to corporate challenges but with an added layer of emotional complexity.

Creating New Shared Experiences

The development of new shared activities and interests becomes crucial in retirement. This process involves more than simply spending more time together—it requires building new patterns of interaction and finding fresh ways to connect outside the familiar context of business life. The goal is to develop activities that create mutual engagement while respecting individual interests and needs.

Maintaining Personal Space

Preserving individual autonomy while increasing togetherness becomes a crucial challenge in retirement. This balance requires a conscious effort to maintain separate interests and activities while building a new shared life. The key is developing patterns that allow for independence and togetherness, creating a sustainable rhythm for this new phase of life.

Making the transition work

The practical aspects of retirement require as much attention as the emotional and relational dimensions. Time management becomes more complex when one moves from a structured corporate environment to self-directed days. The challenge is creating enough structure to maintain purpose and productivity while preserving retirement freedom.

Financial planning should go beyond traditional retirement considerations to include the practical aspects of new activities and ventures. This planning must address both personal fulfillment and practical needs, creating a framework that supports your chosen post-retirement activities while ensuring long-term security.

Cultivating and maintaining support networks is crucial during this transition. These networks should go beyond professional connections and include individuals who offer emotional support and guidance during this significant life change. The aim is to build a diverse support system that helps people navigate retirement’s practical and emotional challenges.

Looking forward

The most successful transitions we’ve observed share a common element: the retiring leader shifted their mindset from loss to creation. They viewed retirement not as the end of their leadership journey but as the beginning of a new chapter.

The art of stepping down lies not in denying these psychological barriers but in acknowledging and working through them while building a meaningful next chapter.

The most successful transitions we’ve observed share a common element: the retiring leader shifted their mindset from loss to creation. They viewed retirement not as the end of their leadership journey but as the beginning of a new chapter where their experience and wisdom could be applied in different, often more personally meaningful ways.

Your next chapter awaits. The question is not whether you will write it but how you will approach it. Will you hold on for too long, potentially diminishing your legacy? Or will you begin now to create a transition that honors both your achievements and your organization’s future?

The goal is not to replicate the intensity and structure of executive life but to create a new chapter that provides meaning, impact, and personal fulfillment while utilizing the valuable experience and insights gained throughout your leadership career. By recognizing the psychological challenges and actively working toward your next chapter, you can create a transition that meets both your personal needs and your organization’s future.

About the Authors

Michael Watkins is a professor of leadership at the IMD Business School, co-founder of Genesis Advisers, and a bestselling business author of books including The Six Disciplines of Strategic Thinking and The First 90 Days.

Chris Donkin is a Managing Partner at Savannah Group and co-lead of the firm’s Board Practice, advising clients on next generation leadership succession.

The post The Executive’s Guide to Retirement: Making Peace and Building Your Next Chapter appeared first on The European Business Review.

By Carlos Rey

Psychologists have long battled to formulate frameworks that allow us to understand and interpret the human psyche. Predictably, their findings have often been complex and difficult to apply in an everyday context. Here, Carlos Rey presents a new method that is both practical and intuitive.

Diagnosing personality is useful for various applications in organizations. An effective diagnostic method can assist in enhancing self-awareness and personal development, making informed hiring decisions, facilitating better communication between individuals, and aiding in the development of balanced and cohesive teams.

Philosophy and psychology have long explored personality, from Hippocrates’ temperaments to modern methods like DISC, MBTI, 16PF, and Enneagram. Each offers unique utilities based on their foundations.

In this context, the DPMC Foundation and the Management by Missions and Corporate Purpose Chair of UIC have developed the Alpha-Beta-Gamma method. This new diagnostic tool uses a philosophical-anthropological approach to enhance interpersonal relationships with an easy-to-apply diagnosis.

Personality dimensions

The Alpha-Beta-Gamma method examines three fundamental dimensions of personality: Head, Heart, and Hands¹. The Head refers to rationality, planning, and objectivity, which involves structured and logical thinking. The Heart includes emotions, empathy, feelings, and emotional intuition, highlighting elements that enable emotional connection and understanding of others. The Hands represent action orientation, proactivity, pragmatism, and experience-based intuition, emphasizing the ability to perform tasks effectively and practically, based on experience and direct action.

Understanding these three dimensions is essential for a comprehensive view of an individual. Each dimension offers key traits that together enhance self and mutual understanding. Three profiles emerge from combining these dimensions in pairs:

• Alpha (Head-Hands): Individuals in this category adeptly merge rationality with practicality, exhibiting pragmatic planning driven by a strong sense of responsibility and duty. Nevertheless, their limited engagement with emotional aspects, both personal and interpersonal, may cause them to be perceived as utilitarian and insensitive.
• Beta (Head-Heart): These individuals seamlessly integrate emotions with rationality, displaying depth and charisma while connecting with both their own motivations and those of others. However, their lesser inclination towards action-oriented approaches can result in their being viewed as overly general and impractical.
• Gamma (Heart-Hands): This group effectively combines emotional insight with action, demonstrating intuition, creativity, and motivational skills that propel initiatives and practical solutions with enthusiasm and passion. Nonetheless, their reduced focus on logical thinking may lead to perceptions of superficiality and instability.

Diagnosis

For years, we have diagnosed personality across a diversity of professionals using this model. We employ systematic self-observation and introspective reflection in three steps, both individually and in group workshops:

Step 1: Understanding

The first step involves presenting individuals with a symbolic triangular representation of the three dimensions—Head, Heart, and Hands—at the vertices of the triangle, and the three personality profiles on the sides (see figure 1). Next, participants are asked to describe each of the three dimensions in their own words to ensure they understand the scope of each one. The concepts related to each dimension, as outlined in table 1, are used as a guide.

Step 2: Exploration

After understanding the three dimensions of the model, individuals are asked to position themselves at the vertex (the dimension) with which they feel the greatest affinity. Some participants choose the Head, others the Heart, and others the Hands. After identifying their chosen dimension (vertex), they are asked to describe the advantages and disadvantages of this vertex and the other vertices. This exercise promotes introspective reflection and self-observation, preparing them for the next step.

Step 3: Positioning

We prompt individuals to position themselves on the side of the triangle with which they identify most strongly (Alpha, Beta, Gamma), thereby determining their personality profile. Subsequently, we encourage them to reflect on their choice and explain the characteristics of the selected profile, including its description, strengths, and weaknesses. For guidance, we refer to the concepts outlined in table 2.

The Alpha-Beta-Gamma method enables individuals to conduct self-diagnosis with considerable ease. With sufficient familiarity and training in the method, they can also identify the personality profiles of those they interact with. Our observations indicate that diagnosing individuals with whom there is greater affinity or closeness is more straightforward. However, with adequate training, it is also feasible to accurately determine the profiles of less-familiar individuals.

Creating powerful connections

After individuals acquire the skills to perform self-diagnosis and diagnose others, they are prepared to implement the method. This method aims to achieve two primary objectives: fostering connections between people with diverse profiles and enhancing awareness of the limitations present in relationships among similar profiles.

When two people have differences, complementarity may occur, where each provides something the other lacks. However, it is not always straightforward to determine what that specific “something” is. The Alpha-Beta-Gamma model helps identify complementarity between different profiles in three areas: (1) “what we have in common,” (2) “what you can contribute to me,” and (3) “what I can contribute to you.”

When two people have differences, complementarity may occur, where each provides something the other lacks.

In “what we have in common,” the method facilitates the creation of powerful connections between people, from self-confidence and the desire to find common ground with others. The key is that each pair of different profiles always has a common vertex: Alpha and Beta understand each other in the Head, Beta and Gamma in the Heart, and Alpha and Gamma in the Hands. This ability to easily find “what we have in common” improves communication, fosters trust, helps resolve conflicts, and enhances leadership.

The method also allows for identifying areas of complementarity between individuals. The concept is that anyone with a different profile can offer support in areas where one may be less developed, and vice versa. For instance, an individual with an Alpha profile can provide practical intuition and pragmatism to someone with a Beta profile, while a person with a Beta profile can offer emotional intuition and empathy to someone with an Alpha profile. This applies to any combination of different profiles, facilitating a mutual exchange of skills (see table 3).

This understanding of relationships allows us to approach people with different profiles from a perspective of vulnerability and humility, acknowledging that everyone has something to contribute, and we also have something to contribute to others. This simplifies connecting with others without pretenses or masks. Relationships become more natural and genuine, as this method involves connecting with others based on one’s own personality without changing or pretending to be someone else.

The second goal of the Alpha-Beta-Gamma method is to increase awareness of the potential advantages and limitations present among people with similar profiles. When individuals with similar profiles collaborate, their relationship can progress smoothly due to shared commonalities. However, there may be a reduced level of complementarity, potentially resulting in a lack of certain dimensions. For instance, two Alphas working on a project may have strong understanding in the domains of logic and action but may struggle with addressing emotional aspects. The Alpha-Beta-Gamma method highlights both the shared characteristics and the gaps in relationships between individuals with similar profiles (see table 4), encouraging the pursuit of complementarity from third parties or an increased focus on the missing dimension to address its deficiencies.

Advantages and disadvantages of the method

When compared to other models, the Alpha-Beta-Gamma method offers simplicity and ease in both diagnosis and application. Its intuitive and practical design makes it particularly suitable for use in everyday relationships, especially those involving frequent interactions. However, it also presents certain disadvantages. Each personality model discussed earlier in this article—MBTI, DISC, Enneagram, or 16PF—possesses unique advantages and disadvantages. Understanding both aspects for each model is crucial to selecting the most appropriate method for specific situations and optimizing its application once chosen. In the case of the Alpha-Beta-Gamma method, its advantages and disadvantages can be categorized into four distinct groups:

• Forced Choice: The method, as designed, requires a forced choice of two dimensions between Head, Heart, and / or Hands, and does not allow combining all three simultaneously. In cases where people could be characterized in all three dimensions, forced choice facilitates reflection but may provide limited information. In turn, in situations where a person’s personality is mainly defined by a single dimension (Head, Heart, or Hands), the forced choice of two dimensions could result in a self-diagnosis or diagnosis of others that does not reflect reality well.

• Metaphorical Language: Head, Heart, and Hands represent common concepts that facilitate self-diagnosis and the assessment of others. These metaphors act as “universal languages,” aiding consistent application across different cultures, countries, and education levels. For instance, test-retest trials have shown high reliability values comparable to those in other personality diagnostics. However, a potential drawback is the variability in individuals’ interpretations of these three symbols. This method works effectively when there is a shared understanding of the dimensions represented by Head, Heart, and Hands. It may be more challenging to implement in contexts where interpretations of each dimension vary significantly, such as in multidisciplinary teams with diverse cultural backgrounds.
• Reduced Number of Personality Profiles: This model has fewer categories compared to others like DISC (4), Big Five (5), Enneagram (9), or MBTI (16). The advantage is that, with only three profiles, diagnosis is simpler and it is easier to find common ground and contributions between different people. However, this also means a more generic diagnosis that does not include important characteristics like introversion / extroversion, present in other approaches.
• Ambiguity: The method relies on subjective observations from instructions such as “choose the dimension with which you feel the greatest affinity” and “the side with which you feel most identified.” Although these instructions generally provide sufficient guidance to achieve high reliability values, there can be some ambiguity in their interpretation. This may cause uncertainty for individuals unfamiliar with the model. Therefore, it is important to correctly follow the three phases of the method—understanding, exploration, and positioning—in order to obtain a reliable diagnosis.

These disadvantages make the Alpha-Beta-Gamma model probably less suitable than other methods for hiring personnel, assigning tasks according to personality profiles, or deep self-knowledge. However, its advantages make it an excellent option to boost self-confidence, develop interpersonal relationships, and create trust and cooperation dynamics in teams.

Conclusions and future research

In comparison to other personality diagnostic models, such as MBTI and DISC, which have histories spanning over 50 and 100 years respectively, our method is in its early stages of development and implementation. Future research will enable further refinement of the method, addressing existing limitations and expanding its capabilities. Areas for development include reducing ambiguity, creating questionnaires, and designing more effective guidelines for both self-diagnosis and diagnosis of others.

To date, and based on our experience, we can affirm that Alpha-Beta-Gamma is a personality diagnostic tool that helps build self-confidence and generate relationships based on trust and complementarity. It facilitates the desire to contribute to others from our strengths, and encourages seeking the contribution of others in areas where we have fewer skills. It promotes more authentic and natural relationships and, when applied to large teams or entire organizations, it becomes a common language that creates meaningful connections between people and supports high-performance cultures.

Acknowledgements: The author is very grateful to John Almandoz, Miquel Bastons, Pablo Cardona, Joan De Dou, María Fernández, Mayte Márquez and Alex Montaner for their comments on earlier drafts of this work.

About the Author

Carlos Rey is the Director of DPMC Foundation and the Chair in Management by Missions and Corporate Governance at Universitat Internacional de Catalunya. He is co-author of Management by Missions, Purpose-Driven Organizations: management ideas for a better world and other books and articles in leading scientific journals like Long Range Planning and Journal of Business Ethics.

The post Alpha-Beta-Gamma: A New Method for Diagnosing Personality and Enhancing Successful Relationships appeared first on The European Business Review.

By Dr. Claudio Antonini and Dr. Kamil Mizgier

When it comes to building models for the purpose of forecasting, system designers are naturally concerned that their models should be accurate. There is, however, another system characteristic that is of equal, if not greater, importance—its resilience.

In discussions about forecasting, it might serve well to remember its mother ship, the field of control theory. In this field, the objective is to control a system, sometimes called a “plant,” which might be, for example, a robotic arm, a submarine depth system, or the telescope camera of an interplanetary probe. To control these systems, actions must be implemented and, conceptually, they can be grouped into two processes that work in unison: one process that commands the plant, and another that estimates the variables on which the control is based. Let us consider an airplane. If the objective is to maintain course at a certain speed and altitude, the control part would be exercised by the combined actions of a turbine and a few control surfaces (ailerons, rudder), and the variables to be estimated will be the airspeed, attitude, and altitude, among others. In an economic system, the commands may be taxation, interest rates, or import restrictions, and the estimates may be the level of employment, the rate of inflation rate, or the currency exchange rate.

Forecasters today apply techniques almost exclusively in the time domain.

Whatever the specific variables controlled or estimated, overall, the fundamental and critical feature that allows a system to follow commands—to be controlled—is feedback. This mode of working, when feedback is implemented, is called “closed-loop.” Conversely, without feedback, the system would be labeled “open-loop.” Summarizing—no feedback, no control.

Compared to open-loop systems, feedback helps in (a) reducing the effect of modeling error and external disturbances, (b) changing, if necessary, the whole system stability, and (c) improving accuracy, that is, the “distance” to a desired set point. In the case of an airplane, if feedback is broken for some reason, the airplane would not be able to use the estimated (also called, forecasted) variables and would not be able to be controlled. Effectively, the airplane would be unable to maintain its required speed and altitude. The nightmare of a control engineer is an open-loop, uncontrolled system.

The arrangement of dividing control into two processes, control itself and estimation (also known as “filtering” or “forecasting”, depending on the author and disciplines), is well illustrated in a seminal book, Time Series Analysis: Forecasting and Control by George Box and Gwilym Jenkins¹. A testament to the importance of the book is that it has seen five editions since its first, in 1970. In this work, Box and Jenkins consider time- and frequency-domain techniques to analyze systems described by their time series, stressing time and again that the most important characteristic of a control system is its stability. However, nowadays, Box and Jenkins is rarely, if ever, quoted in forecasting literature. Forecasters are focused on other performance parameters of the system and may not be aware of the possibility of controlling it to get even better performance.

Most likely, practitioners ignore feedback due to their restricted focus, not paying attention to topics that Box and Jenkins discussed over various editions of their book. Forecasters today apply techniques almost exclusively in the time domain (except for some work with FFTs), do not consider transfer functions, have not heard of poles or zeros, and do not have ways of measuring the system’s stability. Effectively, forecasting is working in an open-loop architecture and, for that reason, practitioners are so concerned with “accuracy,” something that, in a closed-loop system, is of secondary concern when compared to the primary importance in that field, stability.

Several studies have been published that aim to model closed-loop systems, particularly in areas such as economics² and supply chain management³. We illustrate this concept by running a small program to simulate supply and demand for a hypothetical demand-planning exercise. In this model, we simulate the output (or quantity produced) based on demand and observe how closing the feedback loop affects the accuracy of our predictions. In the first model run, the simulation assumes that demand grows linearly (figure 1). In the second run, we enhance the model by introducing randomness to demand (figure 2). The no-feedback model simply uses the demand from the previous two samples to predict how it will grow in the next sample. The formula output_no_feedback[t]=output_no_feedback [t-1]+(demand[t-1]-demand[t-2]) represents a very simple linear demand forecasting model.

In comparison, the feedback model adjusts predictions by applying a correction factor based on how far the actual output (output_with_feedback[t-1]) deviated from the demand in the previous sample (demand[t-1]), effectively closing the loop.  To state this as a formula, output_with_feedback[t]=output_with_feedback[t-1]+feedback_factor*(output_with_feedback[t-1]-demand[t-1])

The results of the simulations with feedback and without it are shown in figures 1 (demand grows linearly) and 2 (random demand).

In both cases, we see a solid improvement in terms of accuracy (getting closer to the demand) even when that was not a design objective.

Social systems are more difficult to model than physical systems, which follow well-known laws.

The large improvement in accuracy is attributed to using a new structure for minimizing the error. This is a profound difference with articles that analyze alternative methods to improve accuracy where different methods for forecasting are employed but always keeping the same open-loop structure. In this case, we are closing the loop, departing significantly from minimal changes in algorithms that keep the same open-loop structure.

But … why do forecasters ignore feedback?

Most probably, forecasting practitioners deal with types of systems in which they cannot model the feedback process and, thus, “what one cannot model one cannot control.” These are possible reasons:

• Social systems are more difficult to model than physical systems, which follow well-known laws
• Events in social systems are single-case experiments; rarely can they be repeated
• Even if they were successfully modeled, humans would try to exploit loopholes and react in ways that were not considered during the modeling phase (the Lucas principle in economics)
• There may be a belief that forecasting demand (although useful in itself) is a substitute (in terms of performance) to having a model for the feedback process

In addition to the fuzziness of the social systems that forecasters must deal with, in social environments the time scales are orders of magnitude slower than those in physical systems. In the case of an airplane’s autopilot, typically, the signals that are used to estimate aileron or rudder positions and turbine parameters are sampled every few milliseconds. Thus, humans may not be able to control the airplane in real time (particularly if they are naturally unstable airframes) and the control has to be automated. On the other hand, forecasting sales in a supermarket may be done with monthly data or, in macroeconomic systems, with quarterly data. The fact that data in these cases is available so infrequently may give humans the idea that they have ample time to make decisions and affect the outcomes of their system (for example, sales, output in a GDP, or unemployment) in a desired direction. To that effect, they indeed take action, but without the rigor of a control engineer, who makes a significant effort in modeling the system to be controlled and simulating various techniques to get the desired outcomes.

Whether by choice (relying on modeling demand and ignoring the modeling of the feedback decision process), necessity (social systems difficult to model or data available too infrequently), or lack of familiarity with modeling techniques (relying on crude and simple regressions instead of more dynamic approaches), and confronted with systems that behave under their own open-loop dynamics, forecasters have no other possibility than measuring how far they are from an intended target. That is, they have no other possibility than to keep developing and using “accuracy” indicators, much as a man walking down the middle of the street decides that he’s doing well if he hits the curb in 3 minutes of walking blind, rather than in 1 minute.

Comparing feedback and no-feedback prediction models, it becomes evident that human-controlled systems often fail to achieve optimal performance as compared to airplanes and other engineered systems. Systems overwhelmed by an exploding amount of information and indicators can exacerbate problems rather than resolve them. Such control relies heavily on noisy, incomplete, or misleading data, which can result in decisions that reduce performance.

The key takeaway is that resilience should be a design concern in the event of performance degradation. Systems that prioritize adaptability and robustness—while acknowledging the limits of prediction—are better equipped to deal with uncertainty and mitigate risks. For example, flood prediction systems in Europe failed numerous times in 2024, highlighting the dangers of relying too heavily on inaccurate weather forecasts without building sufficient resilience into the system. Needless to say, in cases where feedback modeling could be implemented, ignoring it would be a risky—if not negligent—strategy.

About the Authors

Dr. Claudio Antonini, MIT nuclear safety engineer, after working in the design of GNC systems for missiles and drones, has applied that numerical experience in the field of finance for the last 25 years. Working at UBS, he developed the largest global implementation of a genetic algorithm for banking, and has continued to apply data mining, machine learning, and artificial intelligence algorithms for risk management, in consultancies (Deloitte, AlixPartners) and the Bank of New York Mellon. He publishes consistently on forecasting topics.

Dr. Kamil Mizgier brings his extensive practical experience and deep knowledge to explore challenges in strategic risk management. By leveraging his 15 years of expertise from key roles, including Global Supplier Relationship and Risk Management Leader at Dow and risk modeling leadership positions at BNY Mellon and UBS, he delves into the latest trends, tools, and techniques in risk management, offering invaluable perspectives that bridge academic rigor and practical application.

References

1. Box, G. et al. 2015. Time Series Analysis: Forecasting and Control 5^th Edition, John Wiley and Sons Inc., Hoboken, New Jersey.

2. Carranza, R. G. 2016. “The Closed Loop Economy.” International Journal of Design & Nature and Ecodynamics, 11(4), pp. 600-9.

3. MahmoumGonbadi, A. et al. 2021. “Closed-loop supply chain design for the transition towards a circular economy: A systematic literature review of methods, applications and current gaps.” Journal of Cleaner Production, 323 : 129101.

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By Georgie Fienberg and Adrian Furnham

If you want the best from your car, it helps to have some idea of how it all works. But do you know what’s going on under the bonnet of your team? What’s that weird rattling at the back? Why have we slowed down? And where’s that smoke coming from? Here’s an owner’s guide.

Most of us work in teams; we have to. The psychology of teamwork has been extensively studied. Successful teams, particularly and inevitably the board (the grown-ups), improve all business outcomes – morale, revenue and performance. Working in a happy, safe, and healthy team is a primary driver of employee engagement at all levels.

Equally, unhappy, inward-looking, back-stabbing, and politically devious teams cause mayhem. We know that boards often experience problems that render them dangerously ineffective. This includes bloated membership, naked ambition, conspiracies of silence, an ambiguity of roles and, despite this, resisting help.

But teamwork does not happen by chance. Teams are made of individuals with quirks and passions, blind spots and insights, foibles and strengths. We study the three cornerstones of individuals: their ability, (bright- and dark-side) personality, and motivation. They “come to the party” with complex needs, hopes, and contributions and set up complex dynamics, just like families. Some have an insight into their dynamics but most are focused on other things. Many fail and need help.

Team types

Over the years, we have observed and worked with teams in many organisations. Some come to us for help; others have been referred. Our research has led us to come up with a taxonomy of teams. This has always been based on a mixture of individual difference data from robust psychometric tests, as well as observation and … data. We believe our list is both comprehensive and insightful. What have tried to do is first describe the behaviours they display and what they think they’re great at. We have been particularly interested in the reality of how they actually operate and, critically, the consequences of their habits. Most important of all, we have noted around three actionable recommendations for each to improve team functioning.

1. The PLU (people like us) team

Behaviour:

They stroll into the meeting room mid-laugh, reminiscing about last night’s drinks or that one legendary offsite way back that no one else was at. Their inside jokes and shared history are thicker than concrete. These are the “People Like Us” – and, if you’re not “us”, good luck getting a word in.

There’s a lot of nodding, a lot of “great point”, and an alarming amount of back-slapping (sometimes metaphorical, sometimes physical). Their loyalty to each other is admirable – until you realise that it extends to never meaningfully challenging each other, ever.

Their energy is warm, their connection is genuine, but they use language, humour, and metaphors that unwittingly exclude people – private jokes, shared references, even an unwritten set of rules about how things get done. Outsiders don’t get it, but that’s fine, because PLUs don’t really notice outsiders.

What they think they’re great at:

“We have an amazing culture – there’s so much trust and support in this team.”

Reality:

The trust is real, but it’s selective. Challenge is rare, because deep-rooted patterns of friendship complicate the candour in conversation. Diversity of thought is limited, because anyone who “doesn’t fit” either stays silent or exits. The team reinforces its own perspective, making it an echo chamber rather than a high-performing unit.

Consequences:

• Strong “groupthink”, with ideas rarely sc
• Exclusion of outsiders, severely limiting diversity of thought and decision quality.
• Lack of honest feedback, leading to strategic blind spots.

How to Fix It:

• Introduce structured debate. Assign a “devil’s advocate” in discussions to challenge consensus thinking.
• Rotate team dynamics. Switch up project groups to mix people who don’t normally work together.
• Seek external / outsider input. Bring in different perspectives to challenge and test ideas.

2. The big-character team

Behaviour:

This team moves fast, because their leader moves fast, and often loudly. Every idea is met with enthusiasm, momentum is non-negotiable, and meetings feel more like TED Talks, except that no one else is allowed on stage. The leader speaks and heads nod, perhaps too enthusiastically. They may even clap. The introverts are left staring at their notepads, waiting for this to be over.

The leader finishes making their point. “Thoughts?” they ask expectantly. Silence. No one actually disagrees. Or at least, no one is willing to be the one who does. The Big-Character Team follows momentum, not scrutiny. The leader is magnetic, articulate, and convincing. The result is that ideas get nodded through without being tested.

What they think they’re great at:

“We have a strong, visionary leader who keeps us moving forward.”

Reality:

There’s movement, but not necessarily progress. The “spectators” in the team don’t contribute, and dissenting voices are drowned out. The leader assumes agreement but, in reality, many people are just nodding along.

Consequences:

• The loudest voices dominate decision-making.
• Over time, rather than challenge or contribute, team members disengage, and valuable perspectives are lost.
• Ideas aren’t stress-tested, leading to poor execution.

How to Fix It:

• Reverse the hierarchy. The Leader speaks last to prevent premature alignment.
• Build psychological safety. Explicitly ask
  for opposing views and acknowledge
  dissent positively.
• Balance airtime. Introduce a “no repeat contributions” rule to force new voices into the conversation.

3. The false-harmony team

Behaviour:

This team is suspiciously polite. Meetings run smoothly, decisions come quickly, and consensus is reached without friction. But the real conversations happen later, in side chats, carefully worded emails, and coffee break venting sessions.

On the surface, everything looks seamless, but tension simmers beneath. People nod along, not out of true agreement, but because challenging ideas feels risky. They have opinions, but they’ve learned to share them elsewhere, where it’s safer.

The fear of being seen as negative or “not a team player” keeps people from speaking up when it matters. Concerns get whispered in corridors, frustrations surface in vague Slack messages, and disagreements turn into passive resistance rather than open discussion.

The fear of being seen as negative or “not a team player” keeps people from speaking up when it matters. Concerns get whispered in corridors, frustrations surface in vague Slack messages, and disagreements turn into passive resistance rather than open discussion.

No one is outright lying, but no one is being fully honest either. It’s an organisation-wide game of pretend consensus, where silence is mistaken for alignment, and discomfort replaces productive debate.

What they think they’re great at:

“We’re all on the same page. We don’t waste time on unnecessary conflict.”

Reality:

Disagreement hasn’t disappeared; it’s just been relocated. People conform in meetings but save their concerns for corridor conversations or passive-aggressive email threads. This team mistakes silence for alignment and, as a result, they miss out on the healthy tension that actually improves decision-making.

