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        <title>INSEAD Knowledge</title>
        <link>https://knowledge.insead.edu</link>
        <description>The business school for the world</description>
        <lastBuildDate>Wed, 13 May 2026 10:21:07 +0800</lastBuildDate>
        <language>en</language>
        <item><title>What High Oil Prices Mean for the Energy Transition</title>
                  <link>https://knowledge.insead.edu/economics-finance/what-high-oil-prices-mean-energy-transition</link>
                  <description> <![CDATA[The Iran war has sent oil prices and inflation soaring. It has also produced a less visible but no less damaging consequence: The energy transition is sliding further down the agenda of oil and gas companies.My research, published in Strategic Management Journal, offers hints as to how this could play out. I studied how oil and gas firms behaved during a previous major disruption to their industry – the 2014 oil price crash, which forced them to reckon with excess capacity. Extrapolating from those findings, today’s environment makes the transition to renewables increasingly unappealing for oil and gas firms. Even when firms have strong incentives to reposition, market forces alone are not enough, let alone when companies can instead capture war-generated windfall profits.What happened a decade agoAfter the 2014 price collapse, a small number of oil and gas companies that had already diversified into wind power cut offshore oil and gas spending and redirected it towards wind projects. These firms represented only about 2.5% of the oil and gas companies I studied. But when this minority chose to invest, the impact on offshore wind technology was significant.Where a wind farm sat within close proximity of established oil and gas assets, post-shock investment rose by as much as US$23 million per project, compared with a pre-shock average of US$6 million. These firms also deployed larger, more powerful and more technologically advanced turbines than their pure-play wind rivals. Several projects demonstrated that oil and gas companies possess transversal capabilities that can push the technological frontier in offshore wind.Equinor’s Hywind project, the world’s first commercial floating offshore wind farm, illustrates the point. Developed by a firm rooted in Norwegian oil and gas and commissioned near existing North Sea fields, it drew on engineering competencies that a pure-play renewables developer would have struggled to assemble from scratch.Policy... must create conditions in which the energy transition becomes a strategically attractive use of existing industrial capabilities – not merely a box-ticking obligation or a reputational hedge.  Post-crash conditions converged to pull energy firms towards wind in that period. The industry had idle capacity, lower returns on incremental oil and gas projects, and a pressing need to find productive uses for expensive resources – vessels, engineering and project management expertise, and an entire supply chain that would otherwise have sat idle. Combined with clear government policy favouring renewables, wind power began to look attractive by comparison – at least to some companies.What’s happening nowToday’s conditions are the opposite. In the wake of the Iran war, the incentive to redeploy resources towards renewables has collapsed. BP has announced a reorganisation of its business units that clearly reverses its push into renewable energy. TotalEnergies is swapping offshore wind projects on the United States East Coast for oil and gas projects in Texas. Left to itself, the market is plainly insufficient to drive the scale of transition required by climate targets, particularly as policy and decision-makers put climate policies themselves on the backburner.What the industry can do that others cannotThis matters because the capabilities oil and gas firms possess are not easily replicated elsewhere. The next generation of offshore wind projects – floating foundations, production sites far from shore, cables running across seabeds – would benefit enormously from the industrial project management expertise that sits inside the major oil companies and their supply chains.My research makes one conclusion difficult to avoid: The firms best equipped to accelerate the energy transition are largely not doing so, and today’s price environment gives them little reason to. Generic calls to abandon oil and gas are not only impractical but wasteful, because this industry possesses many of the elements needed to technologically advance and commercially realise renewable projects at scale.What policymakers need to doPolicy needs to do more than price carbon. It must create conditions in which the energy transition becomes a strategically attractive use of existing industrial capabilities – not merely a box-ticking obligation or a reputational hedge. That could mean targeted incentives for wind and other renewables, such as geothermal, that leverage existing oil and gas infrastructure, or long-term contracts that de-risk the investment case for firms considering redeployment. Recent moves by the European Union to shift individual behaviour are commendable, but policy needs to be far more targeted towards industrial players if it is to drive change at scale.The oil and gas industry doesn’t need to remain the villain of the energy transition story. In many respects, it is best placed to accelerate the next chapter. At current oil prices, however, this is unlikely. The gap between potential and action is what policy must target.]]></description>
                  <pubDate>Thu, 07 May 2026 01:00:48 +0000</pubDate>
                  <guid isPermaLink="false"> 48591 at https://knowledge.insead.edu</guid>
                  <comments> https://knowledge.insead.edu/economics-finance/what-high-oil-prices-mean-energy-transition#comments</comments>
                <enclosure url="https://knowledge.insead.edu/sites/knowledge/files/styles/panoramic_large/public/2026-05/shutterstock_1149456404_1.jpg?itok=M2VBbbcb" type="image/jpeg" length="148271" /><dc:creator>Aldona Kapačinskaitė</dc:creator></item><item><title>The Role of Business in the Humanitarian New Normal</title>
                  <link>https://knowledge.insead.edu/responsibility/role-business-humanitarian-new-normal</link>
                  <description> <![CDATA[Since the United States withdrew its support for the international humanitarian community in early 2025, it has cut US$709 million in life-saving grants. The United Kingdom, Germany and the European Union have followed, slashing over 30 percent of their aid budgets and channelling part of those funds to re-armament. Unfortunately, the US’ spectacular success in fighting disease in low- and middle-income countries in the last 30 years is now reversed. In this “new normal”, we’ve seen the collapse of global response capacities and the disruption of the UN cluster’s efforts to coordinate with NGOs on the ground – at a hefty cost. By June 2025, the funding cuts to USAID health programmes had led to the deaths of nearly 270,000 adults and over 560,000 children, at a rate of 88 deaths per hour.  The funding cuts could result in more than 14 million additional deaths by 2030, according to a Lancet study. In the words of Esther Duflo and Abhijit Banerjee, both Nobel-prize-winning economists and poverty researchers: “For many throughout the world, this is a bloody time”.Unintended consequencesThe mortality figures are appalling, but the indirect consequences also deserve our attention. We are seeing the emergence of unintended risks to our social and economic systems: the loss of efficiency, reliable information and influence. On the ground, the nearly 42-percent cut in funding has led to layoffs of 12,000 humanitarian workers and closure of at least 22 humanitarian organisations, representing a critical loss of talent and institutional memory. Take the US’ construction of a floating pier for the delivery of 2 million meals to Gaza per day. Its almost immediate shutdown (attributed to insufficient training, planning and equipment failures) was followed by slow and non-transparent food distribution by military contractors on the ground. This shows that defence and foreign policy bureaucracies face a steep learning curve in responding quickly to emergencies. When the lines between humanitarian and military activities are blurred, it quickly becomes apparent that military capacity is not inherently designed, or equipped, to save lives.  