Consequences:

• Superficial alignment, with issues bubbling under the surface.
• A reluctance to challenge weak ideas, leading to poor decision-making.
• Passive resistance; people agree publicly but don’t execute properly.

How to Fix It:

• Introduce accountability. Before a decision is finalised, each person must write down their view and classify it as “green” (fully aligned), “amber” (some concerns), or “red” (not aligned). The leader sets a minimum number of greens before proceeding. Writing it down forces people to reconsider what they’re truly prepared to back.
• Encourage enquiry over direct challenge. Instead of outright disagreement, prompt discussion with open questions like, “That makes sense from an operational perspective. How would it play out for our customers?”
• Require pre-submitted input. Have team members submit concerns in advance, ensuring that issues are surfaced before discussions, not after.

4. The bright-sparks team

Behaviour:

If ideas were currency, this team would be billionaires. They don’t just brainstorm; they erupt with creativity, throwing out new concepts, angles, and innovations at breakneck speed. Meetings are a whirlwind of inspiration, sticky notes pile up, whiteboards overflow, and the air crackles with excitement.

But, while they excel at the art of conception, they flounder in execution. They make ephemeral progress on multiple fronts, but nothing ever truly lands. There’s always a new idea, a better approach, or an even more exciting opportunity just around the corner. And so, the cycle repeats.

They are always creating, but they aren’t prioritising. And creativity without prioritisation, pragmatism, and follow-through? That’s just expensive procrastination.

What they think they’re great at:

“We’re a highly creative, innovative team.”

Reality:

They are creative. But in their world, the spark is more exciting than the fire. The thrill of ideation trumps the discipline of delivery. And, while they may pride themselves on being idea generators, without execution, all that brilliance is wasted potential.

Consequences:

• High energy but little tangible progres
• Chaos and burnout in the layers below; good people leave.
• Lack of impact because nothing is executed properly.

How to Fix It:

• Prioritise ruthlessly. Not every idea deserves time and resources.
• Set execution deadlines. Hold people accountable for completing what they start. If there’s no deadline, it’s not real.
• Appoint a “closer”. Someone needs to own delivery. This person ensures that at least some of the brilliance makes it out into the real world.

5. The rapid-responder team

Behaviour:

This team don’t just react; they overreact. They’re always in motion, “always on”. Emails are answered in milliseconds, Slack messages get immediate replies, and meetings are more like triage units than spaces for meaningful discussion. The pace is relentless. They take pride in their ability to handle anything but the truth is that they mistake constant activity for actual productivity.

They thrive in crisis mode and, in fact, they unconsciously seek it out. If things are too calm, they get twitchy. Stillness feels like inefficiency. They measure their value in how fast they solve problems, not whether those problems should exist in the first place.

There’s little patience for reflection, big-picture thinking, or long-term strategy. They fight fires all day but never build fire prevention systems.

What they think they’re great at:

“We are the most efficient team in the company. If there’s a problem, we’ll fix it – fast.”

Reality:

They get things done, but often the same things, over and over again. There’s no space for strategic thinking, because they’re so busy reacting to urgent (often trivial) issues; long-term projects suffer.

Consequences:

• Problems are solved on the surface, but deeper issues remain unaddressed, creating an endless cycle of reactivity.
• Short-term fixes dominate. Success is measured by speed, not impact—leaving no space to evaluate whether the right problems are being solved at all.
• The rest of the organisation learns to rely on them as a rapid-response unit instead of taking ownership of their own responsibilities.

How to Fix It:

• Create a pause mechanism. Ask, “Is this urgent or just loud?”, “Are we solving the same problem again?”
• Introduce reflection time. Set aside time to identify patterns, think strategically, and improve processes.
• Instead of always being the first responder, the team should coach others to solve their own problems.

6. The overthinkers

Behaviour:

This team is addicted to complexity. Every decision is a masterpiece of analysis, dissected from every conceivable angle, with every risk painstakingly documented. Nothing moves until every possible scenario has been explored, stress-tested, and debated into submission.

Their meetings are exercises in intellectual endurance. The phrase “Let’s take a step back” is used 10 times per discussion. PowerPoints swell to 60 slides, often with more footnotes than main content. Decisions aren’t made; they are monumental events requiring weeks of prereading, stakeholder alignment, and a multi-step approval process.

Questions are answered with more questions. There is always another variable to assess, another risk to mitigate, another layer of nuance to peel back.

The result? Progress grinds to a halt. A simple “yes or no” becomes a research project. While other teams are executing, this team is still debating whether the decision should even be made at all.

What they think they’re great at:

“We are rigorous, data-driven, and highly analytical.”

Reality:

They believe that their meticulous approach ensures bulletproof decisions but, in practice, it just slows everything down. While they scrutinise every detail, braver (and sometimes less competent) teams are already executing. In their pursuit of perfection, they overlook the cost of delay.

Meanwhile, the rest of the organisation is watching – and waiting. Stakeholders grow frustrated. Colleagues stop bringing them into conversations because they know it will lead to delays. Over time, the team becomes known less for its analytical rigour and more for its inability to get things done.

Consequences:

• Missed opportunities due to slow decision-making.
• Team fatigue from excessive analysis.
• Frustration from stakeholders waiting for action.

How to Fix It:

• Impose deadlines. Force decisions at key moments.
• Set “good enough” thresholds. Define what level of certainty is actually required.
• Appoint a decision driver. Make it someone’s job to move things forward.

7. The martyrs

Behaviour:

They are hardworking, dedicated, and visibly exhausted. Emails at 11 pm – standard; working through lunch – of course; logging in on holiday – only if they take a holiday, which they won’t, because who else would hold the place together? Classic maladaptive workaholism.

The Martyrs pride themselves on their commitment – but it’s not just about dedication. There’s an underlying resentment brewing beneath the surface.

The Martyrs pride themselves on their commitment – but it’s not just about dedication. There’s an underlying resentment brewing beneath the surface. If you leave on time, they notice. If you take a proper lunch break, they see you. And if you dare set a boundary? Expect a pointed “must be nice” comment at some stage.

They say they want better work-life balance. They say they want efficiency. But, deep down, they believe that suffering is a sign of commitment, and anyone who isn’t suffering is somehow letting the side down.

What they think they’re great at:

“We are the backbone of this company. We do whatever it takes.”

Reality:

They are hardworking – too hardworking. But at what cost? Productivity, burnout, passive-aggressive Slack messages?

Their exhaustion doesn’t actually make them more effective; just more resentful. And, ironically, their non-stop work often results in less strategic thinking, more mistakes, and an increasing sense of “what is even the point?”

Consequences:

• Chronic burnout and stress, leading to high turnover.
• A toxic culture of guilt around setting boundaries.
• Short-term wins at the expense of long-term sustainability.

How to Fix It:

• Kill the “busyness badge”. Stop celebrating overwork as a sign of dedication.
• Enforce real boundaries. Leaders need to model leaving on time, taking breaks, and not responding at 11 pm.
• Measure output, not hours. Reward impact, not just effort.

8. The mavericks (aka: the sales team)

Behaviour:

If this team had a LinkedIn bio, it would be: “Breaking records. Breaking rules. Breaking 100 on the golf course.” If they had a WhatsApp group, it would be filled with unread messages and the occasional GIF of a wolf pack.

They are dealmakers, rainmakers, and headline-makers. They win big, because they move fast, take risks, and refuse to be constrained by bureaucracy. Process is for other people. Governance is a suggestion. HR policies? Cute.

They operate on a heady mix of instinct, charisma, and sheer audacity. They don’t just sell an idea, they sell the belief that it will work, often before the details are figured out. They can out-negotiate, out-network, and out-manoeuvre almost anyone, and they thrive in high-pressure, high-stakes environments.

But competition isn’t just external, it’s internal, too. Every win is celebrated but also measured against their peers. Collaboration happens only if there’s an edge to be gained. If you slow them down, they’ll bulldoze past you. If you try to rein them in, they’ll argue their way around the rules. Banter is their love language, and they can charm, hustle, or bluff their way into (or out of) anything.

What they think they’re great at:

“We bring in the business. Without us, there’s no company.”

Reality:

They do bring in business. But their relentless win-at-all-costs approach leaves chaos in its wake. Deals get closed, but the fine print gets overlooked. Targets get hit, but at the cost of client relationships, internal trust and, occasionally, their own integrity.

They resent rules, but the truth is that some of those rules exist to protect them – from lawsuits, reputational damage and, in extreme cases, each other.

Consequences:

• High turnover – burnout, stress, or getting poached by a competitor.
• Risk exposure – regulatory issues, angry clients, “misunderstandings” in contracts.
• Toxic internal competition – every win is someone else’s loss.

How to Fix It:

• Create structure without killing autonomy. Give them flexibility, but with clear guardrails.
• Align incentives with long-term impact. Reward sustainable growth, not just quick wins.
• Manage the internal competition. Channel their drive into collective wins, not just individual battles.

9. The diversity mirage

Behaviour:

On paper, this team is a poster child for diversity. Different backgrounds, different experiences, different perspectives – it looks great in a company brochure. They should be the most innovative, forward-thinking, high-performing team around.

But in reality? It’s not working. Meetings are a minefield. Communication styles clash. Decisions take forever, because no one quite knows how to navigate the differences. Some people dominate, while others retreat.

There’s diversity, but no inclusion. Instead of harnessing their differences, they’re tripping over them. Some feel unheard. Others feel misunderstood. And a few are just quiet-quitting from the whole experience.

What they think they’re great at:

“We are a diverse, progressive team with a wide range of perspectives.”

Reality:

They are diverse, but diversity without inclusion is just optics. The team is fragmented, misunderstood, and struggling to work together effectively.

Instead of leveraging their differences, they’re either avoiding them altogether or fighting over them constantly.

Consequences:

• Great ideas never surface because the loudest voices win.
• Some members feel excluded despite the appearance of diversity.
• Tension, misalignment, and unintentional silos.

How to Fix It:

• Teach the team how to work together, not just exist together. Facilitate real conversations about communication styles and decision-making preferences.
• Equalise airtime. Don’t let dominant voices control discussions; create deliberate opportunities for everyone to contribute.
• Move beyond tokenism. Ensure that diversity translates into meaningful inclusion, where differences are actually valued (not just tolerated).

10. The rotten core

Behaviour:

This team should be unstoppable. They’re bright, good at what they do, respect each other, and challenge ideas without ego. They’ve cracked the code on high performance.

Except there’s a problem. One person – just one – is subtly poisoning the well.

Meet The Rotten Core, who is not overtly aggressive or blatantly insubordinate. That would be too easy to spot. Instead, they operate in the shadows. They roll their eyes in meetings. They make “just saying” comments that undermine decisions. They plant tiny seeds of doubt – about leadership, about a colleague’s competence, about whether this whole thing is even going anywhere.

They excel at plausible deniability. They never outright criticise, just imply. They’re just “raising concerns”. They’re just “playing devil’s advocate”. They’re just “saying what everyone’s thinking”.

And the worst part? They’re not entirely wrong. Every high-performing team has cracks – natural tensions, frustrations, moments of uncertainty. But The Rotten Core amplifies these, distorts them, and makes them fester. The team, once cohesive and driven, starts second-guessing itself. Trust erodes. Motivation dips. And somehow, no one can quite pinpoint why.

What they think they’re great at:

“I just tell it like it is. I’m not afraid to speakthe truth.”

Reality:

They mistake cynicism for insight. Their “truth-telling” is actually selective, designed to stir discontent without offering solutions.

Consequences:

The rot spreads; cynicism is contagious. Once one person starts rolling their eyes or casting doubt, others pick up the same behaviours. Negativity becomes the norm.

Decision paralysis; people hesitate to commit, because they’re worried they’re missing something or, worse, about to be criticised for it.

Instead of focusing on performance, leaders waste time managing politics and emotional fallouts. Energy that should go into growth and problem-solving is spent firefighting internal trust issues.

How to Fix It:

• Make negativity accountable. Ask them, “What solution do you suggest?” every time they raise an issue. If they have none, they’re just stirring the pot.
• Call out the pattern. Not in an aggressive way, but in a “Hey, I’ve noticed a lot of concerns being raised without constructive next steps. What’s going on?” way.
• Reinforce the culture. Remind the team what makes them great and refuse to let one person’s cynicism erode that. If necessary, have a direct, clear conversation about the impact of their behaviour.

11. The Institutional Guardians (AKA: “Tenure is Everything”)

Behaviour:

If you’ve only been here five years, you’re still the new kid. This team runs on history, hierarchy, and a deep respect for “the way things have always been done”.

There is a right way and a wrong way to do things, and, conveniently, the right way just so happens to be exactly how they’ve always done it. New ideas are met with polite scepticism. Fresh perspectives are not needed, thanks. Change only if it was first proposed in 1998.

This team takes immense pride in their legacy; they’ve built something enduring, and they’re not about to let some bright-eyed, MBA-waving newbie come in and ruin it with their modern nonsense. New hires get the message that they can earn their place over a decade or two.

What they think they’re great at:

“We have deep expertise and institutional knowledge. We know what works.”

Reality:

They do have valuable knowledge and experience. But legacy isn’t a strategy. They are so busy protecting the past that they’re stifling the future.

Instead of evolving, they’re preserving. And, instead of leading the industry, they’re watching it move past them, one unapproved change at a time.

Consequences:

• Stagnation – new ideas struggle to take root, and innovation is stifled.
• High turnover of younger talent who feel ignored and undervalued.
• The team feels stable but, in reality, it’s slowly becoming irrelevant.

How to Fix It:

• Separate “valuable legacy” from “outdated tradition”. Audit why things are done a certain way and whether it still makes sense.
• Create structured ways for new ideas to be tested. Pilot fresh approaches without threatening existing systems.
• Mentorship, not gatekeeping. Help long-tenured employees transfer their knowledge instead of just protecting it.

12. The Hub-and-Spoke Crew (AKA: A Group, Not a Team)

Behaviour:

This isn’t really a team. It’s a collection of individuals who all report to the same leader but don’t actually work together. The leader is the hub, and each team member is a spoke – connected to the centre but not to each other.

Meetings feel like a series of 1:1 updates, where each person talks to the leader and no one else says a word. If someone asks for input from another team member, you can physically feel the awkwardness in the room.

They don’t even know what each other does. If someone left tomorrow, half the team wouldn’t even notice, because their job has zero overlap with anyone else.

Collaboration, they believe, is not their problem; alignment is unnecessary; cross-functional projects are irrelevant.

What they think they’re great at:

“We are efficient and focused, and everyone knows their role.”

Reality:

They might be individually productive, but they’re not actually a team. They miss out on: shared learning (because no one talks to each other); efficiency (because information isn’t flowing between them); better solutions (because no one is building on anyone else’s work).

The real irony? The leader is overloaded, because every single issue has to be routed through them.

Consequences:

• The leader becomes the single point of failure, overloaded with decisions, while the team remains disconnected, operating in isolated silos rather than as a cohesive unit.
• Because there’s little collaboration or shared accountability, work gets duplicated, inefficiencies creep in, and valuable insights that could strengthen the team’s output are lost.
• Without a real sense of belonging or interdependence, team members disengage from the bigger picture, focusing only on their own tasks while innovation, problem-solving, and collective progress suffer.

How to Fix It:

• Make meetings about the team, not just the leader. Introduce peer-to-peer discussions instead of just leader check-ins.
• Force some strategic overlap. Design projects where people actually have to work together.
• Get clear on shared purpose. Define why this group exists as a team, not just as direct reports.

Conclusion: the patterns you don’t see

Every team thinks they’re unique. Indeed they are – different industries, different people, different challenges. But, after years of working with teams across the world, we’ve learned that they are far more predictable than they think.

Teams go wrong, and with various serious consequences. They focus on where they want to be, without first getting an honest, objective view of where they are now.

The most important job of a leader is to build a high-performing team. It’s not an HR function or a side project. It is the job. Leaders try to drive performance without first understanding the behaviours, mindsets, and cultural undercurrents that are shaping their team’s trajectory.

We use the Hogan Assessment, not just to describe a team, but to predict how they will behave and perform if nothing changes. It reveals the hidden patterns at play, the unconscious habits shaping decisions, and the risks that could derail progress. We might triangulate that data with broader reviews – team diagnostics, stakeholder feedback, and real-world observations – that make up a very clear picture.

Forewarned is forearmed. Once a leader understands their team – not just their intentions – they face a choice. If they don’t manage it with intention, their team’s effectiveness will be left to chance.

Team-building models, roadmaps, charters and various tools can all help a leader to harness the best of what they have to meet their goals. But, it starts with self-awareness (what do you have?), intention (how will you make the best of it?), courage (to do the right thing, not the easy thing), and discipline (to keep doing it, consistently).

Because great teams don’t just happen. They need to be built, nurtured, and developed – deliberately, thoughtfully, and with full awareness of where they’re starting from.

If you understand the predictability of your team and choose not to act, then performance becomes accidental. But if you take charge, if you own the responsibility of building a high-performing team, then your team’s success is no longer a gamble. It’s a strategy. And that is leadership defined succinctly as the “ability to form, maintain and motivate a team, more adapted and successful than your competitors”. Amen.

About the Authors

Georgie Fienberg is a business speaker and leadership adviser. She works with global clients ranging from FTSE 100 C-suites to the British Parliament, specialising in applying behavioural science to building high-performing teams and cultures.

Adrian Furnham is a business speaker and consultant. He is Professor at Birkbeck Business School and the Norwegian Business School. He has written 100 books translated into 40 languages.

References

• Allen, N.J. & West, M.A. (2017). “Selection for Teams”, The Blackwell Handbook of Personnel Selection. Oxford: (pp. 476-94).

• Belbin, R.M. (2012). Team Roles at Work. Abingdon: Routledge.

• Furnham, A. (2018). “The Dynamics of the Boardroom: Typical Problems and How to Fix Them”, The European Business Review, Oct-Nov, 51-5.

• Johnson, S.S.(2021). “The Science of Teamwork”, American Journal of Health Promotion, 35(5):730-32. doi:10.1177/08901171211007955a

• Kets de Vries, M. (2011). The Hedgehog Effect. London: Wiley

• McCann, D., & Margerison, C. (1985). “Team Management Profiles: Their use in management development”, Journal of Management Development, 4(2), 34–47.

• Mathieu, J.E., Hollenbeck, J.R., Van Knippenberg, D.L., & Ilgen, D. (2017). “A century of work teams in the Journal of Applied Psychology”, Journal of Applied Psychology, 102(3), 452-67.

• Salas, E., Reyes, D.L., & McDaniel, S.H. (2018). “The science of teamwork: progress, reflections, and the road ahead”, American Psychologist, 73(4):593–600.

• van Dierendonck, D., & Groen, R. (2011). “Belbin revisited: A multitrait-multimethod investigation of a team role instrument”, European Journal of Work and Organizational Psychology, 20(3), 345-66.

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By Claire Snook

In 2025, AI-powered search is poised to become the foundation of how brands connect with their customers. Advances like ChatGPT, SearchGPT, as well as the strategic pivot from traditional search engines toward entity association, are rewriting the rules of brand visibility.   

You’re chatting with an AI assistant, asking it to recommend the best eco-friendly brands, and within seconds, it presents a tailored list of options. No endless scrolling, no guesswork – just immediate answers. This is our reality, and its ubiquity means that AI-powered search is completely reshaping how customers discover brands. 

Tools like ChatGPT, SearchGPT, and Google’s approach to entity association has revolutionised search, transforming it from a tool into an intelligent matchmaker. For brands now, the stakes couldn’t be higher. Visibility in this new AI-driven ecosystem isn’t about simply showing up – it’s about being chosen. The question is, how can brands ensure they’re on the list when AI makes its recommendations? 

This isn’t just about making search smarter; it’s about redefining how brands build authority and reputation and establish visibility when intelligent algorithms now drive consumer discovery. 

The shift away from traditional search 

Increasingly, users are bypassing traditional search engines to ask conversational AI tools for direct, personalised answers. Gartner predicts that by 2026, traditional search engine volumes will drop by 25%, with AI-powered systems like chatbots and virtual assistants taking centre stage. 

Yet, this doesn’t spell the end for all search engines. Bing, for example, is redefining itself through its deep integration with OpenAI technology, making itself a cornerstone of the AI-driven search revolution. Bing employs tools like IndexNow to signal real-time content updates, ensuring search results are always current and relevant. For brands, this shift highlights the need to adapt content strategies to align with Bing’s AI-first approach, ensuring they remain visible in GPT ecosystems. Ignoring this evolution risks leaving brands invisible to the growing number of users relying on these advanced systems. 

Generative Engine Optimisation (GEO) a new frontier 

Enter Generative Engine Optimisation (GEO), the strategy brands must master to thrive in an AI-first world. GEO isn’t about gaming algorithms to secure a spot in search rankings; it’s about shaping how generative AI systems synthesise and present information. 

Unlike traditional SEO, GEO focuses on the unique way AI interprets content. Generative systems don’t just catalogue pages; they weave together insights from multiple sources to provide clear, authoritative answers. For brands, this means creating content that not only meets traditional SEO standards but also aligns with how AI tools synthesise data. 

The key to GEO is having a deep understanding of user intent, thinking beyond keywords and backlinks and focusing instead on crafting narratives that align with user questions, values, and expectations. 

Understanding user intent in the age of AI 

User intent has always been central to search strategies, but AI takes it to a deeper level. The keywords relied on by traditional search engines often result in a scattershot of links that leave users piecing together their own answers. AI search, by contrast, interprets full, natural-language queries to deliver precise, context-rich responses. 

Imagine asking an AI assistant about sustainable travel options. Instead of simply listing websites, the AI might synthesise details about eco-conscious airlines, green hotels, and tips for reducing carbon footprints, all tailored to your preferences. For brands, this demands a shift. Content must not only answer questions but anticipate the nuances behind them. 

This requires a focus on clarity, relevance, and delivering content that adds real value to the conversation. When your content becomes the trusted source that AI platforms turn to, your brand naturally earns visibility and authority. 

Building a unified strategy for AI search success 

The days of siloed strategies for SEO, social media, and paid media are over. Success now hinges on crafting a cohesive digital presence that resonates across all channels. 

AI search systems evaluate not just individual pieces of content but the broader context of a brand’s digital footprint. From blog posts and product descriptions to social media activity and external links, every signal contributes to how your brand is represented in AI-generated results. 

For example, a brand focusing on sustainability must demonstrate this value across platforms: blog content that highlights green initiatives, collaborations with eco-conscious influencers on social media, and product descriptions that detail ethical sourcing. Brands should focus on creating a consistent and authentic narrative that AI systems can easily interpret. 

Technical excellence and continuous adaptation 

Behind every great AI strategy is a technically sound foundation. Generative AI systems, like traditional search engines, rely on structured and accessible content to deliver accurate results. This means optimising websites for mobile-friendliness, load speed, and natural language processing (NLP), ensuring that AI tools (and customers) can process your content without friction. 

Equally important is the need for continuous learning and adaptation. The algorithms powering AI systems are constantly evolving, and brands must stay ahead of these changes. Whether it’s analysing citation patterns in AI-generated responses or exploring new tools that align with generative search behaviours, brands must stay informed. 

Practical steps for brands 

1. Prioritise high-quality, relevant content aligned with E-E-A-T (Experience, Expertise, Authoritativeness, and Trustworthiness) principles. Use keyword and semantic research to address traditional and conversational search queries. 
2. Ensure websites meet the technical demands of SEO and GEO. This includes fast load speeds, mobile responsiveness, structured data, and natural language processing readiness. 
3. Tailor content strategies for Bing and GPT-powered ecosystems. 
4. Monitor how AI algorithms evolve and adjust content accordingly. 
5. Actively participate in community platforms and social discussions to enhance brand visibility and authority in AI search.

About the Author

Claire Snook is a digital comms manager at strategic communications agency, AMBITIOUS. With more than 20 years’ experience under her belt in media and PR, Claire brings together digital insights and traditional PR skills. She has worked with top global brands to local start-ups, and everything in between, for agencies and in-house.  

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By Doug Hall 

Transformational ideas require a leap of faith. They require you to break free of your “adultness” to allow your mind to run free and unconstrained. This article presents one of the most direct ways that I know to open your mind (and the minds of others) to thinking differently.   

I call this process Lawbreaker. It’s a method that we’ve used with dozens of our Eureka! Ranch clients searching for break-through ideas. We even used Lawbreaker ourselves to help develop a dream project of mine, creating and selling Customized Bourbon to consumers around the country. In the last section of this article, I include a case study explaining how we did it.  

Challenge Accepted Systems 

Lawbreaker involves attacking your challenge from the opposite of how you would normally think about it. It does this by overtly breaking the traditions, rules, policies, procedures, and beliefs that are the accepted ways of thinking or working.  

There are traditions within every work process, system, and activity in both your personal life and professional life. Most of these traditions were valuable when first developed. However, some of these methods have become fixed while the world around us—technologies, training, experiences—has changed.  

At their worst, these once-helpful systems have evolved into rigid bureaucratic barriers to change. The result is that they now generate more pain and waste than they enable. People spend an awful lot of time trying to improve things that should be destroyed. In many organizations, people haven’t rethought the design of systems for years. And as these systems become dysfunctional, organizations institutionalize that dysfunctionality. The main concept of Lawbreaker is to reinvent a system or product – not just patch or improve the existing one.  

I recognize that the idea of “blowing up” how you do your fall yard cleanup, your work process, or even the annual big fundraiser for your nonprofit can feel terrifying. Your logical mind tells you, “It’s not really broken enough to go through the pain of change.”  

I can’t decide for you what is really bad versus not bad enough to change. What I can say is that it’s at least worth doing a “thinking excursion” on what a reinvented system could offer. Just because you think about it doesn’t mean you have to pursue it.   

Simple Lawbreaker  

Lawbreaker begins by making lists of actions that you ALWAYS DO and NEVER DO when working on your problem area. For example, say your challenge is to find a way to make your morning team meetings at work more productive. Your list of things you ALWAYS DO might include:  

• We ALWAYS take 30 minutes each day for our meetings. 
• We ALWAYS hold meetings first thing in the morning. 

Next, take each of these and challenge them. Adopt a perspective that a requirement of your new idea is to now NEVER DO each of the things you listed as ALWAYS DO.  

• We now NEVER take 30 minutes – This could spark an idea like what if we were to split into two meetings a weekly meeting for an hour—focused on bigger issues—and a 15-minute meeting each day on the urgent issues. 
• We now NEVER hold them first thing in the morning – This could spark the idea of having the meeting at the end of the day—when issues are fresh in everyone’s head. It also allows for “incubation” of ideas and thoughts overnight so everyone can start fresh.

The flip side of ALWAYS DO is NEVER DO. Here we reverse the Lawbreaker. We make a list of things we NEVER Do with our team meeting.  

• We NEVER allow one person to “take over” the meeting. 
• We NEVER make the meetings optional—everyone must attend. 

Next, take each of these statements and challenge them. Adopt a point of view that your new idea for your team meetings is to ALWAYS do the thing that you listed.  

• We now ALWAYS allow one person to “take over” the meeting – This could spark the idea of having a different team member run the meeting each day. As part of this role, they are responsible for providing a 10-minute update on what they are working on personally and what they could use ideas and advice on.
• We now ALWAYS make the meetings optional—no one must attend – This could lead to the idea of having each person record a three-minute audio or video update at the end of each day on learnings, issues, and help that they need. Have each audio/video update posted to a digital platform so all can listen and post comments on. 

While not all the ideas will work out, the return on your investment of time is fantastic. the process just takes just a few minutes, and just one idea could improve your team meeting every day of every week for a year.   