In addition, access to reliable information is compromised due to the politicisation of humanitarian work fuelling misinformation. Since state-led initiatives are not subject to the same rigorous audits and restrictions as international humanitarian organisations, the result is less transparency and accountability, such as the impact of the US$230 million of taxpayers’ money spent on the failed pier project. In the current geopolitical context, the unintended consequences of the new normal – the erosion of neutrality, impartiality and independence – directly impact the integrity of our modern society.  Global citizens cannot stand by as hard-won humanitarian gains and institutions are discarded.We’re all connectedBusiness is intricately linked to economic development. With globalisation, the integration of global supply chains has boosted economic growth, enabling each country to invest in its strengths and source the rest from the world. More importantly, in the last 30 years, it has lifted over a billion people out of poverty. Then there is the interconnectedness between aid providers and the local businesses and economy. For decades, international businesses have benefited from the spillover effects of USAID’s engagement in less developed countries. When local suppliers are contracted by humanitarian aid projects, it gives them the opportunity to expand their business and this in turn drives local economic growth. The entry of aid providers can trigger the development of institutional capacity, which in turn, enables international firms to operate in these emerging markets.Recent large-scale global crises such as the Covid-19 pandemic have made us acutely aware of our interconnectedness. They taught us that no one is safe until everyone is safe, and that trade has helped solve shortages as they occurred around the world. Even rich countries may one day need the kind of emergency relief that depends on the kindness of strangers. The question is how to benefit from the linkages while mitigating the risks. The difference that business makes Could humanitarianism, which directly contributes to an equitable, peaceful and rule-based system, be defined as a public good, like the environment? As global citizens, we should preserve it. And business leaders are uniquely qualified to do so by translating good intentions into plans with realistic resource allocations and measurable results. Targeted social projects by businesses, such as Walmart’s support for hurricane response in the US, are not new. Global logistics companies have joined the Logistics Emergency Team network to offer transport capacity for emergency operations. Companies like Takeda Pharmaceutical Group have co-funded public health supply chain capacity-building with governments in Africa. These companies are not only contributing resources to emergency operations; they are helping to develop capacities. In less developed countries, as they build infrastructure and trade with local firms, they are in fact promoting supplier development. And as these markets develop, their increased economic participation and growth combine to create a virtuous cycle, increasing access to goods and services, and ultimately benefiting the local communities and businesses. Business can also use its know-how (and know-who), to work with governments and key stakeholders to design more resilient systems that are not dependent upon single donors. For example, in response to drastic funding cuts, a public-private supply chain leadership group convened by the European Civil Protection and Humanitarian Aid Operations  has identified over 100 measures to improve aid distribution. But dedicated expertise is needed for public-private partnerships to succeed. In particular, governments will need to deepen their managerial capacity, make better stockpiling decisions and enable cross-border pooling of essential medicines ahead of the next global pandemic. Agents of changeAdam Smith is known for writing the classic “The Wealth of Nations”, but he also stressed the importance of empathy, fairness and community, because efficiency without virtue undermines the economic system. Our research in humanitarian operations reveals that virtue without efficiency is equally unacceptable. As the business school for the world, INSEAD has a role in informing policymakers, business and the public, empowering them to make the needed change to make humanitarian systems more resilient. For decades, our Humanitarian Research Group has worked on improving structures and processes in both commercial and humanitarian organisations to improve performance. Beside strengthening collaboration between organisations extending aid, our knowledge, built on decades of rigorous scientific studies, is translated into action by partners such as the International Federation of Red Cross and Red Crescent Societies. Practical contributions include analysing how much stock to pre-position in crisis-prone regions, devising more efficient use of humanitarian transport fleets, and updating asset replacement rules to reduce costs and carbon footprint in humanitarian operations. Our body of knowledge is fodder for new business models. Business can be a force for good if they adapt commercial practices of supplying food, shelter or medical care to meet the needs of crisis-prone regions. But it’s not just about ideals. The current geopolitical situation and ongoing war in the Middle East drives home the message: The destabilising effects of disease, starvation and political upheaval – on economies, communities and individuals – are real. ]]></description>
                  <pubDate>Thu, 16 Apr 2026 01:00:00 +0000</pubDate>
                  <guid isPermaLink="false"> 48531 at https://knowledge.insead.edu</guid>
                  <comments> https://knowledge.insead.edu/responsibility/role-business-humanitarian-new-normal#comments</comments>
                <enclosure url="https://knowledge.insead.edu/sites/knowledge/files/styles/panoramic_large/public/2026-04/lifeboat_0.jpg?itok=rfelb8FJ" type="image/jpeg" length="753539" /><dc:creator>Bublu Thakur-Weigold</dc:creator><dc:creator>Luk Van Wassenhove</dc:creator></item><item><title>Your Strategy Is a Flashlight, Not a Business Plan</title>
                  <link>https://knowledge.insead.edu/responsibility/your-strategy-flashlight-not-business-plan</link>
                  <description> <![CDATA[I recently had the opportunity to speak at ChangeNow, a global summit that brings together leaders working at the frontier of social and environmental change. The question that opened our panel felt as urgent as any on the programme: What does strategy actually mean in a world that won’t hold still?My answer was blunt. The business plan, as most organisations conceive it, is dead.Strategy is not a business plan. It’s a flashlight, a tool you use to look for opportunities in a constantly shifting environment. In a world where the assumptions underpinning a strategic document can be overtaken by events within weeks, the traditional approach of writing a plan, shelving it and executing against it is no longer sufficient.Search, don't planThe alternative is to understand strategy as a dynamic process of search, one that continuously attempts to match what an organisation has with what the world currently demands. This means regularly asking hard questions: What are our goals? What resources and capabilities do we currently lack to achieve them? What is the most efficient path to closing those gaps?Gaps can be addressed in three ways: through internal development, through strategic partnerships and alliances, or through acquisitions. For social entrepreneurs and impact-driven organisations, the first two are the most relevant. Build what you can develop yourself; borrow, through partnerships, what would take too long or cost too much to build alone.Critically, this isn’t a one-time exercise. It’s a recurring discipline. Organisations must install rules around decision-making: structured processes for periodically reviewing whether they are in the right markets, pursuing the right objectives and building the right capabilities. Besides determining the strategy, consider what would happen if your assumptions are wrong, and how often you’re rethinking what you’re doing. At ChangeNow, I spoke with Monica de Virgiliis, chair of Chapter Zero France and a director at Air Liquide, whose thinking on strategy in uncertain environments maps closely onto this. She distils the challenge into three behaviours:Speed: Companies must move fast, questioning the constraints that previously slowed them down and compressing years of experimentation into months.Optionality: Rather than betting on a single vision of the future, organisations should develop strategies that remain viable across multiple scenarios.Resilience: Building redundancy into systems, diversifying across suppliers and technologies and, critically, adopting a leadership style that admits uncertainty rather than pretending to resolve it.As she mentions in her TEDx talk, the leader's role is not to have the answer, but to find it collaboratively.When good intentions go wrongFootwear brand Toms is one of the most instructive examples of a strategy that began with genuine social purpose and ran into the limits of planning. The original model was simple: For every pair of shoes sold in more economically developed markets, a pair would be donated to communities in less economically developed markets. The intent was noble, but execution created a cascade of unintended consequences.Donating generic footwear to communities with local shoemaking industries risked undermining livelihoods. The shoes were often ill-suited to local climates and terrains and, at a more fundamental level, the model addressed the symptoms of poverty rather than its root causes.Acting on these unintended negative consequences, Toms adapted its business model. Rather than donating shoes, the company now directs a portion of its profits to partner organisations embedded in local communities. These organisations understand local needs and can deploy resources far more effectively. In some cases, this means funding local enterprises to purchase shoemaking machinery, simultaneously generating employment and producing contextually appropriate products.The core concept remains the same – sell in more economically developed countries, support communities elsewhere – but the mechanism changed entirely. This is strategy as search in practice: a willingness to let go of the original plan when evidence demands it, while staying committed to the underlying mission.Ecosystem thinking: the Pratham modelIf Toms illustrates the need for strategic flexibility, the Indian literacy organisation Pratham offers a masterclass in ecosystem orchestration.Pratham began by developing two core assets: a rigorous methodology for assessing childhood reading ability and an evidence-based approach to improving it. Instead of attempting to scale by building its own operations across dozens of countries, a capital-intensive and operationally complex undertaking, it packaged those assets and deployed them through a network of local partners. Today, its methodology is used in Colombia, Brazil, the Philippines, Nepal, Egypt and beyond.Childhood literacy might seem an unlikely candidate for global scalability, but what scales is not necessarily the organisation itself – it’s the knowledge and the model. Identify what you uniquely know, codify it and find partners who can carry it further. Such ecosystem thinking can help organisations with limited resources achieve disproportionate reach.The world has always been turbulentThere’s a temptation to treat the current moment as singularly unpredictable, to argue that AI, geopolitical fragmentation and shifting trade structures have created a complexity without historical precedent. That argument doesn’t hold because the world has always been dynamic. What we’re finally acknowledging is that strategy-as-plan was always the wrong model.Steam, electricity, the telephone, the railroad, semiconductors, the internet – each brought disruption that seemed, at the time, without parallel. The organisations that navigated those transitions successfully weren’t the ones with the best plans. They were the ones with the clearest sense of purpose, the sharpest awareness of their capability gaps, and the flexibility to search for new paths when the old ones closed.The prescription is the same whether you’re building a for-profit venture or a social enterprise: know your gaps, know your ecosystem, stay ready to pivot. Treat strategy not as a destination, but as a continuous act of search. ]]></description>
                  <pubDate>Tue, 14 Apr 2026 01:00:00 +0000</pubDate>
                  <guid isPermaLink="false"> 48526 at https://knowledge.insead.edu</guid>
                  <comments> https://knowledge.insead.edu/responsibility/your-strategy-flashlight-not-business-plan#comments</comments>
                <enclosure url="https://knowledge.insead.edu/sites/knowledge/files/styles/panoramic_large/public/2026-04/light_small.png?itok=iJrNvQ2G" type="image/png" length="973364" /><dc:creator>Andrew Shipilov</dc:creator></item><item><title>How to Build A Successful AI Hub</title>
                  <link>https://knowledge.insead.edu/strategy/how-build-successful-ai-hub</link>
                  <description> <![CDATA[While exact estimates vary, the size of Silicon Valley’s economy was comparable to China’s GDP in 2024, while the combined market capitalisation of major Silicon Valley tech companies topped US$20 trillion in 2025. Considering these staggering numbers, it’s no surprise that many low-income countries have tried to replicate the “magic” of Silicon Valley. In Africa, for example, a number of technology parks have been launched, including Konza Techno City in Kenya, Yabacon Valley in Nigeria, Kigali Innovation City in Rwanda and, most recently, Silicon Accra in Ghana. Common driversBased on my discussions with various ministers of economy, digital transformation and education from Asia, Africa and Latin America, there are four key drivers or objectives behind these tech-hub efforts:Sovereignty: A means of achieving independence from global tech behemoths such as Microsoft, Google, OpenAI and Meta.Localisation: The means to develop content and applications that meet the specific needs and languages of local communities, particularly those underserved by existing content.Building muscle: Offering an environment that can support and nurture local talent to implement these local solutions.Building a viable ecosystem: One that is commercially successful and sustainable, without the need for long-term government subsidies. Lessons in failureWhile the tech hub examples listed above are still under development, they are not the first to try and recreate Silicon Valley. The majority of previous efforts have failed, due to reasons ranging from talent scarcity to political uncertainty.For example, “Hope City,” Ghana’s first Silicon Valley project never took off after its 2013 launch due to bureaucratic and funding issues. Other notable failures include Cyberjaya in Malaysia, KAEC Tech & Innovation Zones in Saudi Arabia, and Amaravati in India.While each offers different lessons, all underline the fact that Silicon Valley’s success is built on a mixture of features that are often intangible and very difficult to reproduce. These include a risk-tolerant culture, closeness to top-tier universities, networks of talent, abundant venture capital and a long history of innovation. This is particularly difficult to replicate in environments that face stifling bureaucracy, alongside a culture of aversion to risk and collaboration.A commercial approachFor the last two decades, INSEAD’s TotoGEO AI Lab has been working with multinationals and non-profits, including the Gates Foundation, to tackle the “content divide” – the lack of relevant, usable online content in many local languages and contexts. As part of this extended mission, the lab is now partnering with entrepreneurs worldwide to use AI in building a new generation of local technology hubs. One such partner is David Osei, co-founder and CEO of Silicon Accra whose Twelve Springs Investment Group is developing business parks that blend high-yield commercial ventures – hotels, luxury apartments, co-working hubs and golf courses – with subsidised or free space for startups and incubators.Launched in 2016, Silicon Accra’s first phase plans office space for 20,000 people and aims to host research institutions, corporates and ICT startups in an ecosystem that drives technological development in Ghana. What sets it apart from many tech hubs is the intention to use profits from real estate developments to subsidise the tech ecosystem. Following a model inspired by London’s Canary Wharf and South Korea’s Songdo, it assumes rapid land appreciation, early anchor tenants, supportive capital markets and startups that can eventually pay market rates. Osei stresses that Silicon Accra is a long-term play. The infrastructure is already in place but full build-out of apartments, offices, labs