Why Lawbreaker Works  

The name “Lawbreaker” engages a mindset of something that is different from the “proper” or “familiar” or “approved” approach to your challenge. The name itself gives you permission to change. Academic research confirms the power of being given direction to your thinking. When teams are given overt permission/direction to “think big” or “think bold” or “think radical,” they do so. Wendy Ferris, Innovation Engineering Black Belt at InVision Edge in Winnipeg, Manitoba, Canada, described the Lawbreaker approach this way.  

We are creatures of habit, and often we get caught up in the complacency of being comfortable or blinded by routine. This why I really like using Lawbreaker. It drives “what if ” scenarios and forces the mind towards change. For example, what if we didn’t have access to email to communicate . . . what would we do instead? Lawbreaker is really effective at pushing our thinking forward.   

At its essence, Lawbreaker is about continuing forward with your thinking even when you believe the idea is impossible. Over my many years of problem-solving I’ve found that perceptions calling an idea impossible are rarely true. You just need to invest time doing some thinking and trust that even bad ideas are useful stimuli for creating great ideas.  

The key to success with Lawbreaker is a willingness to let your mind leap to a new place. As your family, friends, or work team build trust in thinking creatively, you can simply say—let’s try Lawbreaker. And the collective power of the group becomes focused on bigger and bolder leaps of thought.   

Barriers to Lawbreaker  

The biggest barrier to Lawbreaker is fear of big changes. Instead of being bold and brave, most people seek the smallest, least disruptive way to make incremental improvements in how they work. In work situations, it’s common to have spoken or unspoken boundaries on how big of a change your team or organization is willing to accept. This boundary becomes a blockage to your thinking. With Lawbreaker, the goal is to think big and bold.  

Lawbreaker is NOT One and Done  

The reality is that big and bold ideas almost always have negative consequences to other parts of the “system” that surround your problem area. In fact, if your “big” idea doesn’t create other challenges or “Death Threats,” then it’s unlikely to be a truly transformational idea. You need to accept that your big idea will require you to create solutions to the potential negative consequences that your big idea causes to other parts of the “system” you are working on.   

Using Lawbreaker to Create Customized Bourbon 

At our young start-up Brain Brew Distillery, we came up with the idea to enable everyone to have their own Custom Bourbon. This set off dozens of “Death Threats,” to our probability of success as it disrupted everything from production to marketing to operations to regulatory issues. Because Custom Bourbon had never been done at scale, Lawbreaker thinking was the only way to find solutions to the multiple Death Threat problems. Here are a few of the biggest Death threats and how we addressed them.  

Death Threat: Federal and State laws won’t allow for custom bourbon.  

It took about a year of problem-solving at both the state and federal levels to register our custom bourbon labels. Our initial applications were rejected as non-compliant. To gain approval, we did a deep dive into the actual rules and regulations of the TTB (Alcohol Tobacco and Tax Bureau of the U.S. Treasury Department). Reading the regulations closely, we found a pathway for making our labels legal. Initially, the revised applications were also rejected, only this time based on other rules we were inadvertently breaking. Nine or so months later, after many cycles of experimentation, we got approval of our formula, label, and products, allowing us to sell custom bourbon legally.  

Death Threat: Consumers won’t be able to tell the difference between the bourbons they are tasting.   

Our distillery is grounded in our WoodCraft Finishing methodology. It’s based on the simple truth that 70% of the flavor and 100% of the smoothness of Bourbon Whiskey comes from the wood. We started with a set of 24 whiskeys. this proved to be overwhelming for customers. Multiple rounds of consumer testing led us to six distinctly different bourbons, each with a distinctly different taste. the unique tastes are a result of being finished with a unique wood that had been cleaned and toasted to enhance differences: 200-year Oak, European Oak, American Oak, Maple Wood, Cherry Wood, and Smoked Oak.   

Death Threat: Blending whiskey is a difficult skill to learn— consumers will not be able to create a great bourbon to their tastes.   

Borrowing from work we did years ago at Eureka! Ranch creating board games and user experiences for the Walt Disney Company, we crafted a “goof proof” journey for our guests. It’s a step-by-step system that starts with tasting and leads to a structured process for blending that makes it easy for consumers to craft a great bourbon that matches their taste preferences. the method we use is basically a consumer-friendly version of the actual method that Bob Dalgarno, whiskey maker of the Macallan for thirty years, taught me. It’s how he brings together barrels of whiskey from different rick houses to create a luxury whiskey.  

One adaptation to Bob’s approach that we had to make was to find something to replace graduated cylinders. While Bob can quickly use graduated cylinders for measuring, it takes consumers some time to use them. this is especially true when we explain the need to measure to the bottom of the meniscus or the curved surface of the liquid. With the help of a small business in Vermont, we created and produced a patent-pending bourbon-blending ladle. It makes it easy for consumers to quickly measure and blend their bourbon with higher accuracy.  

Death Threat: It will cost too much to make one custom label and bottle at a time.  

Filling custom bottles manually would make the bottles cost twice the $45 retail price that our research showed was the sweet spot for pricing. To drive down cost, we had to rethink the consumer purchase and bottle production system. We started by creating a digital system that allows consumers to enter the name for their bourbon and their recipe via their phone. then custom software translates their recipe into a custom label that prints automatically.  

To speed the process of filling bottles, the custom label includes a QR code on the back label that contains the recipe for the bottle. the operator simply scans the QR code, then places the bottle in the custom WoodCraft Bourbon Blending machine that we invented and built. In about 30 seconds the machine fills the customer’s bottle with the custom bourbon.   

Death Threat: Custom bourbon won’t be scalable.

We quickly found that the demand for YOUR Bourbon YOUR Way was immense. However, state laws make it impossible to ship bourbon to most states. To grow our business we needed a new route to market. After exploring multiple options, we settled on franchising Custom Bourbon. It took a little over a year to navigate the laws and regulations of franchising. Recently, we opened our first WoodCraft Bourbon Blender franchise on Main Street in Louisville, Kentucky. As of this writing, we’ve now signed a second, and we expect to soon have many more.  

Throughout the Custom Bourbon journey, every time we ran into a challenge we simply put our heads together and figured out a solution. Early on, we had T-shirts printed with a variation of the famous quote from an Apple Commercial, “Some call us the crazy ones . . . and we’re OK with that.”  

You, too, can make the impossible possible. You simply have to love it. You have to love your idea so much you are willing to put in the time and energy required to problem-solve your way to making it a reality.   

Adapted from PROACTIVE Problem Solving by Doug Hall © 2025 by Eureka! Institute, Inc. Published by Clerisy Press.

About the Author 

Doug Hall, author of PROACTIVE Problem Solving, is the founder of Eureka! Ranch and Brain Brew Distillery. He has been named one of America’s top innovation experts by Inc. magazine, The Wall Street Journal, Dateline NBC, CNBC, and CIO magazine. A hands-on inventor, Hall helps businesses, governments, and nonprofits find, filter, and fast-track big ideas. His earlier books include the bestselling Jump Start Your Brain, Driving Eureka!, and Jump Start Your Business Brain. A chemical engineer by education, Hall was Master Marketing Inventor at Procter & Gamble – shipping a record nine products in twelve months. For his pioneering work in innovation, Hall was awarded a Doctor of Laws from the University of Prince Edward Island and a Doctor of Engineering from the University of Maine.  To learn more, visit: www.doughall.com or www.eurekaranch.com. 

The post The Lawbreaker: How Deliberate Rule-Breaking Drives Innovation  appeared first on The European Business Review.

By Adrian Furnham

Friendly, dramatic, and attention-seeking, they are difficult to miss. You may find them entertaining in social settings, but what happens when you have to work with them? In this article, Adrian Furnham explains how to understand and deal with people with Histrionic Personality Disorder.

We have all had dealings with the Drama Queen Manager: flirtatious, mercurial, show-offs. In psychiatric terminology, they often have clinical or subclinical Histrionic Personality Disorder (HPD), sometimes referred to as Dramatic Personality Disorder.

The HPD term is derived from the Latin word for actor, but the original term was hysterical from the Latin root meaning uterus. This disorder is found more frequently in women. These people are attracted to “limelight” jobs and strive for attention and praise, but setbacks can easily lead to serious inner doubts and depression. Histrionics are certainly emotionally literate: they are open with all their emotions. But these emotions can change very quickly and unexpectedly.

People with HPD tend to be self-centred and have little room for self-doubt.

Most of us have encountered these characters at school, university or work. They tend to have a pattern of excessive attention-seeking and exaggerated emotional displays. Most have an intense desire for approval which can cause many problems. They often seem “over-the-top”, “theatrical”, and “emotional time-bombs” at inappropriate times and places, such as at work. Their flirtatious behaviour causes them multiple problems in the world of work today.

People with HPD tend to be self-centred and have little room for self-doubt. Of course, if mixed with good looks, articulateness and a handful of qualifications, this can seem very advantageous. Think of the conference talk, the media appearance, and the Tik-Tok clip. The ability to exhibit and touch the emotions of others can be a serious advantage. As all orators know, the message travels from the heart to the head, not the other way around.

But their sense of self-worth hinges on how others view them: even the slightest social rejection or criticism can feel incredibly devastating. Many feel  “close to people”, only to later discover those feelings are unrequited. Colleagues learn regularly to question the authenticity of their words and actions. Are they being sincere or exaggerating?

Flirtatious, mercurial, show-offs

Drama Queens seem uncomfortable in social situations where they are not the centre of attention. They delight in making a drama out of a crisis. Their interaction with others is often characterised by inappropriate sexually seductive or provocative behaviour. Needless to say, this causes more of a reaction in women than men, though this may be changing.

They display rapidly shifting and shallow expressions of emotions. They are, as a result, difficult to read. Most use physical appearance (clothes, hair) to draw attention to self, and this may include body piercing or tattooing. They certainly get a reputation in the office for their “unique apparel”.

Histrionics do not make good managers. They get impatient with and anxious about, details and routine administrative functions.

Many have a style of speech that is excessively impressionistic and lacking in detail. Always they show self-dramatisation, theatricality, and exaggerated expression of emotion… usually negative.  Even the dullest topic is imbued with drama. They are easily influenced by others or circumstances and therefore, are both unpredictable and persuadable. Many Drama Queens consider relationships to be more intimate than they actually are. Being rather dramatic, they feel humdrum working relationships more intensely than others.

Histrionics do not make good managers. They get impatient with and anxious about, details and routine administrative functions. They prefer gossip to analysis; and tend not to be good at any sort of detail. They are highly sociable and have intense relationships. They live to win friends and influence people and can do so by being very generous with compliments, flattery and appreciation. They hate being bored: life with them is never staid and dull. Most don’t like being alone for any period.

Interestingly, the definition of themselves comes from the outside: they see themselves as others say they see them. They therefore lack a consistent sense of who they are. They need constant reassurance and positive feedback from others. And because their heart rules their head they can be impulsive, impetuous and impatient. They live not in the real world, but in a storybook world.

At work, they can be persuasive and insightful. They enjoy the world of advertising, PR, sales and marketing, but need a strong back-up for things like plans, budgets and details. They are often volatile and known for being moody. They can be effusive with both praise and blame. But everything is an emotional drama and emotionally, they can be both childlike and childish. They don’t do stable relationships. At work, they need to be the star, the centre of attention otherwise they can feel powerless or desperately unworthy. They are not introspective. And it is important not to overreact to their overreactions.

Different descriptions

1. Muller (2014) argued that histrionic managers can cause “considerable suffering in the workplace, as well as lost productivity and revenue” (p. 402). Histrionic managers operate primarily based on emotion. Reason takes a backseat. They often tend to: “not see to the heart of things”; exaggerate information; overreact to matters that could be handled more easily by rational discussion; have flawed understandings; have trigger points that set them off “sometimes angrily and aggressively”; have “hyper suspiciousness”; be a source of stress, frustration, anxiety for others.

2. De Haan and Kasozi (2014) have talked about the healthy and unhealthy sides of the histrionic They call the former the Accomplished Thespian and the latter the Prima Donna. They provide a short sketch of a typical person who is the latter:

“The Accomplished Thespian becomes the Performing Prima Donna when his focus is more on the performers than on the reason for the performance. Instead of paying attention to doing what is needed, instead of listening to his counterparts, his energy goes into holding his own performance and ensuring that he is looking good in it. In that sense the performance becomes the purpose and the reward, and the wider function or organizational requirement is increasingly missed. The Accomplished Thespian’s tough resolve tips over into being unhelpful when his performances no longer elicit the longer-term outcomes and achievements that the organization seeks. Experiencing the challenge and criticism of others, he becomes less connected with their needs and becomes more concerned with showing that he is delivering or at least doing his best. Paradoxically his attention to performance per se and ignorance of wider circumstances can create a situation where he’s seen as irascible and self-absorbed. He is then experienced as being closed off to reality and not open to constructive feedback. At his most challenged, the Performing Prima Donna is experienced as a self-obsessed and unpredictable loose cannon, a superficial talking shop, and an organizational liability. Those who work with him try to avoid his worst excesses of showing off, and to protect others from his most embarrassing outbursts.” (p 190-191) 

3. Hogan and Hogan (2009) call these types Colourful: people who seem persuaded that others will find them interesting, engaging and worth paying attention to. They are good at calling attention to themselves – they know how to make dramatic entrances and exits, they carry themselves with flair and self-consciously pay attention to their clothes and the way others react to th

Histrionics are marked by their stage presence or persona, their self-conscious and distinctive aura – they perform extremely well in interviews, assessment centres, and other public settings.

“They are great fun to watch, but they are also quite impulsive and unpredictable; everything that makes them good at sales (and selling themselves) makes them poor managers – they are noisy, distractible, over-committed, and love to be the centre of attention. They are not necessarily extraverted, they are just good at calling attention to themselves. At their best, they are bright, colourful, entertaining, fun, flirtatious, and the life of the party. At their worst, they don’t listen, they don’t plan, they self-nominate and self-promote, and they ignore negative feedback”.  (p. 49)

Histrionics deal with stress and heavy workloads by becoming very busy; enjoying high-pressure situations when they can then be the star. Breathless with excitement, they confuse activity with productivity and evaluate themselves in terms of how many meetings they attend rather than how much they actually get done. A key feature of these people that others may not appreciate is how much they need and feed off approval, and how hard they are willing to work for it. And this explains why they persist in trying to be a star after their lustre has faded. To work with them, colleagues have to be prepared to put up with missed appointments, bad organisation, rapid change of direction, and indecisiveness. This will never change, although it can be planned for.

To be specific:

• Appearance: As noted, they are likely to dress provocatively or with attention-seeking features. This can include revealing clothing, suggestive or extensive tattoos, brightly coloured hair, and eccentric hairstyles, and they may wear multiple accessories.
• Behaviour: They have eccentric and disinhibited behaviours. They may have “splitting behaviors” depending on how an interview is proceeding. Splitting is a mental mechanism in which the self or others are viewed as all good or all bad, without integrating the positive and negative qualities of the self and others into cohesive images. Other behaviours can include dramatic storytelling, hypersexual gestures, and acting out to become the centre of attention.
• Speech: They are likely to speak loudly and dramatically. Their speech is generally impressionistic and lacking in detail. Deficits with speech initiation or vocabulary are not expected.
• Thought process: Usually their thought process is expected to be linear yet limited in range and logic. These individuals tend to be easily suggestible and easily persuaded by others around them.
• Impulse control: They often have poor impulse control, which results in the engagement of many of their pathological behaviours.
• Insight: They are ego-syntonic, where behaviours, values, and feelings are consistent with one’s ideal self-image. Thus so, individuals with HPD typically have poor insight into their condition and how their behaviours impact their social and occupational functioning.

4. In 2000, Theodore Millon suggested six subtypes of histrionic personality disor Any individual histrionic may exhibit one or more of the following:

5. Oldham and Morris (2000) noted seven charac-teristics of this type, which they call Dramatic.

A person who reveals a strong Dramatic tendency will demonstrate more of these behaviours more intensely than someone who has less of this style.

1. Feelings

Dramatic men and women live in an emotional world. They are sensation-orientated, emotionally demonstrative, and physically affectionate. They react emotionally to events and can shift quickly from mood to mood.

2. Colour

They experience life vividly and expansively. They have rich imaginations, they tell entertaining stories, and they are drawn to romance and melodrama.

3. Spontaneity

Dramatic individuals are lively and fun. Their joie de vivre leads them to act on impulse to take advantage of the moment.

4. Attention

Dramatic people like to be seen and noticed. They are often the centre of attention, and they rise to the occasion when all eyes are on them.

5. Applause

Compliments and praise are like food and water to persons with Dramatic style: they need them to go on.

6. Appearance

They pay a lot of attention to grooming, and they enjoy clothes, style and fashion.

7. Sexual attraction

In appearance and behaviour, Dramatic individuals enjoy their sexuality.  They are seductive, engaging, charming tempters and temptresses. (p.  126-127)

Oldham and Morris also offer six tips on dealing with them.

You are attracted to the Dramatic person’s spontaneity, passion, sensuality, and ability to have a good time. Allow the Dramatic person his or her emotional freedom, and enjoy the range of experiences that will result.

Appreciate, praise, flatter, and give feedback. The Dramatic person needs you to react openly and verbally, especially about your positive feelings, at all times. Don’t hold back; there’s no such thing as too much of a good thing with this personality style. But be sure to be honest.

Be romantic. Even if the Dramatic person in your life is a friend, relative, or parent, these sentimental attentions will delight and thrill him or her.

Be realistic about this person’s relative inability or reluctance to handle certain responsibilities, including money. Handle the finances or the financial planning yourself, if need be. Better, supervise or double check essential details.

Don’t hold grudges. Dramatic persons don’t hold things in, and the Dramatic person in your life may be emotionally tempestuous. Try to let go of your own anger or annoyance. Don’t take the Dramatic person’s emotional reactions personally and don’t be frightened by the drama.

Avoid jealousy. Dramatic individuals like to charm other people. Try feeling flattered and turned on by the warm attentions of others to your mate and have a good time at the party. (p. 139-140)

There are drama-queens in all sectors though they are likely to be found in the more human resource orientated world. They can do very well in PR, marketing and training particularly if they are talented. But they certainly remain hard work for their ever-suffering reports.

Three Important Caveats

Dimension not type

Psychiatrists have long given up on the typological approach in the sense of believing that you are, or are not histrionic. It is a matter of degree. You may be low, average, high or very high. Some situations may bring out the less desirable aspects of the disorder. Most of the descriptions are of those very high on the dimension.

Advantage not disadvantage

It is possible that in the right job and with other benefits (like being good-looking, bright, well supported by others) a small dose of histrionic behaviour may be very beneficial. Think of the performing arts, sales, and public speaking. If they have a colleague, PA or trusted advisor to calm them down, reassure and give timely feedback they may thrive.

Front not Back Stage

Goffman, the famous sociologist argued that social life is a “performance” carried out in three places: “front stage,” “backstage,” and “off stage.” All social interaction is influenced by the time and place in which it occurs as well as by the “audience” present to witness it. Thus some people might look a tad histrionic because the situation calls for it, but it is just a show. The histrionic however hates the backstage and likes to live their whole life on the front stage, preferably in the lead role.

Interestingly, of personality disorders like Borderline, OCD, and Narcissism, there appears to be much less academic or clinical interest in Hysterical Personality Disorder. Perhaps it is not such a problem for the client/patient after all, though it may be for their colleagues.

About the Author

Adrian Furnham is an Emeritus Professor in the Department of Leadership and Organisational Behaviour at BI: Norwegian Business School. Recognising that he has more than a touch of Histrionic Personality Disorder himself, he does as all psychologists must do: namely study themselves.

References

• De Haan E. and Kasozi A. (2014). The Leadership Shadow– How to Recognise and Avoid Derailment, Hubris and Overdrive. London: Kogan Page.

• Furnham, A. (2014). A Bright Side, Facet Analysis of Histrionic Personality Disorder. Journal of Social Psychology, 154, 527-536.

• Hogan, R., & Hogan, J. (2009). Hogan Development Survey Manual (3rd ed.). Tulsa: Hogan Assessment Systems.

• Millon, T. (2004). Personality Disorders in Modern Life. Hoboken, New Jersey: John Wiley & Sons, Inc

• Muller, R. (2014). Histrionic Managers Wreck Havoc in the Workplace: Identifying the Phenomenon. The Humanistic Psychologist, 42, 402-412

• Oldham, J. M., & Morris, L. B. (2000). New Personality Self Portrait. New York: Bantam Book.

The post The Drama Queen Leader: Theatricality and Inappropriate Behaviour appeared first on The European Business Review.

By George Kohlrieser

In my years as a hostage negotiator, I learned a profound truth: people do not change because of force—they change because of connection and hope. Hostage negotiators achieve a 95% success rate, not by using weapons, but by using words, influence, and empathy.

You may not be dealing with armed criminals in your workplace, but you might feel hostage to a difficult colleague—the chronic complainer, the micromanager, the underperforming team member, or the one who always finds fault and is negative. These colleagues and situations can make one feel powerless, exhausted, and emotionally drained – like a hostage without a physical weapon. The key to regaining power is to shift from reacting to controlling what you can – and that is yourself. This happens by focus on one’s mindset and then the conversation with connection and influence.

The First Step: Are You a Psychological Hostage?

A mistake many professionals make is believing that their challenging colleague controls their emotions. They feel trapped by negativity, drained by gossip, or undermined by an uncooperative teammate. The real hostage-taker is not only the colleague, but being a hostage to one’s own mindset and emotional triggers.

We must break free from this “hostage mindset” by understanding that we always have a choice. No matter how difficult someone is, we have the power to influence ourself by managing our emotions, our reactions, and the way we communicate. This also sometimes includes drawing a boundary.

Story #1: Lisa and the Unreliable Teammate

Marie was an exceptional professional—dependable, hardworking, and deeply committed to delivering results. For months she carried the weight of her unreliable teammate, Peter.

Peter routinely missed deadlines, made excuses, and avoided accountability. Marie grew more resentful each time she corrected his mistakes. She felt like a hostage—forced into a situation where she had to compensate for his shortcomings.

Marie’s first instinct was to keep quiet and pick up the slack—a strategy many people use to avoid conflict and confrontation. Then she realized this approach was unsustainable.

The Breakthrough Conversation:

Marie scheduled a one-on-one conversation with Peter. Instead of blaming him, she took a curious, problem-solving approach.

“Peter, I’ve noticed that some of your work has been delayed, and I’ve often had to step in at the last minute. I’m starting to feel overwhelmed, and I wanted to understand if something is making it hard for you to meet deadlines.”

At first, Peter was defensive, but Marie’s non-accusatory tone created an opening. He finally admitted:

“I’ve been afraid to tell our manager that I’m struggling. I didn’t want to look incompetent.”

By creating a bond instead of attacking him, Marie uncovered the real issue—fear. Together, they found a solution: they approached their manager to redistribute tasks more fairly. Peter also agreed to communicate sooner if he needed help. Peter himself had been a psychological hostage, leading him to take Marie as one as well.

Key Lesson:

Many workplace conflicts come from unspoken fears. If we assume bad intent, we escalate the problem. If we connect first to understand, we can then invite change.

Story #2: Richard and the Negative Team Member

Richard led a high-performing team, but one person, Alex, constantly drained the group’s energy.

• When they won a big contract, Alex said, “Great, more work for us.”
• When Richard implemented a new strategy, Alex sighed, “This will never work.”
• Soon, team morale began to erode because Alex’s negativity was contagious.

Many leaders ignore and are a psychological hostage to toxic behaviour, hoping it will go away. Negativity spreads like a virus—it poisons the environment if left unchecked. Plain and simple it is an underperforming behaviour.

The Breakthrough Conversation:

Richard invited Alex for coffee. Instead of attacking, he led with curiosity.

“Alex, I’ve noticed that you’re often critical of new ideas. I want to understand what is behind that. Are there concerns that I’m not seeing?”

Alex, caught off guard, admitted:

“I just don’t want us to waste time on ideas that won’t work.”

Richard saw an opportunity:

“I appreciate your eye for detail. How about we shift the approach? Instead of saying why something won’t work, can we frame it as: ‘Here’s a challenge, and how will we solve that?”

Alex hesitated and agreed to try. Over the next few weeks, his default responses slowly changed. Instead of shutting down ideas, he started pointing out challenges and even offering solutions. The team’s energy shifted—they felt safer to contribute without fear of criticism.

Key Lesson:

People don’t resist the change itself. They resist the pain of the change or the fear of the unknown. What is the pain of the change or the fear of the unknown? The best way to influence difficult colleagues is not through forcing change. It is through understanding with connection and dialogue what is behind the resistance.

How to Use the Hostage Negotiator’s Mindset at Work

Managing challenging colleagues is not about avoiding conflict—it’s about leading through it. Here’s how you can transform a difficult relationship in three steps:

1. Break the Hostage Mindset

Ask yourself: “Am I reacting to this person, or am I leading the dialogue?”. When you take control of your response, you free yourself from the hostage mentality.

2. Create a Bond Before Addressing the Problem

In hostage situations, the first step is connecting and bonding even if it is an adversary.

Use curiosity: “I’ve noticed you seem frustrated with this process. What’s your take?”

• Acknowledge their perspective: “I can see this change feels disruptive for you.”
• Listen more than you talk.

3. Shift the Conversation from Disagreement to Collaboration

Instead of saying, “You’re unreliable”, say:
“I want to understand what’s making it hard for you to meet deadlines.”

Instead of saying, “You’re too negative”, say:
“Your insights are valuable. How can we use them constructively?”

Instead of saying, “You need to change”, say:
“How can we find a way that works for both of us?”

Final Thoughts: Freedom Through Influence

In every challenging relationship, there is a choice: remain involved in the conflict or take action to resolve it.

Difficult colleagues don’t have to control your emotions, your day, or your career. The moment you shift from reacting to influencing, you reclaim your power.

True leaders—whether hostage negotiators or corporate executives—don’t avoid difficult conversations. They master them.

The workplace is filled with challenges, but connection is always the key to change. And that begins with you.

About the Author

George Kohlrieser is the author of Hostage at the Table (second edition) and Distinguished Professor of Leadership and Organisational Behaviour at the International Institute for Management Development (IMD).

The post How to Manage Challenging Colleagues appeared first on The European Business Review.

By Keith Kakadia

Establishing an active social media presence can be a great move for all types of business. Not only do social media platforms give you the perfect format for creating more awareness surrounding your products and services, but they can also be an excellent source of referral web traffic. 

However, getting the most value out of social media requires maintaining an adaptive mindset. Tactics you may have used years ago to gain more followers and achieve more engagement are likely considerably less effective today. Social media platforms are dynamic, and algorithms are constantly reshaping how businesses should approach posting content and sharing new updates. 

Still, by keeping your business flexible, you can create a focused and sustainable strategy that will lead to a stronger online presence. 

The Good and the Bad of Social Media Algorithm Changes 

All social media platforms use various algorithms to decide if and when certain types of content should be served to viewers. No different to how Google uses crawlers to index websites and rank them on search engine results pages (SERPs) based on their perceived relevancy, social media platforms apply the same methodologies. 

Although this increased accuracy surrounding behavioral analysis is beneficial for platform users and minimizes the chances they’ll be inundated with information they’re not interested in, these algorithms can create certain challenges for brands. 

From a business perspective, shifts in algorithms can have huge gains or losses in relative brand positioning. Algorithm changes that move in favor of a business could mean significantly more reach and visibility, which often results in more qualified leads and higher conversion percentages. On the other hand, if algorithm changes tip the other way, a business could quickly lose its footing on specific platforms and see declining revenue streams month to month. 