and co-working spaces is ongoing. The long-term ambition is that more than 50 startups, linked to on-site university research labs and training programmes, will be based in Silicon Accra by the end of the decade.TotoGEO’s role is to provide the core technology infrastructure and monetisable platforms that help the park shift from a real-estate-led phase to a productive, revenue-generating innovation ecosystem. Over time, TotoGEO will transfer both know-how and technology to Ghanaian ownership, helping establish a local AI lab that builds customised products for sectors such as agriculture, fintech and govtech, and offering training and other services.These new revenue streams are intended to support startups, subsidise workspaces and attract anchor tenants, creating a self-reinforcing model for local innovation. Where earlier tech hubs often started from scratch, TotoGEO offers a way to “hit the ground running” by plugging into existing platforms, from B2C search engines to B2B tools, so that emerging ecosystems like Silicon Accra can move more quickly from concept to impact.Alternative approachesSilicon Accra’s real-estate-driven approach is not the only option. Several technology hubs in other low-income economies demonstrate alternative blueprints for success – particularly those that embed artificial intelligence into their core strategy from the outset.Take the National Innovation Center (NIC) in Hòa Lạc, Vietnam. Established in October 2019 under Vietnam’s Ministry of Planning and Investment, NIC is more than a technology park. It’s a government-led attempt to build a national innovation platform. The Hòa Lạc campus, inaugurated in October 2023, anchors a national convening hub which links startups, enterprises, academia and international partners. NIC’s key strategy is to target “mission sectors” – covering areas such as smart factories and cities, semiconductors, digital communications and cybersecurity – to concentrate programming and partnerships. NIC emphasises sector-focused pipelines, rather than a fixed number of resident companies. NIC demonstrates how to use national mandate, strong partners, and sector missions to strengthen focus, buying time for the physical campus to become the default meeting place for start-up ventures.Meanwhile in central Asia, the Astana Hub in Kazakhstan adopts a policy-led cluster model where the core value proposition is not space but incentives and internationalisation. Opened as an IT park in 2018, Astana Hub positions itself as a “bridge to the world”. It runs programmes with global partners such as Google for Startups and California’s Draper University. By late 2025, Astana Hub reported over 1,850 participant companies, including more than 470 with foreign ownership or investment. Success stories have included AI video generation company Higgsfield AI, parking management solution Parqour and agritech platform Egistic. The takeaway is simple: Countries that cannot outspend others on venture capital could make it cheaper and easier to build locally – through incentives, visas, and predictable rules – and then layer export pathways and global accelerators on top.A third approach is represented by Ruta N in Medellín, Colombia, a city-led innovation district. Founded in 2009 as a joint venture between Medellín’s Mayor’s Office, UNE (telecom), and EPM (public utilities), Ruta N demonstrates how a municipality can orchestrate ecosystem development without waiting for national policy change. The strategy combines a designated innovation district with a physical complex that functions as a soft-landing base, thanks to its infrastructure and incentivized rents, for companies of varying sizes.Ultimately, there is no single template for a “Silicon-X”. Be it national mandate, regulatory incentives, district branding or real-estate-backed cash flow, what really matters is identifying a structural advantage and turning it into a catalyst for AI-driven growth.]]></description>
                  <pubDate>Mon, 13 Apr 2026 00:53:15 +0000</pubDate>
                  <guid isPermaLink="false"> 48521 at https://knowledge.insead.edu</guid>
                  <comments> https://knowledge.insead.edu/strategy/how-build-successful-ai-hub#comments</comments>
                <enclosure url="https://knowledge.insead.edu/sites/knowledge/files/styles/panoramic_large/public/2026-04/creatingtechhubs.jpg?itok=-XqpOjFj" type="image/jpeg" length="896850" /><dc:creator>Philip M. Parker</dc:creator></item><item><title>The Curse of Success </title>
                  <link>https://knowledge.insead.edu/responsibility/curse-success</link>
                  <description> <![CDATA[The World Bank recently released its 2026 Women, Business and the Law report, which measures how laws, regulations and policies shape women’s economic opportunities and private sector development across 190 economies. Among the 10 topics used to measure women's economic empowerment are workplace, marriage, parenthood and entrepreneurship. One of the highest scorers in the world is Sweden.Across the board, women spend more time on housework and carry more of the responsibility for children, which affects their pay and well-being. Sweden offers 480 days of paid parental leave, with 90 days reserved for each parent. These policies help mothers of young children return to work faster. Similarly, when it comes to laws on marriage, mobility and women's pay, Sweden gets a perfect score.But equality rankings don’t tell the whole story. Getting ahead at work comes at a price – even in Sweden.Success comes at a costEconomists Olle Folke (Uppsala University) and Johanna Rickne (Stockholm University) investigated how career success affects marriages. They compared divorce rates among candidates who ran in Swedish municipal elections – those who won and those who narrowly lost. For women, winning an election increased the risk of divorce. For men, the result of the election had no effect on their marriages.Must women choose between their career and their relationship, then? Or are politicians an exception? To explore this further, Folke and Rickne examined CEO appointments across Sweden over a decade. The pattern was the same as in politics: women promoted to top executive positions were twice as likely to get divorced as men who received equivalent promotions.The curse of success isn’t limited to politics and business. In Hollywood, it’s common knowledge that winning an Academy Award is great for your career, but bad for your love life. That is, if you’re a woman.H. Colleen Stuart (John Hopkins University), Sue Moon (New York University) and Tiziana Casciaro (University of Toronto) tracked all the Best Actor and Best Actress nominees from 1936 to 2010. They found that Best Actress winners were more likely to get divorced than actresses who were nominated but didn’t take home the golden statuette. The Best Actor winners, on the other hand, didn’t suffer from the so-called “Oscar curse”.But a separate study suggests male winners aren’t entirely unaffected. When Michael Jensen (University of Michigan) and Heeyon Kim (Cornell) compared winners and nominees against elite actors who were never nominated, they found that the men’s marriages suffered, too. The researchers attributed this to the influx of professional and romantic attention that follows a major public win.Does this mean winning a Swedish municipal election might generate a flood of romantic proposals for female politicians, and that higher divorce rates are just a reflection of their love lives picking up? Most likely not. Folke and Rickne found no evidence of a "temptation effect" in which women's (but not men's) promotions increase their chances of finding a new partner. In fact, women who were divorced and promoted remarried at a slower rate than divorced women without promotions.The explanation lies elsewhere: in deeply rooted assumptions about whose success is acceptable within a relationship. Folke and Rickne found that the couples who weathered a woman's election win with the least damage were those in which income differences remained small after the promotion. The problem wasn’t success itself, but the status disruption it created.The persistence of gender normsResearchers Alyson Byrne and Julian Barling have given this mechanism a name: status leakage. Studying over 200 hundred women in high-status positions, they found that the strain in these marriages was driven by feelings of embarrassment and resentment, on the part of the man, about a partner's career trajectory rather than income differences. Another factor was a sense that the man’s own hard-earned status was diminished by association. These feelings predicted lower relationship satisfaction and higher marital instability. In other words, what matters isn’t just money, but status and prestige as well. Their research also points to what can protect a relationship. Byrne and Barling tested whether a partner's support could lessen these effects and found an interesting result. Offering emotional support in the form of encouragement, understanding and expressions of pride made no difference to a couple remaining together. But giving instrumental support, such as taking on childcare responsibilities, emptying the dishwasher and staying on top of dentist appointments, essentially eliminated the negative effect on marital stability. When partners provided tangible support, the link between a woman's higher status and relationship strain disappeared. What’s important isn’t the chores themselves, but what doing them signals: that both careers belong to both partners. It’s a shift from "your success" to "our success".My INSEAD colleague Jennifer Petriglieri, who has spent years studying how dual-career couples can thrive in love and work, puts it well: The conventional framing of two careers as a zero-sum game is exactly the trap that breaks couples apart. Couples who navigate these tensions successfully are those who communicate openly about their values, boundaries and fears, and treat each transition as something to work through together.The curse of success isn’t inevitable. It lifts when both partners decide, explicitly, that they are on the same team]]></description>
                  <pubDate>Tue, 28 Apr 2026 01:00:00 +0000</pubDate>
                  <guid isPermaLink="false"> 48511 at https://knowledge.insead.edu</guid>
                  <comments> https://knowledge.insead.edu/responsibility/curse-success#comments</comments>
                <enclosure url="https://knowledge.insead.edu/sites/knowledge/files/styles/panoramic_large/public/2026-03/shutterstock_2256924245_2.jpg?itok=22pR7Lh9" type="image/jpeg" length="309481" /><dc:creator>Kaisa Snellman</dc:creator></item><item><title>Could AI Tools Actually Help Us Feel Better?</title>
                  <link>https://knowledge.insead.edu/responsibility/could-ai-tools-actually-help-us-feel-better</link>
                  <description> <![CDATA[Over one billion people now live with mental health disorders, according to a 2025 World Health Organization report, costing the global economy more than US$1 trillion annually. At the same time, recent estimates suggest that over 800 million people are already using ChatGPT, and that 70 percent of interactions with the chatbot are for non-work purposes. My co-authored research has documented that around a quarter of those people are turning to large language models (LLMs) for mental health support.A massive uncontrolled, real-world experiment in AI and human psychology is already underway. People aren’t waiting for researchers or regulators to tell them whether it’s a good idea to talk to a chatbot about their problems. They are already doing it. The question is no longer whether AI will shape mental health, but how, and whether we can make these systems safe and effective.Typically, the narrative around digital platforms and mental health has been almost entirely negative. Social media has been linked to rising depression, anxiety and psychological distress, while alarming stories about chatbots giving dangerous advice have reinforced fears that AI will only make things worse. These concerns are real and should not be dismissed. But they don’t capture the full picture. The early evidence suggests that AI’s psychological effects are more varied, and in some cases more positive, than the sensational headlines imply.What the early evidence showsIn our recent study, my co-authors and I examined how people’s well-being changes after brief, structured interactions with chatbots. We tested four exercises grounded in psychological research: savouring positive experiences, expressing gratitude toward someone close, reflecting on sources of meaning, and reframing one’s life as a “hero’s journey”.The results were striking. All four interactions significantly improved happiness, life satisfaction and sense of purpose, while reducing anxiety and depressed mood. These effects emerged after a single conversation lasting just 8 to 10 minutes on average. Perhaps most surprising, the chatbot interactions also increased users’ interest in traditional therapy rather than replacing it – in a way, the tool kickstarted the conversation about well-being.These are early findings and should be treated with caution. But they suggest that well-designed AI interactions can function as a low-cost, scalable entry point for psychological support – not as a substitute for therapy, but as a complement and even a pathway to it.Who is using AI for mental healthInterestingly, in another study, also conducted in the United States, my co-authors and I found that young Black men were the most likely to turn to LLMs for mental health support. This makes sense when you consider the barriers these communities face: cost, insurance gaps, provider availability and stigma. As our respondents reported, LLMs offer something that is immediate, private, free and non-judgmental. For people who have been effectively excluded from the mental health system, that matters.These findings suggests that the people most helped by AI may not be the ones dominating the current public debate around it. Most people agree that AI therapy systems should not replace human therapy, but in many cases, the status quo they are replacing is “nothing”.A framework for doing this responsiblyThis doesn’t mean we should simply offload mental health support to general-purpose chatbots, like ChatGPT. Prior work has shown that chatbots can amplify narcissistic tendencies (through uncritical agreement with the user) and have the potential to influence vulnerable users who may be suffering from psychosis. The stakes in mental health are higher than in most other domains: In the worst case, a poorly functioning system could mishandle suicide risk. We therefore need a principled, critical approach to integrating AI into mental healthcare.Drawing on the analogy of autonomous vehicles, my colleagues and I have proposed a three-stage model. At the assistive stage, AI handles low-risk tasks – psychoeducation, activity planning and collecting behavioural logs – freeing therapists to focus on face-to-face work. At the collaborative stage, AI takes on more responsibility, such as scoring assessments or providing real-time feedback on therapy worksheets, but always under therapist oversight. A fully autonomous stage, where AI independently conducts assessments and delivers interventions, remains a distant and uncertain prospect.The central idea is that the systems should not advance to the next stage until they have shown they are completely safe in the prior stage – we wouldn’t trust a car to drive itself if it can’t park itself or stay in the same lane. To guide evaluation at each stage, we developed the READI framework (Readiness Evaluation for AI-Mental Health Deployment and Implementation). It specifies criteria for safety, privacy, equity, engagement, effectiveness and implementation. For example, a mental health chatbot should be able to detect suicidality and escalate this to human care. It should not be optimised for engagement (i.e. endless chatbot conversations) at the expense of patients getting better. And its effectiveness shouldn’t just be compared to doing nothing, but against existing treatments.Where AI may help most: training therapistsOne area where AI’s potential is especially promising, and the risks more manageable, is in the training of therapists. AI can make training more scalable and engaging by letting trainees practice real-world scenarios without needing real-world patients, much like a flight simulator. I was trained as a therapist myself, and wish that I had access to such tools to practice difficult situations with patients before encountering them for the first time in real life.For example, consider the treatment of post-traumatic stress disorder. There is a new and highly effective treatment for it, called written exposure therapy, which guides patients through five structured writing sessions to develop a trauma narrative. The treatment is cost‑efficient and effective. But training therapists in this method requires close supervision, and new therapists cannot be