How Platform UX Redesigns Impact User Behavior 

Designing digital platforms with the user in mind is a key aspect for success for all types of businesses, including social media sites. User experience (UX) design updates usually mean navigation layout changes, newer content formats, and possibly the elimination of redundant platform features.  

When websites make these changes, they’re often doing it for a specific reason – usually to bring more attention to other parts of the platform or creating a more efficient lead funnel. When social media platforms make these subtle or larger changes to their layout, it can directly impact user behaviors when engaging with brands. Understanding the impact that UX changes have on your own business is critical to make sure you optimize your marketing approach to compensate for the changes. 

Strategic Steps You Can Take to Evolve With Social Media Changes 

To help your business stay ahead of algorithm shifts on social media platforms, below are some strategic steps you can take: 

1. Stay Up-to-Date on Potential Changes

Keeping your business informed about potential social media changes is critical. Social media algorithm changes can happen quickly and without much work. However, brands that stay informed are in a much better position to adapt their strategies proactively.  

Following social media blogs and subscribing to platform newsletters are valuable resources for staying in the know. Also, it’s always good to take a look at what the leading social media agencies are rolling out for their campaigns. It provides a direct view into how industry leaders are adapting to these changes, offering inspiration for your own strategy. 

2. Rely on Data Analysis

Data analysis is essential for better understanding your audience’s behavior and the relative performance of the content you produce. By tracking key metrics, you can gain valuable insights into what resonates with your target audience.  

Most social media platforms have analytics tools that can offer a wealth of information. This includes allowing you to monitor engagement rates, your overall brand visibility, and other important metrics. For instance one of the most asked questions we get is knowing the best times to post on X/Twitter. Being able to have the right tools to understand the intricacies of each platform, your industry and the corresponding audience, can help you maximize engagement and reach the right audience at optimal times. 

3. Prioritize Higher Quality Content

Creating high-quality and engaging content is more critical than ever. Considering the sheer volume of information available online, brands need to regularly produce content that stands out and provides value to their audience. 

Customizing your content approach to the specific platform and its user base is a great way to do this. Take the time to understand the nuances of each platform. This will help you to create content that resonates with the target audience and stays in alignment with the platform’s best practices.

And increasingly in today’s social media environment, platforms like TikTok focus so much more on the quality and consistency of your content to grow your followers, that you cannot try to expedite and spend your way to a huge follower base. The content must be authentic, high quality and resonate.  

4. Diversify Your Content Formats

Experimenting with different content formats is another great way to reach a wider audience and adapt to algorithm shifts. Incorporating video content, live streams, interactive polls, and other engaging formats can greatly improve the user experience and bring more attention to the brand.  

Diversifying your content formats also provides better resilience against algorithm changes. If one format experiences a decline in reach, other formats can help maintain a strong presence and continue to drive engagement. 

5. Future-Proof Your Social Media Strategy

Building a strong brand identity and establishing a thriving social community is essential for long-term success on social media. Authenticity is key here. Brands that connect with their audience on a genuine level naturally build more loyalty.  

Flexibility is also crucial. Being willing to experiment with new approaches, adapt to platform updates, and embrace change is essential for staying visible regardless of how platforms shift their UX approach. 

Keep Your Business’s Social Media Approach Adaptable 

Social media platforms are always changing how they source and push content to their users. By understanding the dynamics of social media algorithms and UX changes, making use of data-driven insights, and prioritizing high-quality and diverse content, you’ll ensure your social media strategy remains effective, regardless of the platform’s evolution.

About the Author

Keith Kakadia, founder and CEO of Sociallyin, has been at the forefront of transforming the social media marketing landscape for over 13 years. From humble beginnings at Mississippi State University to building a world-class agency that serves clients like Samsung, Carnival Cruise Line, and Nikon. Keith has earned a reputation as a trailblazer in leveraging social media to drive brand success. 

The post Adapting to Algorithm and UX Changes: Why Your Social Media Strategy Must Evolve with the Platforms  appeared first on The European Business Review.

By Alessandro Lanteri and Mark Esposito

The rapid development of AI technology has brought in agentic AI systems with the ability to be autonomous and make independent decisions. This will redefine how organizations work and create a solid global economy.

In an era where artificial intelligence is rapidly transitioning from simple automation to sophisticated autonomy, the advent of agentic AI marks a pivotal shift in the technological landscape. Agentic AI systems, characterized by their ability to make independent decisions and act autonomously without continuous human oversight, are poised to revolutionize industries and reshape the workforce. For example, Nvidia CEO, Jensen Huang wants the company to grow to 100 million employees, the majority of which will be digital agents.

This is not merely a speculative vision of the future. Nvidia is already using some of these digital employees to design chips and develop software. Elsewhere, AI agents are also employed by AT&T to detect fraud and optimize network usage and by The Ottawa Hospital to improve patient experience and reduce administrative burden.

As these autonomous agents become increasingly capable of performing tasks that once required human supervision, next-generation enterprises will emerge that are autonomous, scalable, and networked and will surpass conventional models.

Next-Generation AI

This new generation of virtual employees is fundamentally different from the first-generation AI expert systems of the 1950s, the second-generation machine learning models of the 1990s, and even the latest generative AI developments like ChatGPT or DALL-E⁴. These advanced systems represent a new kind of artificial intelligence known as agentic AI because they possess agency (sometimes referred to as ‘agenticness’)⁵ — the capacity to perceive their environment, reason about complex situations, make decisions, and execute actions to achieve specific goals without continuous human supervision. Designed to act independently, these AI agents learn and adapt through their interactions and experiences.

Agentic AI operates through a four-step process for problem-solving:

• Perception: AI agents begin by gathering and processing data from various sources, including sensors, databases, and digital interfaces. This step involves extracting meaningful features, recognizing objects, and identifying relevant entities within their environment.
• Reasoning: A foundation model functions as the reasoning engine. It understands tasks, generates solutions, and coordinates specialized models tailored to specific functions such as content creation, image processing, or recommendation systems.
• Action: Agentic AI integrates external tools and software in order to execute tasks based on the plans it has devised. To ensure tasks are performed correctly, guardrails can be established. For example, a customer service AI agent might be authorized to process claims up to a certain amount, while claims exceeding that threshold would require human approval.
• Learning: Agentic AI continuously enhances its performance through a feedback loop. The data generated from the AI’s interactions is fed back into the system to refine and improve its models. This ability to adapt and become more effective over time empowers businesses to drive better decision-making and operational efficiency.

For example, in the financial sector, an agentic AI could analyze market trends, adjust investment portfolios in real-time, and execute trades independently to maximize returns while managing risk. These same tasks are still performed by people in some financial boutiques and by people supported by AI in larger financial institutions. The key distinction between agentic AI and other forms of artificial intelligence lies in autonomy and capacity for independent action (table 1).

Strategic Advantages of Agentic AI

The long-term promise of any technology depends on its ability to confer some unique competitive edge. Agentic AI indeed offers strategic advantages that go beyond traditional AI systems, by expanding some of the known benefits of AI — operational efficiency and cost reduction — and empowering new benefits — improved decision-making and scalability and flexibility.

• Operational efficiency. Agentic AI can autonomously handle intricate, multi-step processes that still require significant human intervention with current AI systems. This reduces the operational burden on employees and ensures that critical services are maintained around the clock — because AI agents operate continuously without fatigue — and so improves overall productivity.
• Cost reduction. Automating tasks with agentic AI reduces labor costs and minimizes errors, leading to savings. Agentic AI optimizes the use of resources such as materials, energy, and time, contributing to cost-efficiency and sustainability goals.
• Improved decision-making. Agentic AI can process vast amounts of data in real-time, providing immediate insights and enabling quicker, more informed decision-making. This leads to better strategic alignment and responsiveness to market dynamics.
• Scalability and flexibility. Agentic AI systems can adjust in real time to changes in the environment, market conditions, or organizational strategies, ensuring optimal scale, continuity, and resilience. They can be scaled up or down on demand, in a similar fashion to scaling cloud computational power, without the delays associated with recruiting and training new staff.

The strategic benefits of agentic AI are compelling. Moreover, though developing agentic AI is expensive, deploying it is “effortless”⁸. Therefore, as soon as agentic AI services become available, businesses will rush to adopt them.

Trajectories of Agentic AI

With widespread adoption, agentic AI will gather data that accelerate its performance (table 2) and therefore magnify its impact on organizations and workers.

Short-term evolution

In the immediate future, agentic AI applications will look like refinements of the current AI trends toward operational efficiency, achieved by automating routine and repetitive tasks. AI agents will handle administrative duties such as data entry, scheduling, and basic customer service inquiries. Early adopters in sectors like manufacturing, logistics, and healthcare will leverage agentic AI for tasks such as predictive maintenance, supply chain optimization, and patient monitoring.

Medium-term transformation

As agentic AI matures, its integration into organizations will become more profound. In the medium term, job roles and organizational structures will be transformed. AI agents will take over tasks that feel complex to humans. Decision-making processes will evolve. For example, agentic AI will contribute to strategic planning by simulating scenarios and forecasting trends with a level of speed and accuracy unattainable by humans alone. Organizations will restructure to maximize the benefits of agentic AI, adopting flatter hierarchies and more agile team configurations. Finally, the workforce will undergo significant changes. While some traditional jobs may diminish, new roles centered around AI — such as AI ethicists, strategists, and maintenance specialists — will emerge. Continuous learning will become imperative as employees must adapt to rapidly evolving technologies.

Long-term disruption

In the long term, agentic AI is anticipated to fundamentally disrupt entire industries and redefine the nature of work and organizational structures. Visionaries like OpenAI CEO Sam Altman have envisioned scenarios where companies could grow to unicorn status under the management of a single individual⁹. With agentic AI, one-person unicorns will become the norm in certain sectors. Autonomous operations will empower disruptive business models, with AI agents managing core functions with minimal or even no human oversight. For example, in industries such as transportation, the widespread adoption of fully autonomous vehicles and logistics networks could revolutionize mobility and supply chains. As market conditions evolve, agentic AI systems will dynamically scale to meet demand. Nvidia CEO Jensen Huang has predicted that “AI’s will recruit other AI’s to solve problems” , highlighting a future where autonomous AI agents work together to address complex challenges without human supervision.

Next-Generation Enterprises: Autonomous, Scalable, and Networked

Historically, humans with human intelligence have designed jobs for humans, leveraging human skills and coordinating tasks that humans can perform. As technology evolves, it has been incorporated into these tasks and their organization, gradually refining jobs over time. Presently, humans still play a critical role in hybrid work systems built on collaborative intelligence, where tasks at which humans excel are intelligently integrated with those at which machines excel, achieving performance levels that would otherwise be impossible.

As agentic AI masters new skills, future tasks may be redesigned by AI agents within agentic meshes in a way that could potentially eliminate human involvement altogether or relegate humans to serving as inputs within machine-first systems of value creation.

Over time, however, AI agents will eventually “find each other, collaborate, interact, and transact” in an interconnected ecosystem, which can be called an “agentic mesh”. Interconnected AI agents can exchange data, insights, and resources in real-time, creating a dynamic network that functions as a cohesive whole. This interconnectedness allows for seamless coordination and optimization of complex systems without human supervision. As agentic AI masters new skills, future tasks may be redesigned by AI agents within agentic meshes in a way that could potentially eliminate human involvement altogether or relegate humans to serving as inputs within machine-first systems of value creation.

The original logic of a one-person unicorn may have been that one human can supervise and control AI performing the tasks humans would perform. That too might evolve into a system where AI agents supervise tasks that other AI agents would perform.

The emergence of agentic AI is set to revolutionize the business landscape by empowering next-generation enterprises that are autonomous, scalable, and deeply networked.

Autonomous. Agentic AI autonomy allows enterprises to operate with greater agility and responsiveness. For example, in the manufacturing sector, autonomous AI agents can oversee production processes, adjust parameters in real-time to optimize efficiency, and predict maintenance needs to prevent downtime — all without direct human intervention. This leads to higher productivity and the ability to adapt swiftly to changing market demands or unforeseen disruptions.

Scalable. The scalability of next-generation enterprises is greatly enhanced by the capacity of agentic AI to handle vast amounts of data and manage complex operations efficiently. AI agents can be replicated and deployed across multiple functions and regions without the limitations inherent to human labor. As business requirements grow, enterprises can scale their operations seamlessly by deploying additional AI agents, ensuring consistent performance and quality. This scalability is not only vertical but also horizontal, allowing enterprises to expand into new markets or add new services rapidly. For instance, in customer service, AI agents can handle increasing volumes of customer interactions simultaneously, providing personalized support to a global customer base without the need for proportional increases in human staff.

Networked. Agentic AI also fosters the development of networked enterprises, where businesses are interconnected through AI agents that collaborate and communicate across organizational boundaries. These networked enterprises leverage agentic AI to form dynamic ecosystems that facilitate real-time data exchange, shared insights, and coordinated actions. In such an ecosystem, AI agents from different companies can interact to optimize supply chains, align production schedules, and respond collectively to market trends or disruptions. For example, in the logistics industry, AI agents representing manufacturers, distributors, and retailers can synchronize their operations to ensure timely deliveries, reduce inventory costs, and enhance overall efficiency.

Conclusion

The autonomous, scalable and networked nature of the next generation of enterprises enables the creation of a complex web of AI agents that continuously communicate, learn from each other, and adapt their behaviors accordingly. This interconnectedness enhances the ability of enterprises to innovate and respond to changes collectively. Innovations and best practices discovered by one AI agent can be quickly disseminated across the network, benefiting all connected entities. This results in a highly adaptive business environment where enterprises are not isolated entities but integral parts of a larger, intelligent network.

Moreover, the combination of autonomy, scalability, and networked operations allows next-generation enterprises to implement radically innovative business models. Organizations can operate with leaner structures, reducing overhead costs associated with large human workforces while maintaining — or even improving — service quality and operational efficiency. Resources previously dedicated to routine tasks can be reallocated to strategic initiatives, research and development, and enhancing customer experiences. Additionally, the networked approach opens up opportunities for collaborative value creation, where enterprises co-develop products or services, share resources, and enter new markets collectively.

By embracing agentic AI, next-generation enterprises can operate more efficiently, innovate rapidly, and collaborate effectively within interconnected ecosystems. This new paradigm redefines how businesses function, fostering a dynamic and cooperative global economy where the collective capabilities of networked enterprises unlock unprecedented opportunities for growth and value creation.

About the Authors

Dr. Alessandro Lanteri is a Full Professor of Strategy at ESCP Business School where he teaches and directs executive education programs globally. He helps executives and students navigate turbulent environments and seize the opportunities of hyper-transformation. His recent books are CLEVER. The Six Strategic Drivers for the Fourth Industrial Revolution (Lioncrest, 2019), Innovating with Impact (The Economist, 2023) and Financial Social Innovations. A New Framework to Understand the Social Innovations Disrupting the World of Finance, from Crowdfunding to Bitcoin (Routledge, 2024).

Dr. Mark Esposito is a professor of economics and public policy with appointments at Hult Int’l Business School and Harvard University. He equally serves as an Adjunct Professor of Public Policy at Georgetown University’s McDonough School of Business. He co-founded the Machine Learning research firm, Nexus FrontierTech and the EdTech venture, The Circular Economy Alliance. He has equally co-founded The Chart ThinkTank and The AI Native Foundation. He was ranked by Thinkers50 in 2016 as one of the 30 rising business thinkers in the world and was shortlisted for the Breakthrough Award in 2019 and the Strategy Award in 2023.

References

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2. Robuck, M. (2024). AT&T Arms Agents for Next Phase of GenAI Revolution. Mobile World Live, Jul 18.

3. The Ottawa Hospital (2024). The Ottawa Hospital Introduces AI-powered Digital Teammate to Share Information with Staff, Patients, and Visitors. The Ottawa Hospital, Jun 13.

4. Gill, SS. et al. (2022). AI for Next Generation Computing: Emerging Trends and Future Directions. Internet of Things 19: 100514.

5. Shavit, Y. et al. (2023). Practices for Governing Agentic AI Systems. OpenAI Research Paper,

6. Pounds, E. (2024). What Is Agentic AI? Nvidia, Oct 22.

7. Lanteri, A. (2021). Strategic Drivers for the Post-Pandemic Era. The European Business Review, March 24.

8. Puutio, A. (2024). The Agentic AI race Is on, and the Blue Chips Are All in. Forbes, Nov 15.

9. Confino, P. (2024). Could AI Create a One-Person Unicorn? Sam Altman Thinks So — and Silicon Valley Sees the Technology ‘waiting for us’. Fortune, Feb 4.

10. Broad, E. (2024). Agentic Mesh. Principles for an Autonomous Agent Ecosystem. Towards Data Science, Nov 19.

11. Lanteri, A. (2017). Tesla Is Fixing Its Automation Problems with Collaborative Intelligence. Hult blog, Thought Leadership.

12. Moravec, H. (1990). Mind Children. The Future of Robot and Human Intelligence. Harvard University Press.

According to what is known as Moravec’s paradox, tasks that are effortless for humans — such as motor skills and social interactions — are challenging for machines to replicate whereas, tasks that are difficult for humans, like complex mathematical calculations or analyzing large volumes of data, are relatively straightforward for machines. For example, an algorithm can predict a patient’s risk of a particular condition based on their medical history and lab results, but it struggles to grasp the nuances of the patient’s individual cases or consider their social and environmental factors.

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By Dr. Rebecca Homkes 

Great strategy thrives when it breaks critical tension. Strategic leaders have long balanced timeframes, focus versus adaptability, and clarity amongst uncertainty.  But pressures are mounting, and new information enters faster than systems can filter it.  Leaders must separate the nuances from the distracting noise to ensure they make better, faster decisions that are aligned with strategic priorities.  Dr. Rebecca Homkes shares how leaders can help their teams build critical internal predictability in order to thrive in uncertain environments. 

Great strategy lives at the intersection of tensions.

Strategy is a midterm articulation of value creation: straddling three-year needle movers between pursuing long-term stakeholder value and adapting to shorter-term opportunities. 

Strategy is being flexible and open to new learnings but focused on articulated priorities. 

Strategy is about making choices about where to compete, win, and invest.  These choices demand clarity but must be made when you never know everything you would like to know.   

Leaders have always operated within these tensions, but the pressure of change on the system is heightened.  Daily news cycles have become hourly, with orders and announcements constantly flooding the zone of information. 

As leaders, how do we incorporate the right information that will impact our strategy while filtering out the distractions? 

Bringing nuance in and noise out to thrive during external uncertainty comes from building internal predictability.  You have it when your team can answer yes to these five questions: 

1. I know our critical beliefs, and how these link to our choices 
2. I know what we are trying to achieve, and why it matters 
3. I know where critical decisions take place 
4. I can rely on others to do what they say they will do 
5. When I do adapt, it is recognized and rewarded 

Beliefs form choices  

The foundation of strategy is a set of prioritized, testable beliefs, as these frame your strategy choices that follow.  While most teams discuss trends, high-performing teams turn these discussions into strategic dialogue by articulating their midterm beliefs.  A belief implies taking a stance, and a good belief is one that can be watched or tested over time.  Beliefs are critical, as we need to avoid the trap of jumping from trend to implication.  For example, we see possible tariffs therefore we most stockpile inventory.  This may be the appropriate choice, but knee jerk reactions are not strategy.  To build your foundation, complete this sentence:  

We are seeing X [this trend] and we believe Y for the midterm [your team’s belief] which means Z for us [the possible strategic implication. 

As you move forward, you will get earlier feedback on whether your beliefs are tracking than your execution of priorities.  As the news cycle continues, your team can view incoming information with this belief filter– is this providing more clarity on a belief, challenging it, or irrelevant noise.  

Choices provide alignment

Strategies need goals.  But in a growth strategy the goal has two jobs: tell us where to go and give us a structure to make decisions as we execute.  With information flooding the system, it is easy to get distracted if we are lacking a finish line.  So provide your team with the needed context: what is success. 

Team members also need structure, which they get from boundary conditions. Boundaries provide the non-negotiables or parameters they must stay within as they execute towards the finish line. 

Information that does not relate to your finish line or boundaries is noise; information that gives additional context on our journey must be brought into the discussion. 

Agility in decision-making

Agility without strategy is chaos.  True agility presupposes a strategy so that leaders can align day-to-day decisions with other leaders without needing oversight, micromanagement, or detailed guidance.   The definition of agility is simple but critical: Agility is making good decisions quickly aligned with strategy and then resourcing them appropriately.   

You can build this by better clarifying decision-making rights and ensuring these are in the right place.  When lacking speed in execution, teams often blame process or bureaucracy, but it is usually more basic: they lack clarity of decision-making rights, or they are not distributed appropriately.  Say new information comes in that challenges some critical beliefs, or an ideal customer makes a unique request.  Team members often know a response is required, but they do not know if they can make that decision.   They will freeze, say ‘hold on’ to the customer and ask their boss. Things can continue to escalate until the decision is made, but by then it will probably be too late to matter. Worse, those distributed leaders never build their decision-making capability. 

In thriving organizations, decision-making rights are codified so leaders know if they are to make the decision when relevant information comes, and more critically where to route it to if not.  

Reliability gives speed

Organizations are networks of commitments that extend up, down, and across the organization.  The things that don’t get done are usually the things that come in from the side.  When trust – our ability to rely on others to do what they say they will do – erodes, execution falters.  

When reliability is high, team members are free to execute their commitments without worry or concern about others not being met.  More critically, when reliability is low, we become inwardly focused – spending time escalating issues, calling alignment meetings, and endless chasing.  There is critical information coming in we must address, but we are too busy following up on stuff.  

In high-performing companies, high reliability enhances adaptability. These organizations can execute at speed because they have trust in commitments. When team members can trust others to do what they are supposed to, you can focus on value creation and move faster than others on identified market opportunities.  

Adaptability is a capability 

To achieve this last piece, change must be accounted for as a core part of execution.  When leaders adapt and adjust within the boundaries of the strategy, this must be recognized and rewarded.    Leaders who make fast decisions on the ground that stay within boundaries should be celebrated, especially when the plan is becoming challenged by market uncertainties.  If you assume the world will change, help your leaders learn how to change and then celebrate and reward them when they do it in the market.

But not all news demands a rection, much is a distraction: internal predictability is a capability.   

To have a capable team that can bring the nuance from the market into strategy and ignore the noise the key filter must be built, maintained, and rewarded of knowing: 

• Does this fit within or challenge an existing belief? 

• • If so, how does this affect our choices we are making as we execute towards the finish line? 
  • For these choices, where do critical decisions take place? 
  • As we execute these, can we rely on others to do what they say they will do? 
  • And when we do adapt- appropriately – is it recognized and rewarded 

Internal predictability is powerful.  Noise will continue to overwhelm strategic nuance in the eternal world over the timeframe of your strategy.  Winning teams provide a capability of framing in so they can manage internal uncertainty down, so they can more effectively manage – and thrive through – external uncertainty. 

Concepts have been adapted from Survive Reset Thrive: Leading Breakthrough Growth Strategy in Volatile Times by Dr. Rebecca Homkes.

About the Author

Dr. Rebecca Homkes is a high-growth strategy specialist and CEO and executive advisor.  She is a Lecturer at the London Business School, Faculty at Duke Corporate Executive Education, Advisor and Core Faculty for BCGU (Boston Consulting Group), and a former fellow at the London School of Economics Centre for Economic Performance.  A best-selling author, global keynote speaker and recognized thought leader, she is also the global Faculty Director of the Active Learning Program with the Young Presidents Organization (YPO), leads several fintech accelerators, and serves on the Boards of many high-growth companies.  She earned her doctorate at the London School of Economics as a Marshall Scholar and is now based in Miami, San Francisco, USA and London. UK.

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By Francis Rodino 

If you don’t truly understand your market, you’re shooting in the dark. Successful businesses thrive on market intelligence—knowing exactly who their customers are, what they want, and how they behave. This guide explores how to gain deeper market insights, outmanoeuvre competitors, and position yourself as the go-to authority in your industry. 

Why Market Leaders Obsess Over Their Audience 

Many businesses think they know their market, but assumptions don’t drive growth—data does. If you’re not constantly refining your understanding of your audience and competitors, you’re not standing still—you’re falling behind. In today’s rapidly changing landscape, staying relevant means evolving your offers, testing new strategies, and adapting to what the market actually wants—not what you assume it wants. A winning strategy starts with a structured, proactive approach to market research and positioning. 

1. Define Your Ideal Customer Avatar

To connect with your market, you need to know exactly who you’re speaking to and communicate in a way that resonates with them. This means going beyond basic demographics and understanding their pain points, desires, and decision-making process. When your message speaks directly to them, they’ll listen. 

Who are your ideal customers? What industry, niche, or profession do they belong to? Consider demographics—age, gender, income, education, and location—but also dig deeper into their psychographics. What do they value? What interests them? What challenges do they face daily? How do they make purchasing decisions? 

The clearer you define your audience, the more precise and effective your marketing becomes. Instead of casting a wide net, you’ll engage the right people who are already looking for your solutions. 

The best way to gain these insights is by speaking directly to your customers. Ask about their biggest challenges, frustrations, and what they wish existed to make their lives easier. Surveys and feedback loops can uncover hidden objections and unmet needs. Online communities—Facebook groups, LinkedIn discussions, Reddit threads—offer unfiltered insights into what your target market is thinking. 

Data analytics further refine your understanding. Look at website traffic, email engagement, and conversion rates. Which pages get the most visits? What offers get the best responses? Which ads perform best? Every interaction is a clue that helps sharpen your messaging and positioning. 

At the core of all successful businesses is one principle: the better you understand your customers, the better you can serve them. When your message aligns perfectly with their needs, they won’t just notice you—they’ll trust you. And in today’s competitive landscape, trust is the foundation of long-term success. 

2. Analyse Your Competitors

If you don’t know your competition inside out, you’re at a disadvantage. Identify your top three competitors and examine their strategies: 

• What promises and claims do they make? 
• How do they engage with their audience? 
• What are their pricing structures? 
• How do they differentiate themselves? 
• Why would your prospects choose them over you? 

Identify gaps in their approach and position your business to dominate where they fall short. Understanding what’s working (and what’s not) in your industry allows you to refine your own strategy and stand out in the marketplace. 

3. Assess Market Awareness and Sophistication

Not all customers are at the same stage of awareness when it comes to your product or service. Some don’t even realise they have a problem, while others are actively comparing options. Your messaging needs to align with their level of awareness: 

• Unaware: They don’t yet recognise the problem. Your job is to educate. 
• Problem-Aware: They know something’s wrong but aren’t sure of the solution. Focus on their pain points. 
• Solution-Aware: They’re researching options. Demonstrate why your solution is the best fit. 
• Product-Aware: They’re comparing competitors. Use social proof, case studies, and clear differentiators. 
• Most Aware: They just need the right offer or incentive to convert. 

Markets also evolve in sophistication. In an unsophisticated market, customers aren’t aware they need your service, so education is crucial. In a new sophisticated market, demand is growing, and thought leadership helps establish authority. In an established market, differentiation becomes essential. In a complex market with heavy competition, strong positioning and storytelling matter most. And in a saturated market, only innovation, brand loyalty, or exclusivity will set you apart. 

By understanding where your market falls on this spectrum, you can craft messages that truly resonate and drive conversions. 

4. Leverage Data to Drive Sustainable Growth

Businesses that capture and analyse data gain a significant competitive advantage. Instead of making decisions based on gut instinct, they use real insights to refine their strategies, optimise operations, and accelerate growth. 

By tracking website traffic, customer engagement, and sales patterns, you can pinpoint where your most valuable customers come from. Are they finding you through organic search, referrals, or paid ads? Understanding these trends allows you to invest in the highest-performing channels. 

Customer engagement metrics highlight what resonates most with your audience. Which content generates the most interest? What messaging leads to conversions? What types of posts spark conversations? Fine-tuning your marketing based on real behaviour ensures your efforts align with what your customers actually care about. 

Conversion rates and customer lifetime value provide deeper insights. How many leads turn into paying customers? What is their long-term value to your business? This data helps refine sales strategies, improve retention, and maximise revenue. 

Competitor analysis and market trends also play a crucial role. Monitoring shifts in customer behaviour and industry changes allows businesses to adapt quickly and seize opportunities before their competitors do. 

The fastest-growing companies aren’t just making better decisions—they’re making data-driven decisions. Knowing what works, what doesn’t, and where to focus ensures you scale with confidence. 

5. Test, Optimise, Repeat

Understanding your market isn’t a one-time task—it’s an ongoing cycle of testing, analysing, and refining. The best businesses don’t rely on assumptions; they continuously gather real data, identify patterns, and adjust their strategies accordingly. 

To truly understand your market, you must test different approaches. This could mean experimenting with pricing models, refining messaging based on customer feedback, or adjusting your services to better meet demand. Pay close attention to how your audience responds—what offers get the most engagement? What objections keep coming up? Where do leads drop off in the buying process? 

Every interaction with your market is an opportunity to learn. Surveys, customer interviews, and A/B testing reveal insights that help fine-tune your approach. Perhaps your ideal customers prefer a different communication style, or they prioritise features you hadn’t considered. The key is to remain adaptable. 

Markets evolve, and so must your strategy. The businesses that thrive are the ones that consistently analyse trends, optimise their offerings, and double down on what works. By treating market understanding as an ongoing process, you’ll stay ahead of the competition and position yourself for sustained success.

About the Author

Francis Rodino is an award-winning expert in sales automation and digital marketing, focused on helping SMEs thrive in the AI-powered era. With over 20 years of experience at the intersection of technology and marketing, Francis has led digital campaigns for global brands like PlayStation, Disney, and the Olympics, and helped Top Gear reach its first 10 million followers on Facebook. Now, as an international speaker and founder of Lead Hero AI, Francis helps SMEs leverage AI tools, marketing automation, and scalable strategies to generate leads, boost profits, and secure lasting success in today’s competitive digital landscape. He is also the author of Leads Machine. 

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By Kyrillos Akritidis 

Venture capital (VC) funding is often the lifeline for startups seeking to grow rapidly and achieve their ambitious goals. However, with global startup investments growing somewhat more strained in recent years, securing funds has become more challenging than ever.  

Startup funding in 2024 did not achieve much of a difference in the YOY perspective, rising only 3% from 2023 ($304B to $314B). But at the same time, the number of funding deals has seen a decline – 6,056 transactions in Q3 2024, which is the lowest it’s been since 2020. This clearly shows that investors have grown a lot more sensitive about where they put their money. 

It’s no longer just about having a brilliant idea; startups must demonstrate good prospects, robust planning, and have a clear value to investors. If you’re a startup founder trying to find your way in a highly competitive landscape, this article may offer you some practical ideas and guide you on a path to success. 

Understand Your Funding Needs and Timeline 

Before you can even think about approaching VC investors, you need to assess whether your startup truly needs external funding at its current stage of development. If the answer is “yes”, then you need to determine precisely how the new funds would be used and establish a timeline for your funding needs.  

Investors appreciate it when projects can offer them a concrete plan and an understanding of where their money would be going. 2024 has seen a sharp rise in startup failure rate in the U.S. (a surge of 60%), as startups went bankrupt even when they had venture backing. Given this backdrop, it makes perfect sense why investors would become a lot more cautious. 

So here’s what you can do. 

First of all, make sure to plan ahead, knowing when you’ll need your next round of funding. This way, you can start discussing things with investors early, reducing the risk of running out of funding at a wrong time. By demonstrating a forward-thinking approach, you will show investors that your startup is well-prepared and has long-term plans, which would paint you in a favorable light. 

Another helpful thing to do is dividing your startup’s growth plans into stages, with funding needs being clearly separated into categories (Seed, Series A, and so on). Set realistic and measurable goals for each stage. You can, for example, seek to expand your user base to a specific number, launch new features, or achieve a particular revenue volume during each of the phases. An important thing here is not to overreach: don’t try to sell investors overblown target figures, because it will severely undermine trust if you fail to reach them. 

Build a Detailed Business Plan and Financial Forecast 

Continuing from our previous point, your business plan is, for all intents and purposes, your face so you can definitely expect investors to scrutinize it forwards and backwards. As such, you need to make it as clear-cut as presentable as can be. 

Make sure to clearly outline your value proposition and explain what your startup is deserving of their money. What problem do you solve, why does it do a better job of it than the competitors, what are the key advantages that you believe will help you find success? All these questions need to be answered so that investors can make their own projections about your future prospects and decide whether or not to believe in you. 

I will also highlight once again that having precise financial projections will be advantageous here and that you should avoid inflated numbers. Transparency is necessary to build credibility: if you show bloated expectations and then fail to live up to them, it risks undermining your position.  

Lastly, a strong plan should also include scenarios for potential challenges and how you plan to deal with them. The business landscape is constantly shifting, so expecting a smooth sailing at all times would be naïve. When things go wrong, you need to be ready to deal with them, and it is best to prepare well in advance. Showing investors that you’ve considered risks and strategies to minimize them will position your project as a well-organized one, boosting your appeal. 

Due Diligence Preparation 

Aside from your business plan, investors will also want to examine all your official documentation in detail. Having grown cautious as they have, nobody wants to risk running into problems with regulators. As such, your startup must be prepared to provide all relevant documentation that pertains to your financial, legal, and operational integrity. This includes financial statements, tax filings, employment records, and so on. 

Contracts with clients, suppliers, and partners must also be clear, up-to-date, and compliant with legal standards to demonstrate operational stability. And if you have any patents and intellectual property, you should ensure that they are properly protected and that your innovations are safe. 

The importance of a well-prepared due diligence package truly can’t be overstated — it signals to potential investors that your company is professional and reliable, building trust and making the investment process that much smoother.  

VC Support is Not Just About the Money 

Having venture support can be helpful in a variety of ways, and not all of it comes down to funding alone. Investors also bring with them industry expertise, previous connections, and the ability to help you with strategic guidance — all things that can be invaluable to a startup that’s freshly starting out. 

In order to harness all of these potential benefits, you need to dig deep and start asking the right questions. Such as: “What additional resources, beyond funding, does your project need to grow?” or “Which of those advantages can this particular investor provide?” 

Whether it’s mentorship, or helping your recruit capable talents into the team, or facilitating networking and connecting you to potential partners, VC support can be a powerful tool for you to wield.

About the Author 

Kyrillos Akritidis is Co-Founder and Managing Director at Schwarzwald Capital, a VC fund dedicated to empowering innovative fintech and creator economy projects. Previously, he headed several fintech companies, held senior positions at banking institutions across Europe, and worked at major international accounting firms like KPMG. Kyrillos is also a Fellow of the Institute of Chartered Accountants in England and Wales (FCA). 

The post How to Secure Venture Capital Funding: A Step-by-Step Guide for Startups  appeared first on The European Business Review.

On his first day back in office, President Donald Trump signed more than 200 of executive actions, of which, one was an executive order proclaiming that the U.S. government will recognize only two sexes, for ending “radical and wasteful” diversity, equity and inclusion programs inside federal agencies.

In 2020, the Supreme Court issued a 6-3 ruling in Bostock v. Clayton County affirming that discrimination against someone because they are LGBTQ is sex discrimination under Title VII of the 1964 Civil Rights Act. Justice Neil Gorsuch. With the “two sexes” new order, Trump’s moves to scrap many diversity, equity and inclusion (DEI) policies inside the federal government”, cutting funding to DEI programmes across all agencies and including a review of offices renamed because of DEI initiatives.

Several large US companies have ended or scaled back their DEI programmes since Trump was elected, including McDonald’s, Walmart and Facebook parent company Meta. Others, like Apple and retailers Target and Costco, publicly defended their existing programmes.

The controversial order asserts a new legal definition of sex that strips federal recognition of the gender identity of some 1.6 million trans and nonbinary Americans, and directly contradicts a number of existing laws and recent court rulings.

The “two sexes” order impact

Sex and gender are not always the same thing. Sex generally refers to a person’s anatomy, whereas gender has to do with a person’s social and personal identity and may differ from their assigned sex at birth.

Trump’s ‘two sexes’ executive order requires that the federal government use the term “sex” instead of “gender,” and directs the State Department and the Department of Homeland Security to “require that government-issued identification documents, including passports, visas, and Global Entry cards, accurately reflect the holder’s sex. “Americans have been able to select “X” on their passports since April 2022 under former President Joe Biden. The new gender order states that it will “defend women’s rights and protect freedom of conscience by using clear and accurate language and policies that recognize women are biologically female, and men are biologically male.”

For decades, feminist legal scholars and women’s rights advocates have opposed efforts to define gender based strictly on biology. Recent state laws that use these definitions to discriminate against transgender people have resulted in invasive and traumatizing efforts to determine who “counts” as a man or as a woman, targeting youth who are even suspected of being transgender because they do not conform to sex stereotypes. The ‘two sexes’ order likewise ignores the existence of intersex people and others with variations in sex characteristics beyond the overly-simplistic definitions endorsed.

Under the Biden Administration, citizens could update their gender markers to reflect their gender identity in a process. In 2022, the Biden Administration rolled out an “X” gender marker for nonbinary, intersex, or gender nonconforming people. Trump’s executive order denies the legal recognition of transgender and nonbinary people, barring them from updating their gender on federal documents, such as passports, visas, and Global Entry cards. The executive order does not impact state policies or most state identification documents, but it could generate issues when it comes to applications where two forms of IDs are necessary, such as applying to loans, employment, or housing.

A peer-reviewed study found that when states pass anti-transgender laws—with policies like bathroom bans, which bar trans students from using the bathroom that matches their gender identity, or challenges to gender marker updates, which make it more difficult for trans people to have their accurate gender on state IDs—suicide attempts among trans and nonbinary youth ages 13 to 17 increased from 7% to 72%.

Some immediate impacts of the gender order will likely be felt by the more than 2,000 transgender people currently held in federal custody. The order specifically calls on the Federal Bureau of Prisons (BOP) and the Department of Homeland Security (DHS) to ignore the guidelines of the Prison Rape Elimination Act (PREA) and enforce a blanket policy forcing transgender women into men’s prisons and detention centers against their will. This puts them at a severely heightened risk of sexual assault and abuse by other incarcerated persons and prison staff. The order also mandates that BOP withdraw critical health care from trans people in federal prison.

The Transgender Scapegoat

Although transgender people make up less than 1% of the adult U.S. population, anti-transgender politicians spent more than $215 million on ads scapegoating trans people and promoting a Project 2025 agenda that threatens to rollback reproductive freedom and punish people for departing from traditional gender roles.

A recent ABC News report found that nearly a third of recent campaign funds — or $21 million, according to the report — for television advertising has been spent on anti-trans messaging from the Trump campaign and various conservative political groups. The independent journalist collective the Bulwark pushed the total even higher — to $40 million poured into anti-trans advertising within the last five weeks. The ads, paid for by the Trump campaign, use a litany of anti-trans coding. Ground Media found that while the negative messaging didn’t change viewers’ minds, it did significantly increase viewers’ negativity about trans and nonbinary people across all demographics. In other words, these ads help to reinforce the idea of maintaining the stigma which reinforces the ongoing culture war against queer and trans people. In this case, even if Harris had won the election, marginalized communities in red states will still be under threat from Trump supporters and from growing legal restrictions on those regions.

Transphobia promotes the idea that trans is a thread to the nuclear family and traditional values, while often hides a broader ideology of exclusion, scarcity and deprivation. Trans people are by far more victims of violence and hate crime than no trans (cisgender) people, yet half of these aggressions are not reported to police.

Gender’s dysphoria controversy

A recent analysis of GP records in the UK has found that the number of children presenting with gender dysphoria in the country has risen 50-fold in a decade. This analysis found that more than 10,000 people under the age of 18 identified as transgender or struggling with their gender identity in the UK. Also, a survey from the U.S. Centers for Disease Control and Prevention found that 3.3% of U.S. high school students identified as transgender in 2023, with another 2.2% identified as questioning.

Gender-affirming care (GAC) is a model of care which includes a spectrum of “medical, surgical, mental health, and non-medical services for transgender and nonbinary people” aimed at affirming and supporting an individual’s gender identity. Gender affirmation is highly individualized, not all trans people seek the same types of gender affirming care or services and some people choose not to use medical services as a part of their transition. An analysis by the Reuters news agency and health technology company Komodo Health found that 282 minors with a prior diagnosis of gender dysphoria underwent mastectomies in 2021. About 4,230 minors received cross-sex hormones and fewer than 1,400 received puberty blockers that year.

In a Gallup poll last year, 61 percent of Americans said they opposed laws banning psychological support, hormonal treatments, and medical surgeries for minors, compared with 36 percent in favour. The Trump administration’s executive order directs agencies to end their reliance on guidance from the World Professional Association for Transgender Health (WPATH), announcing that the US, as a matter of federal policy, will not “fund, sponsor, promote, assist, or support” what are commonly known as gender-affirming care procedures (Protecting Children from Chemical and Surgical Mutilation). Under the President’s order, the Department of Health and Human Services must take “all appropriate actions” to halt gender-affirming care under Medicare, Medicaid and the Affordable Care Act, and publish a review of best practices for promoting the health of youth with gender dysphoria and “other identity-based confusion” within 90 days.

At least 26 US states have passed laws or policies limiting minors’ access to gender-affirming care; 17 states are facing lawsuits challenging their laws/policies limiting youth access to GAC, and 24 states impose professional or legal penalties on health care practitioners providing minors with GAC.

A study published in psychiatrist.com has shown that a significantly higher proportion of patients with gender dysphoria had a primary diagnosis of depressive disorders (82% vs 75.2% in those without gender dysphoria), included anxiety disorders (63.6%), PTSD (28.2%), and neurodevelopmental disorders (27.4%), and there existed a statistically significant difference when compared with non–gender dysphoria patients.

Among hospitalized young people in the United States, 66% of those with a gender dysphoria diagnosis were admitted for suicide attempts or self-harm in 2019, compared to 5% without gender dysphoria, according to a study published in The Lancet Child & Adolescent Health. The study looked at over 2 million instances of young people (6 to 20 years old) hospitalized for any reason and determined how many of those hospitalizations were related to suicide or self-harm attempts, for those with and those without a gender dysphoria diagnosis. Hospitalized young people with gender dysphoria had a higher prevalence of suicide attempts compared to those without gender dysphoria in both 2016 (36% versus 5%) and 2019 (55% versus 4%). Similarly, prevalence of self-harm was higher in hospitalized young people with gender dysphoria in both years (13% versus 1% in 2016 and 15% versus 1% in 2019). This study is the first to use a large nationally representative inpatient database to understand the relationship between gender dysphoria and attempted suicide and self-harm, but talks about the connection between suicide and gender dysphoria are being strongly intensely argued.

Conclusion

Scapegoating LGBTI minorities and Gender roles has become a tactic applied by politicians posing as defenders of so-called “traditional values” to strengthen their base and gain or stay in power. In addition to mobilising certain categories of voters, the exploitation of societal homo/transphobia has proven a convenient way to divert public attention away from government failure to address pressing social issues and rising inequalities and broader attacks under way on human rights and democracy.

Moralist public debate promoted by politicians and opinion-makers is assured to take a prominent role within the public opinion landscape, as it ensures controversy and drags artificially inflicted pressure on people, who feel as if they have to take strong views in a side or in another. Its aim is to create controversy that leads to polarization, to confronted views, and to living under ongoing fear. The influence of the anti-gender movements in politics is increasing. Some politicians are not hiding their affiliation and others may seek convenient alliances because the issues raised are known to attract votes and distract attention from real problems.

For some years now, there have been reports about the expansion of these increasingly organised, transnational and well-funded movements, made-up of religious extremists and ultra-conservative organisations. The anti-gender movements call into question the concept of gender, and whether it is a protected category in the human rights framework, promoting an ultra-conservative – no longer realistic at present – view of the family, sexuality and women’s role in society.

Toxic anti-gender rhetoric is a costly strategy which seeks to maintain stigmatisation and undermines inclusion and social cohesion in general.

The President of the European Commission, when announcing the LGBTIQ Equality Strategy 2020-2025, sent a powerful message in favour of inclusion and diversity by stating that “being yourself is not your ideology. It’s your identity”.

The post “two sexes” – Trump Executive Order: From Gender Dysphoria Controversy to Gender Stigma appeared first on The European Business Review.

By Luke Treglown

AI is transforming how we work and interact, not just through efficiency but by mimicking human qualities like personality and empathy. As we debate whether AI can truly possess humanity, its growing ability to act “human” sparks deeper questions about its role in our lives. Luke Treglown explores the implications of our perceptions of AI’s empathy and personality, challenging us to rethink what makes these traits meaningful in an increasingly AI-driven world.

Introduction

We have been so blinded by stories of AI making us more productive, effective, efficient at work that we have completely missed the bigger disruption that AI is already having: the ability to be “human” at work.

It is difficult to have any conversation at the moment without someone mentioning ChatGPT, AI, and large language models (LLMs). It is simply everywhere and is becoming engrained in how we operate; 93 percent of Gen Z workers admit to using AI every day as a part of their jobs (Independent article from November 2024). But LLMs are not just tools or algorithms that help us answer emails in a softer tone; they are conversational actors, capable of mimicking human qualities like personality and empathy.

Yet we remain somewhat oblivious to the impacts of AI systems that look, feel, and act strikingly human because we are comforted by a belief that they will never truly be “human”. Articles discuss the superhuman talents that will differentiate us from AIs, such as building connections and practicing empathy (Chamorro-Premuzic, 2023; Chamorro-Premuzic & Akhtar, 2023). But what if that is not enough anymore and these are not traits that really make us unique?

The innovations and advancements show no signs of slowing down, with each new release and iteration responding and sounding increasingly human. As a result, there is a growing interest in exactly how “human” our AIs are.

There are two main groups when it comes to evaluating the question of how “human” AIs are becoming. The first group, which we call “the AI evangelists”, argue that we are stepping ever closer to artificial general intelligence and that AIs are showing evidence of human-level outputs and qualities. There is evidence that AIs can display qualities previously thought to be unique to humans, including solving theory-of-mind tasks (Kosinski, 2024), displaying distinct personality traits (Pan & Zeng, 2023), showing empathy (Welivita & Pu, 2024), and engaging in moral reasoning (Kidder et al., 2024).

To be empathetic and display personality, you need to possess the capability to feel emotion or to have motivation, neither of which AIs have.

Then there is the second group, which we will call “the AI sceptics”, who argue that we are getting way too far ahead of ourselves and that these results are all hallucinations or “data leakage”; they only know how to answer these questions properly because they have been trained to do so before. For instance, small variations and changes to classic theory-of-mind tasks stump AI and cause it to no longer be able to answer accurately (Ullman, 2023). Central to this argument is that AIs are precluded from ever being able to possess human-like qualities because they simply are not human. To be empathetic and display personality, you need to possess the capability to feel emotion or to have motivation, neither of which AIs have.

But are these two groups focusing their arguments and evidence on the entirely wrong thing? Rather than trying to resolve, prove, or refute whether AIs genuinely possess human-like qualities, we should instead be looking at the output of their behaviour and how it is being interpreted by users.

This idea comes from Daniel Dennett, who wrote about this concept in his book The Intentional Stance (1987). Dennett was interested in how we can explain or interpret behaviour. What causes something to behave or act the way it does? Dennett argued that there are three ways we can do this:

1. Physical stance. The best way to understand something’s behaviour is by explaining it through physical properties, such as the laws of physics or chemistry (e.g., an apple falls from a tree because of gravity).
2. Design stance. We can explain the way something behaves because it is inherent to the function or design of the thing; its behaviour is best understood by knowing what it is designed to do (e.g., assuming that a clock is designed to tell time).
3. Intentional stance. The behaviour is best explained by assuming that the thing has beliefs, desires, motivations. A dog digs a hole because we assume that it has wants and intends to bury its bone.

For Dennett, the intentional stance can be applied to machines, robots, and AI. He uses a chess-playing program as an example. When it makes a move, we interpret it as wanting to take our pieces and trying to beat us at the game. There is practical and functional value in our thinking that the chess-playing app has motivations and intentions, because that is the way it appears to be behaving.

Importantly, Dennett argues that it is not actually important to focus on whether or not the thing actually has intentions. All that matters is whether assuming that it has intentions is the best way to understand and predict its behaviour. Dennett emphasises the pragmatic value of using the intentional stance with AI. He avoids debates about whether AI “really” has beliefs or desires, focusing instead on whether such attributions help us predict and interact with AI effectively. He compares this to the way we interpret animals; we don’t need to resolve metaphysical questions about whether our dog “really” loves us in order to recognise that this interpretation is useful for understanding its behaviour.

But how does this relate to AI, personality, and empathy?

Taking a view from the intentional stance, I think it is clear that AI absolutely has personality and empathy. In fact, it is more meaningful to interpret its behaviour from the intentional stance, as it has some pretty serious and interesting implications.

AI, Assessments, and Cheating

Ever since we started assessing and evaluating individuals, there has been concern about cheating. Whether it is sneaking notes into the exam room or getting your smarter friend to take the test for you, we display increasing imagination and ingenuity when it comes to trying to get a leg up and improve our scores. Assessments help us to make decisions by accurately evaluating an individual’s competencies, capabilities, or personality. If there are doubts about the legitimacy or genuineness of the responses, then the validity of the assessment is called into question.

Increased access to AI has meant that this topic has resurfaced as a critical topic for assessment providers, academics, and practitioners. AI poses a unique challenge to assessments of comprehension and veridical truths (Hickman et al., 2024) because it is easily able to get to the “right answer”. Similarly, AIs are seemingly able to reason “social truths” and do well in situational judgement tasks that are aimed at assessing attributes like teamwork, ethics, prioritisation skills, and safety behaviour (Borchert et al., 2024; Mittelstadt et al., 2024). Instead, aptitude assessments that prioritise speed of learning will still be relevant, where what differentiates you is not only getting the right answer but also how quickly you can do it.

But what about when there is no “right answer”? How would an AI approach an assessment of personality or behavioural preferences? And would different LLMs and AIs respond to the same assessments consistently?

Taking the intentional stance to AI and personality creates opportunity for academics, practitioners, and assessment providers.

There is growing interest around the idea that LLMs and AI are developing personality. Recent studies suggest that these models display measurable differences across well-established frameworks like the Big Five personality traits (Jiang et al., 2023), HEXACO dimensions (Bodroza et al., 2023), and even the Myers-Briggs Type Indicator (MBTI; Huang et al., 2023). For those interested in the traits that undermine and derail human behaviour, LLMs have also scored on less-savoury traits such as those in the “dark triad” – Machiavellianism, narcissism, and psychopathy (Weber et al., 2024) – raising questions about their ethical implications. Beyond just measuring these traits, personality in LLMs has been linked to their ability to simulate theory-of-mind behaviours, enabling them to anticipate or infer human thoughts and intentions (Tan et al., 2024).

Critics of this research argue that the responses to assessments are not consistent and are susceptible to influence, bias, and hallucinations, meaning that LLMs obviously do not possess personality. For instance, LLMs are biased in personality assessments towards item presentation and picking the first option (Wang et al., 2023; Zheng et al., 2023). Gupta et al. (2024) found that applying assessments to AI is unreliable, as the results differ greatly simply by changing the instruction text and question order.

However, whether AIs possess personality is not the issue or concern for the role of assessments in making accurate, valid, and predictive decisions about people. What matters is that AIs are able to function and respond as if they do have personality. If AIs are going to be used increasingly often by candidates, what will this mean for assessment providers that are looking to spot and combat “faking”? There is already evidence that AIs are better at faking than humans when asked to respond in an ideal fashion to a job description (Philips & Robie, 2024), but that certain assessments are harder to fake than others because the “right answer” is not clear.

Taking the intentional stance to AI and personality creates opportunity for academics, practitioners, and assessment providers. For psychologists, we need to improve our research into AI and personality, exploring how training sets cause LLMs to differ in their “default personalities”, how changing instruction texts and prompt design impacts responses, and whether AI responses converge or diverge from norms we see in human responses. For practitioners, the implications are that they need to have a clear understanding of what they are looking for in a candidate, how the assessments they have chosen will validly assess and evaluate an individual against that, and equip themselves on how different AIs can perform on their assessments and what factors to be on the lookout for.

AI and Empathy

When OpenAI released ChatGPT, one of the use cases that I can imagine they did not expect was the volume of people that would look to their AI for therapy, counselling, and guidance.

AI’s ubiquity has caused a boom in popularity with people seeking out the support of AI for personal issues and mental-health concerns.

AI’s ubiquity has caused a boom in popularity with people seeking out the support of AI for personal issues and mental-health concerns. YouGov found that nearly a third of young people said they would be comfortable with discussing their mental health with an AI, where nearly half say that ease of access and availability are the most appealing things about seeking out an artificial therapist.

It is not surprising. We know that people are more likely to self-disclose, engage in less impression management, and display emotion more intensely and openly when talking to a computer than to another human (Lucas et al., 2014).

What if an AI is able to console, comfort, and advise? If an AI does not have emotion or personality, will it be able to display the empathy and emotional astuteness needed to support people when they are at their most vulnerable?

The data suggests that AI is very good at displaying empathy. Users are seen to project empathetic qualities, such as warmth and having “great bedside manner”, onto AI outputs, even when they know they are talking to an artificial intelligence (Inzlicht et al., 2023). In certain cases, patients are seen to actually prefer AI responses to their questions and rate them more favourably than responses from trained physicians (Ayers et al., 2023). Empathic AIs are also not held back by human qualities like tiredness (Cikara et al., 2014), bias towards their own in-group (Batson et al., 1995), or avoiding empathetic conversations altogether (Cameron et al., 2019).

If we change our perspective on empathy away from the “provider” to the “receiver”, the ability to be empathetic is evaluated by the impact it has. Research into AI and empathy then takes a different shape and purpose. How does the data an AI is trained on impact its ability to respond dynamically to individual questions and concerns? How do different tones of voice, choice of words, ability to explain concepts clearly, and perceived personality have an effect on perceived empathy? As with human-based interventions, what guardrails and safety measures are needed to ensure the safety of, and avoid harm to, the individual?

The reality is that users do not seem to care whether an AI possesses emotion or empathy itself, but rather whether they perceive themselves to have received empathy: do they feel understood, cared for, and heard?

People are increasingly using AI interfaces to seek support and guidance on personal, often vulnerable, issues. Whether an AI possesses the metaphysical properties of empathy or not is the wrong focus. We need instead to be evaluating AI’s empathy from a functional and pragmatic sense, asking how AI’s expressions of emotion and empathy are being received by users and the impact that it is having on their well-being.

One industry where empathic AI will become disruptive is coaching, where AI is being used to augment, facilitate, and democratise coaching to larger groups of people. Empathy is a cornerstone of effective coaching relationships; the ability for the coach and coaches to build rapport is critical for the success of the intervention.

There is a really important role in understanding how empathetic different LLMs are, how they are interpreted, and what impact this has on the person being coached. However, there is very little research looking at how empathetic interactions with AI are perceived and what impact they have on the coaching experience. If different LLMs may vary significantly in their ability to emulate empathy, this will likely impact how they are interpreted, as well as their effectiveness in driving personal and professional growth. For leaders in the coaching industry, understanding the nuances of AI-generated empathy is going to be key to building great tools that enhance, rather than hinder, the deeply human process of self-reflection and development.