trained fast enough. We’ve been developing an AI coach that allows therapists to train with simulated patients, while an AI supervisor gives in-the-moment feedback. This way, the trainee gets realistic practice and has to think on their feet. So far, therapists have been loving the early versions of the tool.The bigger pictureWe are at an early stage of understanding how AI will reshape human psychology. The technology and its impact on society is developing faster than our ability to study it, yet hundreds of millions of people are already using it in ways that impact their mental health and emotional lives. Much of the public conversation has been shaped by fear. That fear is not unfounded, but it is also incomplete.The early evidence points to real opportunities: brief AI interactions that improve well-being, access to support for underserved populations, and better tools for training therapists. Realising these opportunities without causing harm will require careful evaluation, honest reporting of both positive and negative findings, and a willingness among psychologists, technologists and policymakers to work together. As with the training tools, my hope is that new AI tools can help us be better at being human for each other.AI isn’t ready to replace human therapists, but it’s already shaping mental health. Now, psychology’s task is to shape that impact wisely.]]></description>
                  <pubDate>Mon, 20 Apr 2026 00:15:07 +0000</pubDate>
                  <guid isPermaLink="false"> 48501 at https://knowledge.insead.edu</guid>
                  <comments> https://knowledge.insead.edu/responsibility/could-ai-tools-actually-help-us-feel-better#comments</comments>
                <enclosure url="https://knowledge.insead.edu/sites/knowledge/files/styles/panoramic_large/public/2026-03/aitools_mental_health.png?itok=cbriih6B" type="image/png" length="971268" /><dc:creator>Johannes Eichstaedt</dc:creator></item><item><title>How On‑Demand AI Assistance Undermines Learning</title>
                  <link>https://knowledge.insead.edu/responsibility/how-demand-ai-assistance-undermines-learning</link>
                  <description> <![CDATA[Imagine two students training with the same AI tutor. Both receive tips at key moments, but one can additionally request help whenever they want. Who learns more? In theory, giving students greater agency should increase engagement and active participation. However, in practice, without adequate self-regulation, students may become over-reliant on AI assistance – which could ultimately undermine learning.As AI tutoring tools provide personalised, on-demand support at an unprecedented scale, this has become one of the most fundamental questions in management education, employee training and student learning. I studied this with Hamsa Bastani from The Wharton School and Osbert Bastani from the University of Pennsylvania. We recruited over 200 chess students for a 12-week intensive AI-enabled training programme. Students were randomly assigned to either a system-regulated condition (in which the platform automatically provided AI tips at key moments) or a self-regulated condition (in which students could additionally request help at any time by clicking a button). The only difference between groups was access to this button.After 12 weeks, those who could request AI help at any time improved their performance by just 30 percent, compared to 64 percent for students in the system-regulated group. Students with on-demand AI access learned less than half as much, a remarkably large effect for such a subtle difference in system design. Even more striking, these students were fully aware of their over-reliance on AI yet continued to increase their use of it over time.These findings matter far beyond chess. As AI tools proliferate across schools and workplaces, from coding assistants to medical decision-support systems, users have unprecedented control over when they receive help. Our research suggests that even small differences in system design can have dramatic consequences for long-term human skill atrophy.Why self-regulated AI use hinders learningWhile some negative effect from the excessive use of AI assistance is expected, the magnitude demands explanation. Our analysis points to two potential mechanisms that amplified learning loss.First, on-demand AI assistance short-circuited productive struggle. Students in the self-regulated condition performed significantly better during training games, but this initial success came at the expense of long-term learning. When tested without AI assistance, they performed substantially worse than their counterparts who had struggled through difficult challenges on their own.The damage wasn't uniform across all types of assistance. Learning losses were driven specifically by students requesting assistance on problems within their “zone of proximal development” – problems that were challenging but feasible for their skill level. These are precisely the problems for which struggle, error and targeted feedback produce the greatest learning gains. By ​​bypassing this process with on-demand solutions, students deprived themselves of the very experiences that build expertise. Interestingly, requesting help on trivial problems (below their skill level) or highly complex ones (far beyond their abilities) had little impact on learning. The damage occurred specifically when AI assistance displaced productive struggle on appropriately challenging problems.Second, self-regulation reduced overall engagement. Students with on-demand access completed 24 percent fewer training games than their system-regulated peers. Our post-study surveys revealed why: Many reported that clicking the help button diminished their sense of accomplishment and made training feel less rewarding.Yet, despite this awareness, these same students increasingly relied on AI over time. In the first week of training, they requested help approximately five times per game. By week 12, this had more than doubled to 11 requests per game. Meanwhile, students in the system-regulated condition steadily improved, eventually closing the performance gap with their self-regulated peers.This pattern reveals a classic failure of self-regulation: short-term convenience overrides long-term goals, even when the trade-off is fully understood. Our chess students weren't naive about AI's risks; they were caught in an agency trap where immediate ease consistently won over future learning.When motivation matters (and when it doesn't)We explored whether student skill or motivation might moderate these effects. Common wisdom suggests that more skilled or motivated learners would be better equipped to self-regulate their use of AI assistance. Our findings tell a more nuanced story.Highly motivated students, those who reported spending more hours per week on chess prior to the study, experienced substantially smaller learning losses from self-regulated AI access. However, even among the most motivated students, on-demand assistance still reduced learning compared to system-regulated assistance. Skill or expertise, however, offers no such protection. Beginners and advanced players both fell into the over-reliance trap. This finding contradicts the prevailing view that expertise enables better self-regulated learning.The design implications are clear. Organisations deploying AI‑assisted learning and training systems should:Resist the urge to give users unlimited control. The intuition that more choice enables better learning can be wrong. Educational AI systems should algorithmically determine when to help based on what best supports learning by targeting moments when assistance accelerates learning rather than displaces it.Recognise that user awareness is not enough. Our students knew they were over-relying on AI but couldn’t help themselves. System design must account for the gap between intentions and behaviour. Don’t expect users to self-regulate effectively, even when they understand the risks.Consider the types of assistance provided. Our research suggests that what we call attention signals – alerts that flag important decisions without prescribing solutions – can encourage engagement without triggering over-reliance. These signals prompt learners to slow down and think carefully at critical moments while preserving the productive struggle essential for learning.Monitor engagement metrics alongside performance. In our study, students with on-demand AI access didn't just learn less, they also practiced less. Reduced engagement may be an early