Conclusion

It doesn’t matter whether AI truly has personality or empathy. What matters is that users believe that it does. This perception is reshaping industries, from executive coaching, where empathetic AI challenges the role of human rapport, to personality assessments, where AIs can take and fake assessments better than humans can. Shifting our perspective on AI will transform professions, redefine trust and connection, and challenge leaders to navigate the blurred lines between human and artificial traits. This shift is needed because AI that appears empathetic and human-like is no longer a futuristic concept; it’s already influencing how people are assessed, coached, and developed.

About the Author

Dr. Luke Treglown is a psychologist and data scientist specialising in combining AI and people science. As Director of AI at Thomas, he advances AI-driven solutions to enhance workplace connections. Author of 35+ publications on personality, leadership, and resilience, he explores how AI augments interpersonal and intrapersonal dynamics at work.

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The post The Empathy Illusion: Why AI’s Perceived Humanity Matters More Than Its Reality appeared first on The European Business Review.

DeepSeek, a large language model built by China, has become both a sensation as well as a source of concern for the US AI ecosystem, causing the Nasdaq to tumble.

For many managers, DeepSeek adds struggle and turbulence to an already complex technology evolution attached to AI. It is thus rather important to eliminate the noise and sort out the facts from all the current fantasies about the emergence of DeepSeek and its true meaning and consequences for the AI revolution. Here are some crucial elements to make a more informed judgment.

DeepSeek and the AI revolution

1. LLMs are part of an ecosystem

One should always keep in mind that LLMs work on microprocessors and trained datasets. The strength of DeepSeek lies in its strategy of relying on open source to limit its own training costs, to easily access public data, and to leverage Nvidia chips despite US export restrictions.

Its reliance on open source datasets, including foundational models such as LLaMA or Falcon, has among others allowed DeepSeek to develop at a fraction of the cost of proprietary models such as OpenAI’s GPT-4.

However, DeepSeek’s strength is also its weakest link, given its reliance on the generative AI value chain and publicly available datasets. This dependency limits its ability to create a unique competitive advantage and exposes it to the risk of being overtaken by others using the same resources.

2. The new wave of LLM 2.0

The first generation of the LLM battle focused on “more is better” by scaling parameters and tokens. OpenAI’s GPT-4, for instance, uses approximately 175 billion parameters, representing a significant investment in training and computing resources. In this second iteration of LLM, the focus has shifted to quality data and verticalized, domain-specific models.

DeepSeek’s strategy of optimizing a 20-billion-parameter Mixture of Experts (MoE) architecture aligns with this shift, providing major cost efficiencies without sacrificing much in performance. This performance may look remarkable when compared with other high-profile models, such as open source LLaMa or proprietary models such as OpenAI (figure 1).

Notwithstanding some excellence, a deeper look also suggests the following:

1. The cost per token of DeepSeek reflects its likely marginal costs, which is around 5/10 cents per 1,000 tokens or a 10-times improvement versus OpenAI. This cost per token is, however, in the range of other open-source models
2. The LLM 2.0 trend, while demonstrating a better trade-off between cost and performance, does not mean that DeepSeek is an absolute performer. In terms of general knowledge, OpenAI and DeepSeek perform very similarly, but GPT-4o is better at coding tasks and outperforms DeepSeek significantly (75.9 per cent vs. 61.6 per cent) on mathematical reasoning and training. Finally, GPT-4o has multimodal support (69.1 per cent), while DeepSeek lacks this capability entirely, making it cut from a large number of AI use cases based on multimodalities such as content generation (figure1).

Figure 1: Performance benchmarks, DeepSeek version 3.0.

3. A low-cost LLM model limits its marketability

Note that DeepSeek may have deliberately avoided features such as multimodality and mathematics due to time-to-market and cost considerations. Attempting to estimate these cost / time effects, adding multimodal capabilities or improving coding and mathematical reasoning for DeepSeek will add a multiple of four to eight times the current development cost ($20m-$40m) and a significant time investment (12-24 months) (figure 2).

This will significantly offset any cost advantage for DeepSeek, while today it limits its marketability for domains where mathematical reasoning is large (e.g. insurance and capital markets) and multimodal capabilities are a necessity (media, content generation).

 Figure 2: Adding multimodality and upgrading math / coding for DeepSeek.

4. DeepSeek is one of many in the global AI race

DeepSeek is only one piece of the large puzzle in play between China and the US regarding AI dominance. The AI war already has quite a long history. Regarding global semiconductor dynamics, China is exploring alternatives in the global semiconductor value chain. By tapping into massive data pools from China, India, Africa and, potentially, Europe, China could diversify its reliance on US-based chip manufacturers. European players, such as ASML, may also see an opening to compete in this space, offering a potential shift in global semiconductor dynamics.

Regarding global semiconductor dynamics, China is exploring alternatives in the global semiconductor value chain.

In all cases, DeepSeek versus OpenAI or Nvidia is also a symptom of the AI war between China and the US. But this has two consequences. The first is that China represents the largest demand pool of semiconductors in the world – and US companies have long relied on the Chinese market for their success. China, for instance, represents 66 per cent of revenue for Qualcomm, 55 per cent for Texas Instruments, and 35 per cent for Broadcom. By comparison, China accounts for (only) 25 per cent of Nvidia’s revenue.

The second is that retaliation by China has often been based on “dumping” (pricing below marginal cost). While it is difficult to assess the marginal cost of the DeepSeek model, which relies on a clever MOE architecture that uses 20 billion parameters, or 10 per cent of its total size at the time, we have already mentioned that the true cost per token of DeepSeek is likely ten times cheaper than fully fledged models like OpenAI, which means that current pricing is still above marginal cost and can not be challenged by the World Trade Organization. Still, China can only continue this if it relies on open source data, models, and the work of others, as DeepSeek is intending to do.

5. AI and the war for talent

The fact that Chinese engineers can match US counterparts is also known – and skills are the main drivers of LLM competition. Let’s remember the Eric Schmidt conversation a few years back, where he said: “Most Americans assume that their country’s lead in advanced technologies is unassailable. … China is already a full-spectrum peer competitor in terms of both commercial and national-security AI applications. China is not just trying to master AI; it is mastering AI.”

China’s AI giants, Baidu, Alibaba, and Tencent (BAT), have, in fact, demonstrated a head start in artificial intelligence. Despite claims of lagging behind US companies, BAT’s AI initiatives rival and often mirror those of their US counterparts, such as OpenAI and Google. Baidu’s early AI investments and projects like Apollo have redefined the auto industry, while Alibaba’s Tmall Genie competes with Amazon Echo, and Tencent’s WeChat-integrated smart devices rival Apple’s ecosystem.

BAT’s global ambitions are further hindered by limited access to foreign language data compared to US counterparts like OpenAI and Google.

However, as with DeepSeek, BAT’s performance is heavily reliant on foreign semiconductor supply chains. BAT’s global ambitions are further hindered by limited access to foreign language data compared to US counterparts like OpenAI and Google. This gap has driven BAT to pursue international partnerships to localize their technologies, but with the inherent risk of being sandboxed or outright rejected.

6. The long road ahead for LLMs

Despite impressive advancements, LLMs remain far from meeting the performance requirements of many sectors, such as financial services, precision manufacturing, and healthcare. Financial firms, for instance, require models with precise, real-time analysis capabilities, while manufacturers need robust AI for highly technical use cases.

The battle is just beginning, and models will need to be significantly upgraded to address enterprise-specific requirements beyond customer service and content generation. This opens up opportunities for proprietary players such as OpenAI, as well as emerging competitors such as Mistral AI, which aims to focus on specialised, enterprise-grade solutions.

A key insight comes from the SWE bench (software engineering): at 50 per cent verified accuracy, DeepSeek falls short for enterprise-grade software engineering tasks. This includes issues such as limited ability to generate correct, efficient and production-ready code, as well as challenges in understanding edge cases or debugging complex, real-world software problems.

Finally, even with strong benchmarks, most enterprise use cases demand factual accuracy and consistency, but LLMs often hallucinate, and DeepSeek is no exception, meaning that even with nearly 90 per cent MMLU performance, DeepSeek cannot guarantee correctness in high-stakes domains such as law or medicine. In regulated industries, hallucinated output could lead to compliance violations, legal liability, or even harm.

7. Open-source and proprietary models: A coexistence model

The open-source–versus–proprietary battle is not new in high-tech industries. Historical patterns – such as Linux in servers, ARM in mobile processors, or the GSM standard in telecom – suggest that open-source solutions will often coexist with proprietary models.

Linux fundamentally disrupted the proprietary server market but, rather than eliminating proprietary players, it expanded the size of the market.

The overall size of the server market grew significantly as Linux enabled widespread adoption of web hosting, cloud computing, and enterprise applications.

The adoption of Linux dramatically reduced costs for enterprises and start-ups, making server-based applications affordable for smaller businesses. The overall size of the server market grew significantly as Linux enabled widespread adoption of web hosting, cloud computing, and enterprise applications. In turn, proprietary systems such as Windows Server still exist and thrive in certain segments (e.g., enterprises that value integration with Microsoft’s ecosystem). Companies such as Red Hat have built profitable business models around open source Linux, providing enterprise support, consulting, and security patches.

Similarly, the adoption of GSM as an open standard in telecommunications was a critical factor in the explosive growth of the mobile market in both developed and emerging markets, significantly increasing the size of the global market.

While proprietary technologies such as CDMA initially competed with GSM, they eventually became niche players. Proprietary technologies struggled unless they offered clear advantages (e.g. better coverage or speed in certain scenarios).

As a result, the market can see explosive growth from open source, and proprietary players can still win if they segment the market and have a sufficiently attractive value proposition. Competition, in turn, leads to a significant acceleration of the market based on the attractiveness of cost reductions and quality improvements, to the benefit of all players.

DeepSeek’s reliance on open source tools such as PyTorch and its low-cost architecture are in line with this trend, but players such as OpenAI and Mistral AI are likely to focus on high-quality, domain-specific models.

8. Can Nvidia be the biggest beneficiary of AI growth, after all ?

The rise of open-source AI, including DeepSeek, has significant implications for Nvidia:

• Without open source: Nvidia would remain reliant on a few major players, with slower market expansion.
• With open source: Open-source accelerates AI adoption, creating explosive demand for Nvidia GPUs across a broader customer base. Open-source AI fosters decentralization, driving GPU demand among smaller players, start-ups, and emerging markets.

Nvidia is already adapting to this landscape by broadening its offerings. Affordable GPUs like the Jetson Orin Nano and scalable cloud services like Nvidia AI Enterprise cater to cost-sensitive developers and enterprises. Furthermore, Nvidia actively supports open-source initiatives, including PyTorch and NVDLA, to ensure that its hardware remains central to the AI ecosystem. Emerging markets in Asia, Africa, and Latin America – where open-source adoption will likely dominate – present a significant growth opportunity for Nvidia. These moves solidify Nvidia’s role as the foundational provider of AI for the future.

Is DeepSeek changing the CEO journey ?

The above has demonstrated that DeepSeek is part of LLM 2.0, leveraging the open source boost possibly in a context of an AI race between the US and China, and China’s strategic necessity to diversify sources of reliance in the AI ecosystem. More broadly, it demonstrates that open source will likely be part of the outcome.

In these circumstances, what are the key action points for a CEO?

1. Accelerate AI adoption

1. Affordable and accessible AI: The emergence of open-source models like DeepSeek and LLaMA, combined with increasingly affordable infrastructure costs, is democratizing AI. Enterprises can leverage these advancements to rapidly scale AI capabilities without incurring exorbitant expenses.
2. Peer adoption drives network effects: The reduced barriers to entry foster widespread adoption across industries, creating momentum and enabling businesses to extract value from AI faster than ever before.
3. Opportunity for business innovation: The balance between open-source and proprietary models allows enterprises to innovate while managing costs, ensuring that AI investments align with specific operational goals and industry needs.

Action point: Prioritize adopting AI to accelerate operational efficiencies, improve customer engagement, and gain a competitive edge in your sector. Look at open-source solutions to experiment and iterate quickly before scaling.

2. Infrastructure plays will dominate: align with key ecosystems

1. 1. Ecosystem centralization: Despite the rise of open source, the AI infrastructure market will likely remain concentrated in a few dominant players like Nvidia, OpenAI, Microsoft, and Google. These companies will continue to drive AI development through GPUs, APIs, and cloud services.
   2. Integration is key: Enterprises must align their strategies with the leading ecosystems to access state-of-the-art capabilities while minimizing friction. Building within these ecosystems ensures compatibility, scalability, and support for future innovations.

Action point: Integrate into dominant AI ecosystems early by partnering with key players, leveraging their APIs, cloud services, and hardware platforms. Focus on interoperability and modularity to avoid vendor lock-in while ensuring access to cutting-edge tools.

3. Mitigate risks: Navigate regulatory, political, and compliance hurdles

• Regulatory uncertainty: Generative AI faces increasing scrutiny, with potential risks around data privacy, ethical concerns, and bias. Governments worldwide are racing to regulate AI, introducing compliance complexities for enterprises.
• Geopolitical risks: AI is deeply intertwined with global political tensions, particularly between the US and China. Enterprises must be cautious of supply chain dependencies, export restrictions, and geopolitical shifts.
• Hallucination and liability risks: Generative AI models often produce “hallucinated” outputs, raising risks for regulated industries like healthcare, banking, and legal services.

Action point: Build robust risk management frameworks by:

• Establishing strong governance policies for AI use.
• Ensuring compliance with relevant regulations (e.g., GDPR, HIPAA).
• Diversifying supply chains to reduce dependency on any single region or vendor.
• Designing contingency plans to respond to regulatory shifts or model failures.

Final message

AI adoption is no longer optional; it’s a necessity. The convergence of open-source accessibility, infrastructure dominance, and regulatory scrutiny creates a dynamic ecosystem. Enterprises that proactively embrace AI while managing risks will not only survive but thrive. The key is moving fast, collaborating smartly, and acting cautiously where necessary to capitalize on the opportunities AI offers, while safeguarding against its risks.

About the Author 

Jacques Bughin is the CEO of MachaonAdvisory and a former professor of Management. He retired from McKinsey as a senior partner and director of the McKinsey Global Institute. He advises Antler and Fortino Capital, two major VC /PE firms, and serves on the board of several companies.

The post Making Sense of DeepSeek appeared first on The European Business Review.

By Fernanda Arreola and David Jaidan

The accessibility of new tools for improving our decision-making based on data seems to be a promising way to gain insights. From the choice of our holiday itinerary to the ranking schools for our next master’s degree, we seem open to the idea that data processing engines like ChatGPT, Gemini, and others, can help us make decisions. But how far are we ready to go?

Decisions that are guided by our intuition

Today, there is an ongoing debate around the question of if AI can replace human intuition. Intuition is “the ability to understand or know something immediately based on feelings rather than facts.” Intuition is something that AI is not since AI today cannot reproduce feelings.

Intuition can play a significant role in decision-making, especially when faced with complex or time-sensitive situations. According to research, up to 85 percent of CEOs make critical decisions using intuition. This intuitive decision-making process involves accessing emotional and sensory information acquired through associated learning and stored in long-term memory, which is then unconsciously applied to form judgments or decisions.

Intuitive decision-making is particularly effective when it draws on our expertise if developed through years of experience in a specific domain.

Intuitive decision-making is particularly effective when it draws on our expertise if developed through years of experience in a specific domain. Phillips, Klein, and Sieck discuss that the key to improving intuitive decision-making skills is to strengthen the knowledge base within one’s job context through deliberate, focused practice. This approach allows individuals to develop what some researchers call “unconscious expertise,” which enables them to quickly recognize patterns and make effective decisions in their area of specialization. The Recognition-Primed Decision (RPD) model developed by Klein suggests that experts make decisions by recognizing patterns from past experiences and quickly simulating how an option would perform.

Intuition is therefore based on a recollection of information stored in our long-term memory, which is influenced by nonrational perceptions including feelings and emotions. Intuition can be thought of as insight that arises spontaneously without conscious reasoning. Research by Dijksterhuis and colleagues in 2006 supported the value of intuition, particularly for complex decisions. Their “deliberation without attention” hypothesis suggested that while conscious thought is beneficial for simple choices, it can be detrimental when dealing with more intricate matters, such as buying a house.

In both residential and commercial real estate, intuition is vital. Imagine walking into a house and immediately feeling that it is where your family should be, the way sunlight lights up the rooms, the laughter you can almost hear in the hallways. Or imagine stepping into a potential store and feeling that this is the perfect spot for your business, already seeing customers being drawn to your door. The decision to buy a new house or invest in a business property is not just a transaction, it is a turning point that can shape our future.

The rise of AI in real estate

Artificial intelligence has made significant inroads into the real estate industry, revolutionizing how properties are valued, marketed, and sold. According to a report by McKinsey, AI has the potential to generate up to $180 billion in revenue for the real estate industry in the future. AI-powered platforms can analyze vast amounts of data, including property characteristics, historical sales data, market trends, and neighborhood information, to provide accurate valuations and personalized recommendations.

For homebuyers and business owners, two features are particularly interesting:

1. Personalized Recommendations: By entering your preferences like location, price, and specific amenities, AI creates a list of properties that match what you want, showing you options you might not have thought of.
2. Predictive Analytics: AI predicts market trends and property value growth, helping you make financial decisions. It can show which neighborhoods are improving, which could be good for an investment.

But AI has its limits. It cannot understand the emotional feeling of a potential home or the special character of a neighborhood. It might miss things that cannot be measured but still matter for a person’s happiness or a business’s success.

Balancing AI and intuition

AI-powered platforms can analyze vast amounts of data, including property characteristics, historical sales data, market trends, and neighborhood information, to provide accurate valuations and personalized recommendations.

As discussed, AI gives useful data tools, but it cannot replace emotional intelligence, personal connection, and intuition. Our instincts help us feel if a property is right, and our past experiences allow us to envision if a property matches our lifestyle. This is similar to a business location; it is our imagination that will fill the gaps of an empty room with the possibility of making it a showroom for our product or service. Therefore, relying too much on AI might make us miss out on properties that do not fit the algorithm where we have input our basic choices, which in the end is the perfect location when we visit in person and imagine how the attributes can adapt to the real place.

AI hybrid approach

The early conclusion is that, for real estate, AI is far from being capable of overtaking humans for decision-making. But it can make our choices more powerful if we put together a hybrid approach that makes the best of both worlds interact. In the context of real estate, this hybrid approach could involve:

1. Using AI tools for initial property screening and market analysis.
2. Leveraging intuition during property visits.
3. Using AI to tune up the final criteria for the search, being able for instance, to compare rationally five different property runner-ups.
4. Consulting with human real estate professionals who can provide local expertise and emotional support throughout the process.
5. Making sure we consider the emotional and logical options and their impact on biases; this will make a more informed and objective decision.
6. Finally, before deciding, we should never assume that the mix of intuition and AI will render the perfect result. Instead, we should understand that every business decision, regardless of how well-informed it is, has risks associated with factors that are outside our control, our current knowledge, and any technological expertise.

Considering this final point, acknowledging the potential risks is crucial for real estate and business decisions. This is because not only ourselves but also AI can carry over biases from its training data, which can lead to inaccurate recommendations, as shown by some well-known examples of algorithm failures. Plus, since AI relies on existing data, it might miss the subtle, changing dynamics within communities. The weak point of AI is that it is fully based on data, and if this data is not precisely updated, it may not match reality. The further this data drifts from what is real, the more likely AI is to make mistakes. This is why safeguards are important, and the best way is to use AI as a tool to help make decisions, being a key principle to remember that AI is there to help us make decisions and not to make them for us.

The future of AI in real estate

For real estate, AI is far from being capable of overtaking humans for decision-making. But it can make our choices more powerful if we put together a hybrid approach that makes the best of both worlds interact.

As the real estate industry continues to evolve, the integration of AI and human intuition presents a powerful combination for homebuyers. Daniel Kahneman, who won a Nobel Prize in economics for his work on human judgment and decision-
making, has proposed that we can mobilize two different thought systems: System 1 is fast and intuitive; System 2 is slower and relies on reasoning. The fast system, he holds, is more prone to error. It has its place: it may increase the chance of survival by enabling us to anticipate serious threats and recognize promising opportunities. But the slower thought system, by engaging critical thinking and analysis, is less susceptible to producing bad decisions. The key contribution of AI is, therefore, to make the second system faster, so that it can match the speed of the intuition-based one, reducing the likelihood of mistakes.

Many people in real estate are still unsure about AI’s impact. Their concerns are understandable, but it is important to remember that AI is always improving. While some may not be convinced now, they might change their minds as the technology gets better.

Conclusion

To conclude, while AI offers data-driven insights and efficiency, human intuition provides the emotional intelligence and contextual understanding necessary for such a significant life decision. By leveraging both AI tools and their instincts, homebuyers and business owners can make more informed and satisfying decisions.

About the Authors

Fernanda Arreola is a Professor of Strategy, Innovation, and Entrepreneurship at ESSCA. Her research interests focus on service innovation, governance, and social entrepreneurship. Fernanda has held numerous managerial posts and possesses a range of international academic and professional experiences.

David Jaidan is the founder of Minerva View, a location intelligence SaaS company delivering strategic insights. Operating at the intersection of technology, business, and research, he made significant contributions to privacy-aware and explainable AI at Scalian, a leading European consulting firm. His climate work at Météo France was recognized by the IPCC.

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The convergence of Web3 and AI, two of the most promising technologies of our time, has sparked a compelling narrative. This fusion, with its groundbreaking potential, has ignited substantial discourse. Whether it signifies true innovation or is merely marketing-driven hype is at the forefront of this narrative. The interest it has generated across various sectors is undeniable. However, the current conversation, while speculative, is shrouded in uncertainty. The innovative potential of both Web3 and AI is clear, but their integration’s practical application and scalability are still in their infancy. This leads many to wonder whether this hype will translate into real-world impact.

The Promise of WEB3 and AI

Web3’s decentralised architecture offers a unique environment for AI systems to function with greater transparency, security, and autonomy. Theoretically, the decentralised structure of blockchain can distribute ownership of data and computational resources, thereby levelling the playing field for AI. For instance, blockchain-based data marketplaces could empower users to share their data directly with AI systems, bypassing traditional intermediaries and ensuring that individuals maintain control over their privacy and compensation.

Web3’s decentralised architecture offers a unique environment for AI systems to function with greater transparency, security, and autonomy.

In decentralised finance (DeFi), we already observe AI being employed to optimise trading strategies and monitor risks in real time, leveraging the transparency and security that Web3 provides. Smart contracts—another innovative aspect of Web3—have the potential to enable AI systems to autonomously execute tasks within decentralised applications (dApps), eliminating the need for central authorities. This dynamic could enhance efficiency, reduce costs, and foster trust among participants in various sectors, from finance to healthcare.

However, despite these promising developments, most discussions surrounding decentralised AI remain theoretical. The necessary infrastructure for decentralised AI is still underdeveloped, and many current Web3 applications are confined to niche or experimental categories. This gap between potential and practical implementation raises questions about the technology’s readiness to meet real-world demands.

Challenges in Merging WEB3 and AI

The convergence of Web3 and AI is not without its challenges. The foremost among these is the underdeveloped infrastructure. The concept of fully autonomous AI-driven Decentralized Autonomous Organizations (DAOs) is captivating. Still, current technology struggles to manage the complexities that real-world AI applications would demand in a decentralised context. The infrastructure supporting these technologies must evolve significantly to facilitate their synergistic relationship effectively.

Data transparency and ownership present critical hurdles as well. AI models rely on extensive datasets to function effectively, yet the origins of these datasets are often unclear. This lack of transparency leads to significant issues surrounding quality, bias, and ethical considerations. Simultaneously, a handful of tech giants control most global data, creating monopolistic conditions that stifle competition and innovation. Smaller organisations are disadvantaged, struggling to access the data needed to develop AI solutions that could transform industries.

Privacy issues further complicate the landscape. Many AI systems are built on data collected without user consent, violating privacy regulations and raising ethical concerns. Moreover, the data used in AI training may be incomplete, biased, or not representative of diverse populations, resulting in suboptimal outcomes and perpetuating existing inequalities.

Many AI systems are built on data collected without user consent, violating privacy regulations and raising ethical concerns.

Scalability is another critical concern. While blockchain technology promises transparency and decentralisation, it often grapples with scalability issues. AI systems necessitate the ability to process vast amounts of data in real time, a requirement that current blockchain solutions struggle to meet due to their limited transaction throughput. The intricate balance between maintaining decentralisation and achieving the required speed and efficiency for AI applications presents a formidable challenge.

Opportunities for Improving the AI Data Market

To overcome these challenges that AI and Web3 face, it is crucial to fix the broken AI data market first. Centralised data control has resulted in a lack of transparency, the availability of low-quality datasets, and high acquisition costs, all hindering AI development. One promising solution is the creation of decentralised data marketplaces using blockchain technology. These exchanges can incentivise individuals and organisations to share their data by offering financial rewards through tokenisation. Even with today’s blockchain technologies, such marketplaces can ensure that data is shared securely and transparently and empower users to maintain control over how their data is utilised.

Transparency and trust within these marketplaces can be enhanced by establishing robust data provenance systems. By tracking the origins, ownership, and processing history of data, these systems can prevent AI models from relying on opaque or biased datasets, thereby ensuring data transparency and improving the quality and fairness of AI systems. “Federal learning” and “differential privacy” are two ways that make it possible to share just enough and only the most relevant information through a decentralised network to train AI models without comprising user privacy. These approaches allow AI to learn from distributed data sources while protecting sensitive information. Such an environment fosters stakeholder collaboration, encourages innovation, and ultimately leads to better AI outcomes that benefit society.

The Role of Blockchain: A Solution or a Complication?

While blockchain technology undoubtedly offers potential solutions to some of AI’s most pressing challenges—such as data transparency, ownership, and security—it is essential to recognise that it is not a catch-all remedy. Blockchain faces its own challenges, including scalability, energy consumption, and legal uncertainties.

To maximise blockchain’s benefits for AI, we must explore solutions such as Layer 2 scaling and sidechains, which can overcome scalability issues. These technologies facilitate off-chain transactions and data processing, reducing the burden on the primary blockchain and enabling faster, more cost-effective solutions. Moving blockchain to more energy-efficient consensus mechanisms such as proof-of-stake can also help mitigate the environmental impact of combining AI and blockchain technologies.

To maximise blockchain’s benefits for AI, we must explore solutions such as Layer 2 scaling and sidechains, which can overcome scalability issues.

Hybrid models that leverage blockchain for security and data integrity while keeping most data processing off-chain can serve as a pragmatic compromise. Such models can effectively balance the need for decentralisation with the operational demands of AI systems. Furthermore, cross-chain interoperability will enable decentralised AI systems to operate seamlessly across multiple blockchain networks, fostering a more integrated ecosystem.

Data Ownership in the Age of AI

Data ownership in the age of AI presents a complex and evolving issue. Technically and legally speaking, individuals should retain ownership of their data. Yet, very often, these days, sharing data with companies often leads to losing and relinquishing control. This centralised governance creates a power imbalance, as companies wield extensive rights over user data through opaque terms of service agreements that many individuals may need help understanding.

The evolving issue of data ownership in the age of AI underscores the need for further evolution in data governance frameworks. Governments are beginning to intervene with regulations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), which grant individuals certain rights regarding their data. However, these regulations often need to confer full ownership and may be difficult to enforce. Besides, the terms are frequently incomprehensible for many users, assuming these users even want to read them in the first place. This situation highlights the need for further evolution in data governance frameworks to ensure individuals can exercise meaningful control over their data.

One potential solution is developing community-owned data networks or Data DAOs, in which communities collectively pool their data and negotiate its use. In this model, data governance becomes a communal effort, empowering individuals to make informed decisions about how their data is utilised while ensuring fair compensation and ethical AI development.

It is also possible to create tokenised data markets, where data is assigned a unique value and traded transparently – imagine you can trace the use of the personal data you have given away. This approach fosters a decentralised, trust-based economy surrounding data, allowing individuals to exert greater control over how their data is used in AI systems. Additionally, privacy-preserving AI models can enable AI to train on localised data without centralising it, offering a viable pathway for balancing innovation with data sovereignty.

The Symbiotic Relationship Between WEB3 and AI

AI and Web3 are mutually dependent technologies. AI relies on Web3’s decentralised infrastructure to navigate data ownership, integrity, and privacy challenges. Conversely, Web3 requires AI to address its complexities, scalability challenges, and under-developed user experiences. By working in concert, these technologies can accelerate their adoption and unlock new opportunities across various sectors.

The “killer application” or definitive moment that showcases the synergy between Web3 and AI may be just a few years away. A breakthrough use case—such as decentralised AI marketplaces or AI-enhanced finance platforms—could demonstrate their combined potential and provide concrete evidence that these technologies extend beyond mere hype. Such applications would not only illustrate the practical benefits of merging Web3 and AI but could also pave the way for broader adoption and innovation. By addressing the hurdles and leveraging the unique strengths of Web3 and AI, we can pave the way for a future that embraces innovation while ensuring equitable access and data sovereignty for all. The journey towards realising this vision is only beginning, but the possibilities are limitless.

About the Authors

Andrea Maria Cosentino, MSc, is an Adjunct Professor of Digital Transformation and Entrepreneurship at Hult International Business School and ESCP Business School. Andrea is the founder and CEO of Impact Fundry, a venture capital studio and strategic consulting boutique that accelerates start-ups, SMEs and corporate enterprises to enable growth and sustainable value creation. He lectures at various universities worldwide with publications in LSE Tech Review, World Economic Forum, and MIT Tech Review. He contributed to the book The Internet of Value published by the Blockchain Center at UCL.

Dr. Terence Tse is a globally recognized educator, author, and speaker. He is a Professor of Finance at Hult International Business School and co-founder of Nexus FrontierTech, an AI company. He is also a visiting professor at ESCP Business School and Cotrugli Business School. His latest co-authored book, The Great Remobilization: Strategies and Designs for a Smarter Global Future, was nominated for the 2023 Thinkers50 Strategy Award. Terence co-authored two Amazon bestsellers, The AI Republic and Understanding How the Future Unfolds. The DRIVE framework from the latter earned a nomination for the Thinkers50’s CK Prahalad Breakthrough Idea Award. Terence also authored Corporate Finance: The Basics, now in its second edition.

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A Global Research Initiative

MIT CISR, renowned globally for its cutting-edge research, has long been at the forefront of studying how executives can maximize the value of digitization within their ecosystems. The Center’s distinctive approach leverages real-world data from numerous organizations, offering unparalleled insights into what drives performance and value creation.

• By completing the survey, participants will contribute to critical research that explores enterprise AI maturity, platform business models, cultural transformation, real-time business operations, and effective change management practices.
• The findings will provide leaders with evidence-based strategies to stay competitive in the ever-evolving digital landscape.

Take the Survey Here!

Real-Time Business: The Next Competitive Step

A central focus of the survey is the concept of becoming a real-time business (RTB). RTBs execute key processes instantaneously using automated operations, AI, and data-driven decisions supported by governance and risk management. As companies strive to adapt, the survey seeks to identify best practices for embracing real-time business models. Insights from participants will provide a roadmap for organizations to transition toward more agile and efficient operations.

Learn more about RTBs here.

About the Survey

The survey, designed for individuals familiar with their organization’s digital strategy, takes just 20–25 minutes to complete. It addresses essential questions, such as:

• How can traditional companies transition to platform-based business models?
• What are the best practices for leveraging AI to drive business value?
• How can organizations shift focus from traditional industries to customer-centric domains like mobility, wellness, and energy efficiency?
• What role should boards and top management play in overseeing digital and AI initiatives?
• How can companies organize their technical resources to align with a more digital and AI-oriented future?
• What new job opportunities and business models emerge as AI and automation reshape the workplace?

Who Should Participate?

This survey is designed for professionals who are deeply familiar with their organization’s digital strategy and who hold the insights necessary to shape the future of their enterprises.

Complete the Survey Today!

What’s in It for You?

Participants will gain access to advanced research findings, offering unparalleled guidance on navigating the complexities of digital transformation. The survey results will equip leaders with practical strategies to drive innovation, strengthen governance, and achieve sustainable growth in an AI-driven economy.

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COP29 underscored the gap between climate commitments and tangible actions, reflecting both progress and significant challenges. What is the critical role of business in bridging this gap and why are some companies leading in this area, and why are some stuck on the sustainability journey?  

The Stakes Post-COP29 

A pivotal agreement was reached on the new collective quantified goal (NCQG) for climate finance, targeting $300 billion annually from developed countries by 2035 and an aspirational $1.3 trillion in total annual financing¹. The sum falls far short of what is needed, sparking walkouts and criticism from developing nations and climate advocates.  

Technical rules for international carbon markets were negotiated, a decade-long milestone that can facilitate cost-effective decarbonisation. Yet, calls to strengthen ambitions on fossil fuel transitions and national emissions targets remain unmet, leaving many stakeholders dissatisfied².  

These outcomes reinforce the critical role of businesses in bridging this gap. Business  possesses unique capacities to lead on sustainability or exacerbate global challenges. Financial institutions  are increasingly aligning portfolios with net-zero goals, but  systemic action is needed to unlock private capital, enhance adaptation finance, and mobilise meaningful resources for vulnerable regions. As the spotlight shifts to COP30 in Brazil, business  must seize this moment to drive the ambition and action needed for a just, sustainable transition.  

Heroes vs Villains 

In the fight for a sustainable future, businesses are cast as either heroes or villains. The heroes are bold and innovative, driving measurable change. They lead with ambition, making science-based commitments and embedding sustainability into every aspect of their operations. They  champion transparency, adopt circular business models, and embrace renewable energy, cutting emissions and waste with measurable impact. Heroes are not just adapting – they are setting the pace for others to follow.  

Villains, conversely cling to outdated, unsustainable practices. They greenwash their efforts, using clever marketing to mask minimal or non-existent progress. They resist change, lobby against climate regulations, and prioritise short-term profits over long-term survival. These companies contribute disproportionately to environmental degradation while undermining the credibility of genuine efforts. 

The line between the two lies in authenticity and action. Are you driving innovation or delaying progress? In an era when stakeholders demand accountability, only heroes will thrive. 

The Business Imperative for Sustainability 

Sustainability is not just the right thing to do – it’s  the smart thing. Investors are funnelling trillions into green assets, with ESG investments projected to exceed $40 trillion by 2030³,⁴. Consumers are demanding accountability, with two thirds willing to pay more for sustainable products in the four major European economies⁵. Regulatory pressures are tightening, pushing businesses to act or face penalties. 

Companies that embrace sustainability future proof their businesses by reducing risks, unlocking innovation, and attracting loyalty from stakeholders. Sustainability is not optional – it’s a non-negotiable strategy for long-term success.  

Showcasing the Heroes 

In the race for sustainability, some companies are setting the gold standard: 

• Patagonia: A trailblazer in circular economy practices, has repaired over 130,000 garments through its Worn Wear programme⁶, reducing waste and encouraging a culture of reuse. Beyond products, the company donates 1% of sales to environmental causes and has transferred ownership to a trust dedicated to fighting climate change⁷. 
• Ørsted: Once one of Europe’s largest coal users, Ørsted transformed into a global leader in renewable energy, cutting carbon emissions by 87% since 2006⁸. Now, 90% of its energy output comes from wind and solar, demonstrating how legacy industries can pivot to a sustainable future⁹.  
• Unilever: With its ambitious Sustainable Living Plan, Unilever reduced CO₂ emissions from energy by 77% since 2008¹⁰, while innovating products like plant-based foods under its Hellmann’s and Magnum brands¹¹ to tackle climate and health challenges¹², and reducing food waste¹³.  

These heroes prove that bold action and measurable outcomes are possible – and profitable. They inspire businesses worldwide to rethink what leadership looks like in a sustainable era.  

Exposing the Villains 

Some are falling conspicuously behind in being more sustainable Take greenwashing – a practice where organisations exaggerate or falsify environmental claims. A sunscreen brand has been criticised for misleadingly advertising its products as “reef-safe”¹⁴ despite containing harmful chemicals that damage coral reefs ¹⁵. Buzzwords like “eco-friendly” are often used without substantiated evidence, misleading environmentally conscious consumers.  

A beverage giant has faced scrutiny for its role in plastic pollution. Despite announcing ambitious sustainability goals, including a pledge to collect and recycle one bottle or can for each sold by 2030 (now accused of silently quitting it¹⁶), critics argue that the company continues to generate excessive plastic waste, maintaining its position as one of the world’s largest polluters¹⁷. In addition, the company has faced criticism for its water practices, such as water inefficient overuse¹⁸ and exerting control over vital aquifers in certain regions, sparking allegations of depriving local communities of essential water resources¹⁹.Not to mention other controversies around public health^20,21. Despite efforts to address these issues through sustainability initiatives, past reputational damage erodes trust in the company’s future commitments.  

These examples illustrate common issues such as lack of transparency, unfulfilled promises, and reliance on unsustainable materials. Both cases provide an opportunity to encourage practices like greater accountability and prioritisation of verifiable, sustainable alternatives.  

The solution? Genuine accountability: aligning targets with measurable outcomes, prioritising sustainable materials, and embracing circular economy principles. Companies must shift from quick fixes to systemic change, transforming their operations to  leave a lighter footprint. When done right, the rewards are clear – enhanced reputation, resilience, and long-term profitability.  

Key Factors for Success 

Sustainability champions share key traits. Leadership commitment sets the tone, with CEOs and boards prioritising environmental goals. These organisations embed sustainability into core business strategies, ensuring it drives innovation and value creation. Transparent reporting builds trust, demonstrating measurable progress and accountability. Collaboration is critical – working with supply chains, communities, and NGOs amplifies impact.  

Business leaders can emulate these practices by setting ambitious, measurable goals and aligning them with their mission. Regularly report on progress to build credibility and engage stakeholders. Foster a culture of innovation and partnership to tackle complex challenges. Finally, to lead by example, making sustainability a visible, non-negotiable priority.  

A Call to Action 

The time for hesitation is over. Businesses hold the power to rewrite the sustainability story – not as villains but as  heroes. By embracing innovation, transparency, and collaboration, organisations can lead the charge towards a thriving, resilient planet.   

The tools and strategies exist – what is needed now is courage and commitment. Do you want to be a hero or villain?

About the Author

Giovani Palafox-Alcantar is the Head of Executive Education and a Research Associate on Sustainable Cooling Production Networks at the Smith School of Enterprise and the Environment, University of Oxford, working with organisations globally on sustainability and environmental education. 

References

1. What was agreed at COP29? – House of Commons Library

2. COP29 outcomes: balancing progress and challenges on the road to climate action – United Nations Environment – Finance Initiative

3. Global ESG assets predicted to hit $40 trillion by 2030, despite challenging environment, forecasts Bloomberg Intelligence | Press | Bloomberg LP

4. ESG AUM set to top $40 trillion by 2030, anchor capital markets | Insights | Bloomberg Professional Services

5. Europe’s big 4 willing to pay more for major purchases if sustainably produced

6. Our Quest for Circularity – Patagonia Stories UK

7. Yvon Chouinard Donates Patagonia to Fight Climate Crisis | Patagonia UK

8. Corporate Knights 2024

9. energy_compact_template_version_3_aug_clean_ORSTED_210827.docx

10. Unilever’s journey towards net zero value chain emissions by 2039 – Climate Champions

11. Boosting Plant-Based Foods | Unilever

12. Unilever sets bold new ‘Future Foods’ ambition | Unilever

13. How Unilever is leading the way in reducing food loss and waste | Nutrition Connect

14. Is Reef-Safe Sunscreen Really Reef Safe? – Think Dirty® Shop Clean.

15. Sunscreen 101: Protect Your Skin and Coral Reefs – Coral Reef Alliance

16. Coca-Cola accused of quietly dropping its 25% reusable packaging target | Plastics | The Guardian

17. Unbottling the truth: Coca Cola’s role in plastic pollution – Greenpeace Aotearoa

18. Coca-Cola forced to make shifts as global fresh water supply dwindles

19. ‘It’s plunder’: Mexico desperate for water while drinks companies use billions of litres | Global development | The Guardian

20. How Coca-Cola Disguised Its Influence on Science about Sugar and Health | Union of Concerned Scientists

21. Evaluating Coca-Cola’s attempts to influence public health ‘in their own words’: analysis of Coca-Cola emails with public health academics leading the Global Energy Balance Network – PMC 

The post Environmental Heroes and Villains – What Separates Truly Sustainable Organisations from those that Play Around the Edges?  appeared first on The European Business Review.

Leadership, Development, and Workplace Well-being

The Seven Key Competencies for Collaborative Leadership

This article explores the essential skills and traits that leaders must develop to effectively navigate today’s dynamic and digital-driven business environments. The article highlights the shift from traditional, top-down leadership models to collaborative leadership styles, where leaders act more as facilitators, empowering teams to innovate and solve problems collectively.

Why read it? This article provides a framework for the competencies required to lead effectively in the digital age. Curious about the seven competencies of a collaborative leader? Find them in the link above.

Gen Z: The Least Happy Generation at Work – How Are They Shaping the Future of Work?

Gen Z, entering the workforce amid rapid social and economic change, is proving to be the least satisfied generation at work. The generation faces unique challenges that affect their workplace happiness. Why read it? Understanding the trends of the new generations entering the workplace will help businesses attract and retain top talent. Learn how to create intergeneration well-being at the office.

From Self-Doubt to Success: Conquering Imposter Syndrome to Thrive in Business and Career

Imposter syndrome—the feeling of inadequacy or lack of skills or talent —is a common challenge in the professional world. In this article, Lior Arussy reflects on his own experience with professional self-doubt and provides practical insights on how to overcome these feelings to unlock true potential.

Why read it? This article offers a thoughtful exploration of imposter syndrome and its impact on career growth. It also provides clear strategies for confronting self-doubt, recognizing personal achievements, and building lasting confidence in your work.

Bridging the Gender Gap: How to Bring More Women to Leadership Roles

Despite high-profile successes, women still encounter significant barriers such as unconscious biases, lack of role models, and stereotypes that hinder their progress. The article addresses the ongoing challenges women face in achieving leadership positions across various industries, from venture capital to the arts. Why read it? Research shows that diverse leadership creates better results. This article explores deep-rooted issues preventing women from reaching leadership roles and offers actionable solutions to break down these barriers.

Strategic Leadership for Growth in Turbulent Times

This article explores how leaders can navigate economic uncertainty and volatility to drive growth and success. Dr. Peter Lorange, drawing from his extensive experience, provides a strategic framework for leading through instability, emphasizing the importance of non-linear thinking, scenario planning, and bold investment strategies.

Why read it? This article presents actionable strategies for executives looking to turn crisis into opportunities by fostering innovative leadership and a culture of adaptability. Get prepared for the turbulent times we live in.

Tech, Business and Trade

Corporate Innovation in the Age of AI: A Changing Landscape

This article delves into how Generative AI (GenAI) is transforming corporate innovation. The article explores how this technology complements human creativity, accelerating ideation, problem-solving, and product development, while reshaping the future of R&D and business strategy.

Why read it? As AI becomes a driving force in corporate innovation, this article provides insights on how businesses can leverage GenAI to streamline processes, improve decision-making, and fuel sustainable growth.

AI and Cybersecurity: A New Battlefield

As AI continues to permeate every sector, it introduces complex challenges in cybersecurity. This article discusses how businesses and governments are grappling with the risks AI poses, including how to regulate it while protecting sensitive data. Leaders must be prepared to secure their operations in an increasingly AI-driven world.

Why read it? Understanding AI’s implications for security is crucial, as breaches or misuse of AI could cause significant harm to businesses.

The AI Hype Has Lost Its Momentum

While AI has been a hot topic for several years, this article explores how skepticism is starting to take hold among investors and economists. AI is powerful, but its promises may not be as immediate or disruptive as originally hoped.

Why read it? Business leaders need to manage expectations around AI adoption and its return on investment.

Is Tech a Trojan Horse of Capitalism?

A critical look at how big tech companies, such as Google and Meta, dominate the digital space by offering “free” services while silently expanding their tech empires. This article raises questions about the true cost of digital capitalism and what this means for businesses in 2025.

Why read it? With growing concerns around data privacy and monopolistic practices, leaders must understand the implications of their technology use.

Global Trade Uncertainty Looms over Trump’s Tariff Threats

With Donald Trump’s return to political prominence, trade uncertainty is on the rise. This article examines the potential impact of his tariff policies, especially on industries like manufacturing and agriculture, and how businesses should prepare.

Why read it? Tariffs can disrupt global supply chains. Understanding how to navigate these changes is essential for companies with international operations.

Mario Draghi: This is How Europe Can Compete with US and China

This article discusses Mario Draghi’s suggestions for the EU to regain competitiveness against the US and China by massively investing in innovation, digital infrastructure, and sustainable energy solutions.

Why read it? Europe’s strategic moves in the coming years will significantly affect global trade dynamics. The conversation about how to get Europe on track with tech, innovation and growth is relevant for leaders and investors in Europe and beyond.

The post Top Picks for 2025: Key Articles for Leaders and Readers appeared first on The European Business Review.

By Avi Liran

Gossip can be hurtful and malicious, leaving behind a bad smell. And while we may not always avoid it, we can choose the type of gossip to engage in. Enter, reverse backstabbing, or deliberately spreading positivity behind peoples´ backs.

Gossip is a funny thing. It can be your best friend or your worst enemy. Casual gossip is the fun stuff that gets everyone talking and makes the world feel a little smaller. But negative gossip? It can leave people feeling like they’ve been run over by a bus! Still, sometimes negative gossip is useful. It exposes the rotten apples, makes the workplace safer, and helps everyone breathe easier. And then there’s my favorite type of gossip which I call “Reverse Backstabbing!”  That’s when people talk behind your back, but in a way that leaves you feeling like a superstar.

Let me invite your imagination to one of those chilly Cleveland winter days. It was freezing outside but cozy in the Weatherhead School of Management at Case Western University. Dr. David Cooperrider kicked off the course on AI (not what you think of), Appreciative Inquiry. The first lesson was an exercise in pairs called the “Appreciative Interview”.

My partner, Jeff, was a real “mentch”(1), a kind-hearted soul, humble, and totally present. With humble curiosity, he listened to me with rapt attention. But instead of reciprocating his undivided attention and appreciating his story, I found myself judging it in comparison to mine.

When someone later asked how it went, I casually remarked that Jeff’s story was uninspiring—classic negative gossip, masked with politeness.

The next day, when Jeff heard that I wanted to sell my work in America, he went above and beyond. He invited me to a CEO dinner, drove me through torrential rain, and even paid my entrance fee. He introduced me to every key player in the room, showing nothing but generosity. Reflecting on it later, I felt a wave of guilt. Here I was, badmouthing his story, while Jeff had been nothing but kind. He later handed me a thoughtful gift—no lecture, just a gentle reminder that I had been too quick to judge.

I felt like the scorpion from the Russian fable “The Scorpion and the Frog.” Don’t you do things you regret and wonder, “What the heck was I thinking?”

It brought to mind an old saying: “Those who point out others’ flaws usually highlight their own.” Carl Jung might call it ‘‘the shadow’’—the parts of ourselves we’d rather not acknowledge.

The lesson from my negative gossip wasn’t about Jeff’s story needing revision; it was my mindset. I resolved never to engage in negative gossip again but to reverse it.

Negative Gossip Hurts Everyone

Imagine finding out that a colleague has been badmouthing you behind your back. Not exactly the kind of news that makes you want to sing Kumbaya at the next team meeting, right? Trust vanishes, and suddenly, working with that person feels like running through quicksand.

Unless the gossip is protecting someone from genuine harm—like serious misconduct or ethical breaches, it’s generally better to zip it. Malicious gossip doesn’t just hurt the target but undermines the whole organization, and eventually, the gossiper finds themselves caught in their own web. It’s a losing game for everyone involved.

The perils of gossip are like trying to drive with your handbrake on. Here’s why:

• Kills trust: When people can’t trust you, they keep their ideas locked up tighter than a vault. Collaboration? More like a cold war.
• Stinks up your reputation: Spreading negativity about others is like being the “workplace skunk“. No one wants to be near you, and the stench lingers on your personal brand.
• Wastes time and destroys harmony: Gossip isn’t just a distraction—it’s a productivity killer. It’s drama, and last time I checked, drama doesn’t move projects forward.
• Ruins reputations and relationships: One careless whisper can wreck relationships and undermine DE&I efforts. It’s hard to undo the damage once people feel disrespected.
• Fuels anxiety, stress, and burnout: Gossip breeds stress like rabbits, leaving creativity and joy to fend for themselves. It’s a shortcut to emotional exhaustion and, eventually, the exit door.
• Divides teams: Gossip creates cliques, breaking down the cohesion teams need to succeed. It’s hard to hit a common goal when everyone’s picking sides.
• Creates enemies where you need allies: People remember who talked smack. In a world where connections matter, gossiping is like burning the bridge you might need to cross later.

“Positive Gossip” Ignites A Virtuous Circle

Sophie, a middle manager in a European bank with its HQ in Singapore had an exceptional team member, Alston, who consistently delivered outstanding results. Yet, despite her efforts, every attempt to secure him a promotion hit a wall.

Her boss promoted a mediocre performer from a peer team, while HR pushed the argument that others with more tenure deserved priority.

Meanwhile, Alston started showing signs of frustration and feeling undervalued after not being promoted two years in a row.

Fearing losing Alston to the competition, Sophie sought advice from Anya, her boss. Anya didn’t sugarcoat it: “You’ve been too modest about your team. The leadership and our HRBP don’t know how valuable Alston is because you’ve kept his achievements under the radar.”

Determined to turn things around, Sophie made it her mission to amplify Alston’s visibility. She openly praised his contributions in meetings, highlighted his achievements in reports, and ensured he had opportunities to present directly to senior leadership. Slowly but surely, Alston’s reputation grew across the company.

But here’s where life throws a curveball: the good news? Alston got promoted! Finally, all that hard work paid off. The bad news? Sophie, despite being a rockstar herself, didn’t. Anya, who had advised Sophie to shout from the rooftops about her team’s achievements, forgot to do the same for her. Eventually, Sophie decided to pack her bags and move to the competition where her talents were valued.

Through the experience, Sophie learned two key lessons. First, talent needs your positive gossip advocacy, and it’s critical to boost your team’s visibility well before promotion season. Second, she realized the importance of championing her own achievements. If you don’t take ownership of your own visibility, you risk being overlooked even if you’re the best in the room.

And this is where positive gossip becomes your secret weapon. What Sophie did for Alston was exactly that. She turned “positive gossip” into action.

Here’s how positive gossip ignites a virtuous circle:

• The Unsung Heroes: Positive Gossip is your secret promotion weapon. Leaders, if you want your team’s promotions to get the green light, start planting seeds of success by spreading the word about their achievements way before the promotion season.
• Trust Magnet: Positive gossip works wonders! A recent study reveals that positive gossip boosts trust, deepens relationships, and creates an environment where information flows freely. It’s like social glue.
• The Boomerang Effect: When you spread Positive Gossip, like backing someone up or giving credit where it’s due, it has a funny way of coming right back to you. It’s the ultimate feel-good boomerang. And for those who believe in a little cosmic justice, it’s a karma booster too. Think of it as good vibes on a return trip—you send them out, and they come flying back to you.
• Boosts Morale: Hearing good things about oneself or others uplifts spirits, making for a harmonious social environment at the workplace. Positive gossip is the workplace’s ”Easter egg”. It is hidden but delightful when they hear about it.
• The Scent of Positivity: In contrast to the repellant aroma of a negative gossip-monger, singing others’ praises turns you into a social potpourri. People will catch wind of your positive vibes and flock to you like bees to nectar.When you sprinkle genuine compliments at work, people not only feel good about the subject of your gossip—but they also start seeing you in a brighter light. It’s the ultimate win-win: you tell people how awesome someone is, and suddenly, everyone’s thinking, “Hey, you’re pretty awesome too!”
• Positive Gossip Foster Innovation and Loyalty: A study (2) within Chinese enterprises found that in organizations cultivating a supportive environment and strengthening interpersonal connections, positive gossip significantly enhances employee innovation. The study also found that positive gossip increases employee loyalty, which, in turn, leads to more innovative behavior.
• Positive Gossip Boosts Job Satisfaction and Sense of Belonging: Another study in China (3) found that positive workplace gossip has a direct positive effect on employees’ job satisfaction. When workers hear or participate in positive gossip, they feel better about their jobs and it strengthens the employees’ identification with their organization.

How To Avoid “Negative Gossip”

If you can’t say something nice, don’t say nothing at all.” ~ Thumper (Bambi)

Don’t spread “Negative Gossip”. If you make a hasty judgment as I did, you might feel shame and regret sharing your “opinion”. Remember in American movies, when police arrest a suspect, they are required to read the “Miranda warnings” to inform the suspect of their constitutional rights. “You have the right to remain silent. Anything you say can and will be used against you in a court of law”. The power of remaining silent can be a shield against impulsive negativity and incriminating negative gossip. In the poker game of life, your best hand may just be keeping your lips zipped.

Don’t take part in “Negative Gossip”. Let the toxic chatter train pass you by. There is no need to hop on it. If cornered for your two cents, pivot to Sherlock mode, demand proof, and champion for the accused to have a seat at the table for their own defense.

Use Socrates’ three sieves. If you can’t control the urge to take part in negative gossiping, at least filter the information and decide whether it’s worth sharing or hearing. The three sieves are Truth, Goodness, and Usefulness.

Before you spill the tea (what you intend to say), let it steep through Socrates’ three sieves: Is it true? Is it kind? Is it necessary? If it doesn’t pass all three sieves, it’s best to keep the kettle quiet!

Face the music test. This is your character’s litmus test. Are you a behind-the-scenes whisperer or a stand-up individual? Do you have the guts to say to someone’s face what you murmured behind their back?

Beware of favoritism. Selective “Positive Gossip” is counterproductive. When it is not inclusive, it backfires and is deemed discriminatory. Favoritism Positive Gossip is like a one-sided seesaw: It may lift one person up, but it leaves everyone else down, hurts morale, and ignites a wave of negative gossip.

Stand up against vicious gossip. Have other people’s back. Reveal your integrity by being the voice for those not present, especially when they’re the topic of unjust chatter.

When we encounter gossip that holds some truth and we’re unable to defend the absent individual, the least we can do is responsibly relay the constructive aspects of the chatter to the person being discussed.