warning sign that assistance is undermining rather than supporting learning. Besides tracking when users are improving during training, track whether they remain motivated to train at all.Using AI doesn’t inevitably lead to skill atrophy. The risk arises specifically when assistance displaces productive struggle on appropriately challenging problems. By limiting AI assistance there, but allowing it freely elsewhere, productivity gains need not come at the cost of skill development.Beyond the classroomAI assistance, whether in software engineering or medicine, presents a double-edged sword for skill development. While it can help streamline workflows and free up cognitive resources, an over-reliance on AI for complex problem-solving is detrimental. If junior staffers habitually defer to AI-generated solutions for challenging cases, they risk failing to cultivate the fundamental reasoning skills required when these systems encounter unexpected problems or fail.As we integrate AI more deeply into education and training, we must design these systems with their long-term effects on human capability in mind. The chess students in our study were diligent learners with strong motivation to improve, training in a domain where AI assistance has been available for decades. If even these learners fall into the trap of over-reliance, the risks are likely far greater in contexts where motivation is lower, or users are less aware of AI's limitations.]]></description>
                  <pubDate>Tue, 17 Mar 2026 01:00:00 +0000</pubDate>
                  <guid isPermaLink="false"> 48451 at https://knowledge.insead.edu</guid>
                  <comments> https://knowledge.insead.edu/responsibility/how-demand-ai-assistance-undermines-learning#comments</comments>
                <enclosure url="https://knowledge.insead.edu/sites/knowledge/files/styles/panoramic_large/public/2026-03/shutterstock_2547509993.jpg?itok=tuwEkXFa" type="image/jpeg" length="818956" /><dc:creator>Stefanos Poulidis</dc:creator><dc:creator>Hamsa Bastani </dc:creator><dc:creator>Osbert Bastani</dc:creator></item><item><title>Four Mindsets That Undermine Workplace Well-Being Initiatives</title>
                  <link>https://knowledge.insead.edu/career/four-mindsets-undermine-workplace-well-being-initiatives</link>
                  <description> <![CDATA[Well-being – be it physical, mental, emotional or otherwise – is essential for a strong and productive workforce. According to a McKinsey Health Institute report, employers increasingly recognise that employee health and well-being are core to performance. Yet, many organisations struggle to find the right approach when it comes to implementing solutions that sustain both well-being and output.For over a decade, I’ve worked with multinational organisations to design and deploy well-being and mental health programmes. Based on these experiences, I’ve found that despite their best intentions, many leaders get tripped up by a few common mindsets. That’s not to say these perspectives are inherently flawed. It only becomes a problem when they are the sole lens through which things are viewed, causing other important aspects to be overlooked.Below, I elaborate on the ways of thinking leaders should avoid if they want to build sustainable and effective well-being programmes that catalyse real organisational change. I also offer practical suggestions for those ready to take these efforts seriously.Let’s “fix” them: overly individual-focusedIf an employee isn’t feeling well, a manager will likely suggest they take a day off. Some particularly empathetic managers may even grant short-term sick leave if they believe someone could benefit from a longer break, especially if that person is under intense stress or displaying symptoms of a mental health condition. “Perhaps they just need some time away,” their manager may think.This works if it’s part of a more holistic approach to employee well-being. However, if the only solution is sick leave or even providing access to free counselling services, the implicit message to employees is: This is an individual issue, so go and work on yourself and come back ready to work again. This approach focuses on addressing the symptoms, not the root causes. It neglects other factors that might be at play, including workload, resource distribution, time constraints and team culture and dynamics. The stress of transitional periods, such as adjusting to a different boss, organisational restructuring or new business strategies, can also affect well-being in ways beyond an individual’s control.Instead, managers could ask, “What else might be happening in the work environment to cause this employee distress?” before enacting the appropriate solutions, whether that’s extending a project deadline or designing a team intervention. As leaders, this is where you need to step in to examine and address the factors that might be compromising that person’s well-being, because no amount of sick leave or counselling sessions would ameliorate the situation. Let’s “change” them: overly short-term focusedAnother mental trap is thinking that simply changing someone’s working conditions will eradicate the problem. I’ve seen leaders spring into action – be it by moving an individual to a different team or reducing their workload – in the hopes of improving an employee’s well-being, sometimes inadvertently sending that person into a panic because they assumed their manager no longer trusted them.These actions are taken with good intentions and are often cited as best practices for workplace mental health. But they fail to consider one important thing: what the individual actually wants. What’s more, if the root of the problem is an organisational culture issue, such as harassment, bullying or a norm of toxic behaviour, then changing teams might offer some breathing space, but it won’t be long before the same negative patterns creep in again.Asking, “How do I involve and include the employee and others in decision-making?” is one way for leaders to escape this thinking trap and resist the bias towards action. Rather than rushing to implement change, leaders can take the time to speak directly with the employee to understand their concerns and preferences. It’s equally important to consult other managers across the organisation to determine whether this is an isolated incident or a pattern requiring broader behavioural change. Let’s “educate” them: overly surface-levelMost companies run some variation of well-being training and educational campaigns. These are foundational for building awareness, and I think they are a good first step to getting buy-in and destigmatising thorny topics like mental health and suicide. Classic formats include guest speaker series, World Mental Health Day events and sending managers to Mental Health First Aid training.These initiatives aren’t the problem. In fact, they are crucial. The issue arises if they’re all a company offers, or treated as a box-ticking exercise. Employees who attend these events tend to be self-selecting – often those who already know how to prioritise their mental health – which means that the people who need support the most may not be reached. Another challenge is that many of these initiatives primarily focus on building knowledge and delivering content, rather than establishing habits or longer-term follow-ups to support behavioural change.Instead of piecemeal initiatives, focus on your overarching well-being strategy. Think of workplace well-being as you would any long-term business strategy: Design it across one-, three- and five-year time horizons, with building blocks that compound over time instead of repeated topics repackaged under a new name. Give employees a clear view of the learning journey ahead. Borrowing strategies from leadership development, such as coaching, can also help translate newly gained knowledge into day-to-day behaviours. Let’s “do something”: overly siloedMany companies allocate a limited budget to well-being programmes, sometimes folding them into learning and development budgets and tacking them on to other training sessions. They may treat such initiatives as the purview of HR or the people and culture department, or as a theme that the communications or marketing teams can build on to boost camaraderie and staff spirit.Without meaningful human and financial support from cross-departmental leaders, the board of directors and the wider organisation, these programmes are unlikely to have their intended effect. Treating them as one-off projects wears out the teams