How To Cultivate “Positive Gossip”

•  Spot the good. Switch and fine-tune your ”success radar” so you’ll be picking up on people’s efforts and small wins like a metal detector on a gold rush.
• Uncover the hidden. Cultivate an X-ray vision for talent. Hone your skill in unearthing hidden gems of talent. Experience sharpens your ability to recognize others’ untapped potential, especially when they’re oblivious to their own gifts.
• Be Timely: Don’t be a praise procrastinator; timely sharing of good news hits harder than a “better late than never” cheer.
•  Be consistent and authentic. Make sure you actually believe what you’re saying to avoid coming across as disingenuous. Inconsistent or fake flattery is the kryptonite to your credibility.
•  Share it with their bosses. Who wouldn’t want their higher-ups to be proud of their achievements? Make someone’s day by singing their praises in front of the very folks at work they aim to impress.
•  Rave on social media. After you’ve lauded them in the hushed tones of office chatter, seek their green light to go public. A social media shout out or a LinkedIn recommendation could be the cherry on their sundae of celebrating them.

In Conclusion

My time with Jeff taught me that gossip, whether it’s negative or positive, has consequences. Negative gossip may be tempting to vent out, but it wrecks trust, damages relationships, and hurts your reputation. It’s a losing game where everyone, including the gossiper, comes out worse.

Positive gossip, though—what I call “reverse backstabbing”—is the exact opposite. It builds others up, strengthens bonds, and even boosts your own credibility in the process.

Next time you catch yourself about to gossip, stop and ask yourself: Are these words going to tear someone down or build them up? Positive gossip creates a ripple effect of trust and cooperation, while negative gossip just drives wedges between people.

If you want to create a culture of respect and success, it starts with the words you choose. Spread positivity, recognize others’ strengths and watch how it not only makes a difference for them but also reflects back on you.

In the end, what you say behind someone’s back doesn’t just affect them—it shapes how others will remember you.

Now go and practice reverse backstabbing. Good luck.

About the Author

Avi Liran (Certified Speaking Professional, MBA) is a Global Chief Delighting Officer, an economist, author, columnist, humorist, and energetic motivational and twice TEDx speaker. Avi is one of the top motivational speakers, working globally from Singapore. He helps many Fortune 500 companies to deliver tangible results to organizations, creating delightful customer and employee experiences.

References

1. A Mentch/Mensch: First recorded in 1910–15; from Yiddish, refers to someone who embodies integrity, kindness, and responsibility. They are compassionate, considerate, and always strive to do the right thing. Being called a mentch is a high compliment, as it reflects a person’s strong character and genuine care for others.

2. Feinberg, M., Willer, R., Stellar, J., and Keltner, D. (2012, January 9). The Virtues of Gossip: Reputational Information Sharing as Prosocial Behavior. Journal of Personality and Social Psychology. Advanced online publication. doi: 10.1037/a0026650

https://www.researchgate.net/publication/221733188_The_Virtues_of_Gossip_Reputational_Information_Sharing_as_Prosocial_Behavior

3. The study titled “The Impact of Positive Workplace Gossip on Employee Innovative Behavior: The Role of Employee Loyalty and Organizational Trust,” published in Frontiers in Psychology, investigates how positive workplace gossip (PWG) affects innovation within Chinese enterprises. The research, conducted across the Pearl River and Yangtze River Delta regions, collected survey data from 327 employees. The study examines the relationship between PWG and innovative behavior, finding that employee loyalty plays a mediating role, while organizational trust acts as a moderator in this dynamic. This comprehensive analysis contributes to understanding how workplace culture and interpersonal relations influence innovation in corporate settings.

Citation: [PMC9730533]. (2022). The Impact of Positive Workplace Gossip on Employee Innovative Behavior: The Role of Employee Loyalty and Organizational Trust. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2022.9730533.

4. The research titled “The Relationship between Positive Workplace Gossip and Job Satisfaction: The Mediating Role of Job Insecurity and Organizational Identity ” was conducted by researchers from multiple universities in China. The study involved scholars from Shandong Normal University, Zhejiang Normal University, China University of Mining and Technology, and Wuhan University. It examined how positive workplace gossip influences job satisfaction, particularly through the mediating effects of job insecurity and organizational identity. The study was based on data collected from employees of a state-owned enterprise in China. It was ethically reviewed and approved by the Academic Committee of Shandong Normal University, and its findings were published in Frontiers in Psychology.

Citation: Wang, D., Niu, Z., Sun, C., Yu, P., Wang, X., Xue, Q., & Hu, Y. (2022). The Relationship between Positive Workplace Gossip and Job Satisfaction: The Mediating Role of Job Insecurity and Organizational Identity. Frontiers in Psychology, 13, 989380. https://doi.org/10.3389/fpsyg.2022.989380.

The post “Reverse Backstabbing”- The Art of Praising People Behind Their Backs appeared first on The European Business Review.

By Ana Doval de las Heras, SVP at Amadeus

Want to know what really matters to your people? Why not ask them? That’s exactly what travel technology company Amadeus did, in an exercise to optimize their IT talent retention. Ana Doval de las Heras tells us what they found.

Unlimited time off? Working from the beach? Pizza Fridays? Ping-pong before lunch? Do professionals even care about perks? Do we now work in a post-perk world?

Every day, a new claim emerges that apparently tells us exactly what professionals care about. But how hard are they listening, and does it matter?

Well-run businesses are the sum of their people, and attracting and retaining the right talent is central to success. This is something my organization cares passionately about, which is why we commissioned an independent piece of research, asking 2,200 technology professionals in eight core markets what their priorities, concerns, and ambitions are.

For global businesses, this has never been more important. As the flow of resources and traditional market dynamics have been challenged, the technology industry has become increasingly competitive. For organizations looking to outpace their competitors, a central part of their business output will be determined by whether they can attract top talent and empower this talent to realize its potential.

For organizations looking to outpace their competitors, a central part of their business output will be determined by whether they can attract and empower top talent.

Innovating the Culture of Tomorrow: Exploring how global technology talent thrives¹ reveals insights that challenge preconceived notions of what technology professionals care about, alongside highlighting long-held truths like the importance of collaborative and people-centered workplaces.

This report has brought the central themes of innovation, flexibility, training, and inclusivity to the foreground, exploring what they mean for professionals and discussing how we as employers can listen more and build these insights into our workplaces.

Innovation Matters, A Lot

Throughout every stage of employment – before joining, during, and after – a company’s reputation for innovation stands out as the most powerful influence on a technology professional’s decisions to join or remain.

When choosing a potential employer globally, they ranked “being innovative” ahead of all factors, including salary, as the most important and decisive factor. Once at work, those working at self-defined innovative companies were over five times more likely (43 per cent) than those at non-innovative companies (8 per cent) to say they were “very happy”, whereas tech workers at companies not perceived as innovative were four times more likely to say they were considering leaving within the next year.

For some readers, the weight and importance attached to innovation could be surprising. However, looking at this against the technology industry as a driver of change makes more sense. James Berry, founder of the UCL MBA program and contributor to the report, explained it this way:

“For technology professionals, the only constant is change, from the problems they solve to the software they use – everything is continually evolving. Technologies, processes, and job titles once regarded as solid and unchanging have changed or even disappeared. And the technology industry is a driver of this change, which means that technology professionals are acutely aware that being at an innovative company promises greater security and longevity.”

In other words, amidst the winds of change, you’d rather be on the boat with the best sail. For organizations looking to attract and retain top talent, this highlights the importance of communicating your innovation credentials in a salient way.

Training And Development

To keep up with the pace of change, most technology professionals anticipate several career pivots and adjustments. While we’ve seen this trend in place for some time, it’s interesting to see it confirmed by the research to the extent that only 6 per cent of tech professionals don’t anticipate a career change or role evolution.

As a result, a premium has been placed on skills, rather than titles, and employees are increasingly seeking training and upskilling opportunities to stay ahead of the curve. Indeed, nearly half (48 per cent) of respondents cited access to training as a key factor keeping them at their current companies.

Training can look different in every organization; at Amadeus, we encourage internal mobility to promote learning and skill diversification. This has resulted in 27.4 per cent of our employees changing roles in 2023. We also offer access to 94,000 training courses and host development sessions within our Career Week, which we just celebrated in November this year.

In an employment market characterized by relatively high attrition rates², employers can leverage training to grow knowledge in their teams and as a retention tool. Upskilling can enhance agility at the employee and institutional level.

Back To Basics: Flexible, Functional Workplaces

Innovation can be an elusive concept with a myriad of competing definitions. Yet, when asked to picture an innovative workspace at a technology company, most people conjure an image of bean bags, table tennis tables, and Lego.

Interestingly, the respondents disagreed with this conception and said that “buzzy” workplaces with recreational spaces were the least conducive to fostering innovation. Instead, it was much more straightforward; respondents called for improved technology (56 per cent), physical tools like suitable desks and equipment (53 per cent), and a quiet space (49 per cent). These responses are refreshing after years of novel office-ware have been prescribed as an enduring solution.

However, what I found most interesting is that having access to facilities to meet with the team face to face to brainstorm and test ideas (48 per cent) is just behind.

Beyond the provision of the de facto spaces to collaborate in, organizations also have a duty to foster socially supportive spaces and create psychological safety. Creativity and, by extension, innovation are facilitated by spaces where people feel able to suggest new approaches and are actively encouraged to experiment. Using internal incubators or creating programs to experiment is one way to build a wider culture of psychological safety.

In an employment market characterized by relatively high attrition rates, employers can leverage training to grow knowledge in their teams and as a retention tool.

At Amadeus, our Nexwave³ and LIFT programs are a space for people to experiment, where ideas are incubated but don’t have to be perfect, and it is OK if they don’t all work out. We have seen some amazingly creative, unique solutions and technologies come from these programs where teams are provided the space to foster innovation. The freedom to innovate is invaluable to employees and delivers significant returns to organizations that enable it.

Real Inclusivity Means Responding To Your Employees

Technology professionals want to see diverse workplaces, and 79 per cent of them want their employers to evidence this. This reinforces the importance of communicating your activities and credentials internally, not least so that employees know what they’re able to access themselves.

Importantly, inclusivity – and what organizations need to offer to enable meaningful inclusivity – will continue to evolve. Organizations should therefore commit to being open, reflexive, and ready to develop new programs as demands arise. For instance, we’ve been an active participant in World Mental Health Day, and this year we have evolved from local events to run our first global Mental Health event, featuring expert sessions designed to support and equip our teams.

In line with this culture of inclusivity, we have vibrant Employee Resource Groups in Amadeus, which foster diversity and a sense of belonging. Our Amadeus Proud Network, for LGBTQIA+ employees and their allies, and our Amadeus Women’s Network, are well established and have chapters in many of our offices around the world. A relatively new group is Amadeus Fenix, which supports employees dealing with long-term illness, either personally or through their family members. Creating a supportive infrastructure that recognizes the complexities of our employees’ lives is crucial to meaningful inclusion and engagement. I believe that this commitment to being open and responding to our employees’ needs plays a role in our status as a Financial Times Leader in Diversity⁴ for the last six years.

The Way Forward

The world is constantly changing, and nowhere changes faster than the technology industry. The rate of change means that technology professionals prioritize being at an innovative company with scope to upskill, develop, and feel supported. And, if these requirements aren’t met, they feel empowered to leave.

We originally commissioned this independent report⁵ to give voice to talent in technology and, now that the results are in, we hope it helps to stimulate thought, discussion, and action amongst employers as we shape our workplaces in the image of the professionals of tomorrow.

About the Author

Ana Doval de las Heras is the Senior Vice President of People & Culture at Amadeus, leading strategy for over 19,000 employees globally. With 30+ years of international experience, she has held various leadership roles since joining Amadeus in 2002.

References

1. New study finds that 40% of global tech professionals expect to make at least three career changes. November 18, 2024. Amadeus. https://amadeus.com/en/newsroom/press-releases/study-priorities-technology-professionals.

2. The True Cost of Employee Turnover in Tech. bucketlist. July 17, 2024. https://bucketlistrewards.com/blog/the-true-cost-of-employee-turnover-in-tech/.

3. The secret sauce: Six changes that made Amadeus Nexwave a top business incubator in the travel industry. Amadeus. November 11, 2024. https://amadeus.com/en/blog/articles/six-changes-amadeus-nexwave-top-business-incubator.

4. Our Awards. Amadeus. https://amadeus.com/en/about/awards.

5. New study finds that 40% of global tech professionals expect to make at least three career changes. November 18, 2024. Amadeus. https://amadeus.com/en/newsroom/press-releases/study-priorities-technology-professionals.

The post What Does the Global Technology Workforce Really Want? appeared first on The European Business Review.

By Nada Sanders, Koen Pauwels, Christoph Riedl, Rick J. Arrowood, and David De Cremer

Should the deployment and facilitation of AI be left to tech experts? How does leadership affect AI? Here are insights from the Beyond Boundaries conference by the D’Amore-McKim School of Business on how business leadership shapes AI adoption and success.

AI is bringing massive changes to society, businesses, and academia. For business schools, it is important to know how organizations, leaders, and educators can address this rapidly changing environment. At D’Amore-McKim School of Business (DMSB; Northeastern University), we take this question seriously and have made it key to our school’s mission to educate socially responsible business leaders capable of working, navigating and creating in an AI-enabled environment. To emphasize the importance of our mission to what we do in our research, teaching and corporate outreach, DMSB has launched a series of conferences called Beyond Boundaries. At the first conference in this series, we explored the relationship between business leadership and AI. The conference brought together educators, students, and AI thought leaders, including Chess Master Garry Kasparov, to engage in deep discussions and collectively identify how to navigate this new landscape. Below, we discuss what the key insights are that emerged from this conference.

The overall conclusion that emerged from the first Beyond Boundaries conference is the importance of leadership as a catalyst and facilitator to leverage AI in successful ways – both in business and academia. The discussion revealed that leaders are ultimately responsible – and not so much tech experts – for setting the rules on how to deploy AI, setting expectations and performance metrics, and offering direction regarding how to use AI in an ethical and useful manner. They have this responsibility since their primary job in any AI adoption project is to align AI with organizational goals and purpose. Only through such alignment can they create value for all involved. Within this context, the most important skills leaders must have relate to knowing and anticipating human psychology – at every level of the organization – and knowing when humans should intervene with AI. Today, while massive amounts of data are available and offer big information, this also results in huge disinformation and difficulty making decisions. It is up to humans to know how to interact with AI to make adjustments and it is up to leaders to provide a guiding environment.

How should businesses use AI?

AI systems approach human-level performance across a variety of tasks – especially in routine and data management tasks that take place in closed systems. However, humans need to know how and when to intervene. In other words, when do we stop looking at the data and use the inferred insights to make actual decisions? This ability requires making a judgment call and who better than humans to do so? Indeed, the advantage comes to the person who knows when to make a decision, and this requires relying on gut instinct and intuition. That is the difference between a good decision-maker and a great one. As Garry Kasparov said during the conference: “Little tweak, here and there has the highest return. We don’t have to challenge machine superiority in 95 percent of the cases.” This means developing the skills to know when to intervene and the humility to allow the algorithm to work autonomously the rest of the time.

It is up to humans to know how to interact with AI to make adjustments and it is up to leaders to provide a guiding environment.

David De Cremer, Dean of D’Amore-McKim School of Business noted that “engineering is easy, humans are tricky.”  The key is knowing when to bring human qualities into play. In the past, machines made us fast; today machines will make us smarter as they will provide information. But, how can leaders ensure that this new wisdom gets translated into real value? “Asking the right questions” is what makes this translation happen and what makes the difference between being a leader ready for the AI era or not. To do so, leaders need to know what their organization stands for and what they want to achieve for society and its stakeholders.

Consequently, business schools need to be aware that they must train future leaders by using AI as a tool that generates information, which is then used by students to give it their authentic touch and goals to transform content into applicable knowledge that can benefit multiple stakeholders. How will all of this influence the adoption of AI in business, the classroom and society? Below, we elaborate on what such adoption may look like.

How do businesses have to adapt to create value with this new technology?

1. Large companies

There is a need for leadership to be actively engaged and change the operating model. If leaders are not engaging, it is quite likely their organizations are not going to survive. Right now, in many organizations the head of analytics is under siege: so many new ideas are percolating upwards and downwards, and leaders have to make tough decisions. As AI is an expensive tool, it is costly for large companies to stay too long in the experimental stage of AI adoption. Large companies therefore have to think and anticipate as much as possible about where AI can create the greatest value – and deploy it in those areas.

Specifically, leaders need to be able to make a deliberate and coherent decision on where the greatest value of using AI is, such as return on equity, revenue, operational efficiency, financial leverage and so forth and those decisions should drive leadership focus. Then, leaders need a game plan on how to leverage AI to achieve those goals. It is a different way of thinking about technology, unlike what leaders have done in the past. That is, whereas in the past technology decisions were made separately they now need to be part of the leadership portfolio to achieve the greatest value and return for the business.

2. Small companies

Small companies are in a different position as they have less leeway to make mistakes and have more resource constraints than large companies. They must be lean and nimble. Nimbleness is what differentiates small companies from competitors. Engaging humans in the loop is also hard as there simply aren’t as many of them involved. Also, for small companies, it becomes difficult to evaluate potential value – when one small mistake can blow up the entire company.  So, an important decision for small companies deploying AI is when and where you take the risk. A simple analogy is what happened to blockchain about 5-6 years ago. What happened was that failure emerged for small companies that stretched their business model to the limit to accommodate the blockchain technology, whereas success emerged for those companies that saw where and how blockchain would create key opportunities for their business model.

3. Business challenge. 

Silos continue to be a dominant challenge within organizations, making it difficult to find a good strategy on how to communicate across boundaries. The answer is likely grounded in promoting a change in organizational structure and breaking down silos through shared data and technology usage. One clear thing is that organizations will not survive if they don’t break down silos. To use technology as a tool to connect and break down silos requires the use of AI. Indeed, AI can help integrate data across silos and facilitate more transparent business processes. Specifically, sharing data between different departments and identifying common goals on what questions need to be addressed can help to make clear that collaborative efforts are needed to answer crucial business questions. Data can also help to make the organization in its entirety see what their exact business challenges are and leaders need to use those insights to drive operational, customer-oriented and financial decision-making. Key business questions that will need to be asked in this approach are: what is the opportunity and how long is the path to value? What is the opportunity cost of making the wrong decision?

4. Risks and Liability. 

One of the biggest issues for businesses concerns risks and liability, such as not having the ability to document ROI or to show your decisions reveal value for the business. This is especially important when AI and data management are driving your decisions, especially short-term ones. Trying to figure out how to calculate value and how to attribute it back to the business will matter and has to align with breaking down silos and getting everyone involved. So, who is taking credit and how do we measure return? As people operate with each other, how do we measure value accurately? What about liability? Who gets credit and who takes liability? One thing is clear: with the arrival of AI, the bar has been heightened significantly.

How do business schools educate the next generation of leaders to make those tough decisions?

1. Setting expectations. 

It is essential to examine AI’s impact on performance and develop appropriate evaluation metrics.

Educators need to lead with a clear vision of how to use AI in their teaching efforts. They have to do so by effectively communicating this vision within the context of AI applications, performance expectations, and ethical considerations. A critical question to address here is the extent to which an AI tool like ChatGPT can assist those who teach and those who attend class, and whether them possessing domain knowledge or being AI novices matters. It is essential to examine AI’s impact on performance and develop appropriate evaluation metrics. The standards in the classroom must adapt when AI becomes universally accessible, as performance expectations will inevitably shift.

Another challenge involves detecting AI usage in the classroom and setting clear expectations for its use. This situation necessitates new rules for essays and guidelines on using tools like ChatGPT. It will be essential to establish the appropriate balance between AI-generated performance and the student’s own efforts in interactions with AI, so we can guarantee that the class experience becomes one where generated information is put to work in authentic and applicable ways. Such approach will incorporate a focus on preparing students to recognize the role of AI in how they can transition content to knowledge that has both value to themselves as leaders and to the organization.

2. Learning how to use AI

A significant challenge is that individuals often struggle to determine when and how to utilize AI appropriately. They may misuse AI, seeking feedback when they have already performed well instead of when they need improvement. AI is a valuable tool for those with a growth mindset, and one opportunity in the classroom is to teach students how and when to use AI effectively as their co-pilot. This teaching is a crucial role for educators as classroom leaders.

3. Reskilling

Reskilling is a popular notion within organizations and it is imperative that we start with it as early as possible – thus, in the classroom. But, what real value does reskilling reveal? Research is not entirely clear on this. First, some studies suggest that AI is particularly helpful in getting novices up to speed, for example, by giving them access to tacit knowledge embedded in the work practices of more experienced colleagues. In this case, AI could help level the playing field. On the other hand, business research has also provided evidence that AI is most useful to human experts. This happens when experts are in a better position to decide when and how to use AI, and subsequently to evaluate AI’s output and leverage it. In contrast, lower-skilled workers are not in that situation and they run the risk of using AI in the wrong situations or use it in the wrong way. For instance, studies show that novice psychiatrists who rewrite their profile with AI, raise the price too much as they overestimate the AI improvement. Overall, there may be a positive return to existing skills and then AI is likely to increase existing trends and thus also increase inequality. Business schools need to examine which processes are most likely at play and create classroom experiences where all students benefit from reskilling.

How will AI in business impact society?

Finally, AI deployment in businesses will also have a significant impact on society. If the deployment of AI can lead to lower costs for businesses by automation efforts and making jobs disappear, what will the costs be to society and how do we deal with this as business leaders?  How do we ensure that businesses can leverage the power of AI in ways that it benefits not only the organization, but all its stakeholders, including society at large? The kind of socially responsible leadership that is needed will have to deal with how to ensure that lay-offs do not translate into societal disasters, that the ambition to create more leisure time for everyone by deploying AI is meaningful to people and, finally, clear on how they will spend their time, while still being able to earn a living and thus contribute to the functioning of society.

Research shows that humans need to be challenged, so the responsibility of business leaders does not stop when employees are replaced by AI and receive a final compensation package. Businesses need to work with governments to create opportunities for human capital that will benefit society directly. This means that business leaders need to be trained as well to see that business responsibilities also include providing solutions to the bigger societal challenges and in this era, this means to think about what the best way will be to democratize AI.

The main conclusion of our first “Beyond Boundaries” conference is that across business, academia and society, business leaders cannot escape their responsibility to think about both the short-term and long-term consequences of AI adoption and use those reflections in guiding how their organizations leverage AI. Leaders and organizations that understand this responsibility and develop the skill to act accordingly will be the ones that will thrive.

About the Authors

Nada Sanders is an internationally recognized thought leader and expert on forecasting, global supply chains, risk and resilience, and human-technology integration, and is Distinguished Professor at the D’Amore-McKim School of Business at Northeastern University. She is author of seven books, including The Humachine: Humankind, Machines, and the Future of Enterprise, 2^nd ed. (Routledge, 2024), which is highly published in leading scholarly journals, and was ranked as the top 2% of Scientists by Stanford Study. She is a Fellow of the Decision Sciences Institute, has served on the Board of Directors of the International Institute of Forecasters (IIF), Decision Sciences Institute (DSI), and is a former president of the Production Operations Management Society (POMS), an organization that in 2020 created an award in her name for her contribution. She is a frequent keynote speaker, has consulted with numerous Fortune 100 companies, and serves on the Board of Economic Advisors of the Association of Industries of Massachusetts (AIM).

Koen Pauwels is the Associate Dean of Research and Distinguished Professor at Northeastern University and founding General Director of its Digital, Analytics, Technology and Automation (DATA) Initiative. He was a Principal Research Scientist at Amazon Ads, with brand building and budget allocation recommendations reaching hundreds of thousands of advertisers.  Koen received his Ph.D. from UCLA, where he was chosen Top 100 Inspirational Alumnus. After getting tenure at the Tuck School of Business at Dartmouth, he helped build the startup Ozyegin University in Istanbul. Named a worldwide top 2% scientist, and ‘The Best Marketing Academic on the Planet’, Koen published over 100 articles on marketing effectiveness. This research was awarded by both managers and academics. Koen is the editor-in-chief of the International Journal of Research in Marketing. His books include Modeling Markets and Advanced Methods for Modeling Markets for analysts, and Break the Wall: Why and How to Democratize Digital in Your Business, and It’s Not the Size of the Data – It’s How You Use It: Smarter Marketing with Analytics and Dashboards for managers.

Christoph Riedl (c.riedl@northeastern.edu) is professor of Information Systems at the D’Amore-McKim School of Business, Northeastern University. He obtained his PhD from the Technische Universität München, Germany. Dr. Riedl’s research focuses on collective intelligence, crowdsourcing, and collaboration in human-AI teams.

Rick J. Arrowood is a Lecturer at the D’Amore-McKim School of Business at Northeastern University and a Visiting Professor in the Executive MBA program at the University of Central Punjab in Lahore, Pakistan. He specializes in Management, Organizational Development, and Leadership, with a research focus on the behavioral aspects of technology use by faculty and students in both traditional and online classrooms. Rick also consults for healthcare technology firms in the US and Pakistan. He has authored numerous case studies, published in leading journals, and serves on the editorial board of the Journal of Education and Education Policy Studies. His previous roles include serving on various nonprofit boards, teaching in Northeastern University’s dual master’s degree programs in Australia and Vietnam. Additionally, he founded The Leader Brew Podcast to share the stories of former students transitioning from the classroom to the real world.

David De Cremer is the Dunton Family Dean and professor of management and technology at D’Amore-McKim School of Business, Northeastern University (Boston). He is the founder and former director of the Center on AI Technology for Humankind in Singapore and an advisory board member at EY (formerly Ernst & Young) for their global AI projects. Before moving to Boston, he was a Provost’s chair and professor in management and organizations at NUS Business School, National University of Singapore, and the KPMG-endowed chaired professor in management studies at Cambridge University He is named one of the World’s top 30 management gurus and speakers by the organization GlobalGurus, one of the “Thinkers50 list of 30 next generation business thinkers” and continuously included in the World Top 2% of scientists. In addition to being highly published in the leading management and psychology journals, he is a best-selling author and his latest book The AI-savvy Leader: 9 Ways to Take Back Control and Make AI Work (published by Harvard Business Review Press, 2024) was named book of the month June 2024 by the Financial Times, selected as a must-read for summer 2024 by the Next Big Idea Club, and #1 new release at amazon.com.

References

• Aksehirli, Z., Y. Bart, K. Chan and K. Pauwels (2022). Break the Wall: Why and How to Democratize Digital in Your Business (Emerald Publishing).

• De Cremer, D. (2024). The AI-savvy Leader: 9 Ways to Take Back Control and Make AI Work, Harvard Business Review Press.

• De Cremer, D., and Kasparov, G. (2021). AI Should Augment Human Intelligence, Not Replace It. Harvard Business Review: https://hbr.org/2021/03/ai-should-augment-human-intelligence-not-replace-it

• Jones, A., and Miller, B. (2023). AI in Education: Navigating Ethics and Performance. Journal of Educational Technology, 15(2), 103-115.

• Kiron, D, Altman, E.J., and Riedl, C. (2023). Workforce Ecosystems and AI. Brookings Institution. https://www.brookings.edu/research/workforce-ecosystems-and-ai/

• Pauwels, K. (2014). It’s Not the Size of the Data: It’s How You Use It: Smarter Marketing with Analytics and Dashboards, American Management Association (AMACOM).

• Sanders, N., and Wood, J. (2024). Humachine: AI, Human Virtues, and the Superintelligent Enterprise (Routledge Press).

• Smith, C. (2022). The Role of AI in Modern Classrooms: Challenges and Opportunities. Educational Review, 29(4), 467-482.

• Williams, D., and Harris, E. (2021). Integrating AI into Teaching Practices: A Guide for Educators. Teaching Innovations, 18(1), 89-101.

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