responsible for delivery and, if no real change follows, employees may grow cynical and view these initiatives as a nuisance rather than helpful.To pave the way for sustainable change, leaders can ask themselves, “How do we embed well-being as a pillar of our business?” Well-being should be integrated into an organisation’s values and performance frameworks, and reflected in the behaviours modelled by leaders. This is where diverse perspectives are essential: Those making decisions about well-being strategies should include people with lived experience of various health conditions, ensuring that organisations don’t inadvertently sideline the very people they intend to support, nor design programmes that fail to speak to their needs.A comprehensive approachIf any of the above resonates, it may be worth pausing to reflect on whether your current approach to workplace well-being is truly the best way forward. Good intentions are a starting point, but they must be translated into something strategic and comprehensive. Here are some suggestions to get you started:Get your board of directors on board. Workplace mental health is a risk-management and sustainability issue for corporate governance. In many countries, directors have an obligation under local work and safety laws to ensure appropriate resources are in place to address such issues. A board that is interested in employee well-being will provide greater support to the organisation’s leaders and ensure accountability. Allocate an adequate, recurring budget to support your organisation’s long-term well-being strategy. People are the cornerstone of any workplace, and mentally fit employees are better equipped to adapt, remain agile and be productive amid inevitable business changes. Investing in your people should be no less a priority than investing in your latest product or service. Seek out your employees’ real experience. Metrics can be misleading, and many leaders place too much confidence in low utilisation rates of counselling hotlines or the absence of formal complaints as indicators of a healthy workplace. In reality, what gets reported and what is actually experienced can differ significantly. To close that gap, leaders need to create the conditions for honest conversations with employees and invest the time to listen without judgement.Treat well-being as a non-negotiable. Every employee should have access to foundational well-being development, which should carry at least the same weight as mandatory compliance, regulatory and data privacy training. These all serve the same ultimate purpose: the long-term sustainability of the organisation.By adopting a more holistic mindset, your well-being initiatives can move beyond surface-level gestures with fleeting impact – creating something that genuinely supports your people, strengthens your culture and delivers lasting and meaningful change.]]></description>
                  <pubDate>Thu, 26 Mar 2026 01:15:00 +0000</pubDate>
                  <guid isPermaLink="false"> 48411 at https://knowledge.insead.edu</guid>
                  <comments> https://knowledge.insead.edu/career/four-mindsets-undermine-workplace-well-being-initiatives#comments</comments>
                <enclosure url="https://knowledge.insead.edu/sites/knowledge/files/styles/panoramic_large/public/2026-03/shutterstock_2494647419.jpg?itok=NxOAUpcd" type="image/jpeg" length="1034892" /><dc:creator>Enoch Li</dc:creator></item><item><title>AI in Healthcare Diagnostics: Promises, Pitfalls and the Path Forward</title>
                  <link>https://knowledge.insead.edu/responsibility/ai-healthcare-diagnostics-promises-pitfalls-and-path-forward</link>
                  <description> <![CDATA[Whether it’s routine check-ups, emergency care or managing chronic illness, everyone relies on healthcare at some point in their lives. AI is no longer a future prospect in medicine; it’s already being used in hospitals to analyse medical images, assist with reading scans and support diagnostic decisions as part of routine clinical practice.Our research highlights how AI systems can operate at scale, flagging urgent abnormalities and enabling clinicians to make faster and, in some cases, more accurate diagnoses. In a sector as large and complex as healthcare, their adoption raises urgent questions not only for medicine, but for organisational design, ethics and trust.Transforming diagnostic practiceRadiology and pathology are uniquely suited to AI adoption due to their reliance on pattern recognition and image interpretation. In radiology, our research shows that AI trained on millions of scans can detect conditions such as tuberculosis, stroke, lung nodules and breast cancer at a level comparable to specialist clinicians. In pathology, AI systems can analyse digitised tissue slides to identify cancer cells, quantify biomarkers and prioritise cases requiring urgent review.In practice, these tools don’t replace clinicians but function as decision-support systems. AI models typically analyse images immediately after they’re taken, identifying potential abnormalities for review. A radiologist or pathologist remains responsible for issuing the final diagnostic report. This human-AI collaboration can significantly reduce reporting times and administrative burden, enabling clinicians to focus on complex decision-making and patient care.The impact is measurable. Our research shows that AI-assisted workflows have reduced stroke treatment delays from hours to minutes, accelerated tuberculosis detection in low-resource settings – such as high-density prison populations – and improved early cancer diagnosis. In health systems facing workforce shortages and rising demand, these efficiency gains aren’t merely convenient but are increasingly necessary.Beyond efficiency: organisational changeDespite its technical capabilities, AI’s success in healthcare depends as much on organisational design as on the models themselves. Introducing AI into a hospital isn’t simply a procurement decision; it requires redesigning workflows, redefining professional roles and building trust among clinicians.Research highlights how intelligent organisations aren’t merely defined by their ability to automate tasks, but by how effectively they combine the complementary strengths of humans and technology. AI excels at processing vast volumes of data quickly and consistently, while clinicians contribute contextual understanding, ethical judgment and accountability. When AI is positioned as an assistive tool, it can augment diagnostic accuracy and free professionals from repetitive tasks. When poorly integrated, it risks creating friction, mistrust and overreliance. Clinician acceptance is therefore critical to successful adoption. Concerns about job displacement, de-skilling and opaque decision-making remain significant barriers. Even highly accurate tools may be underused if they are difficult to interpret and poorly integrated into existing systems, or if they lack endorsement from senior clinicians. Effective leadership by individuals trained in “AI literacy” and transparent communication are essential to bridge the gap between AI adoption and sustained use in clinical workflows.Where AI falls shortWhile AI has demonstrated impressive performance under controlled conditions, real-world deployment exposes important limitations. One key risk is automation bias – the tendency for humans to over-trust algorithmic outputs. Incorrect AI suggestions can increase diagnostic errors, even among experienced clinicians, particularly when errors aren’t clearly signposted.In pathology, AI systems can be vulnerable to factors such as tissue contamination. Unlike human experts, who can recognise and disregard irrelevant material, AI models may misinterpret contaminants as clinically significant features.What’s more, many models are trained on historical medical data. When those datasets reflect long-standing inequalities in research and clinical practice, these disparities risk being reproduced at scale. Women, people from ethnic minority backgrounds and younger patients have historically been underrepresented in clinical trials, and patterns of bias in care have further shaped the data available for training AI systems. In practice, this can translate into underdiagnosis or delayed treatment for already underserved populations, amplifying existing health inequities. Ethical and legal accountabilityThe integration of AI into diagnostics complicates traditional notions of responsibility. In medicine, clinicians are morally and legally accountable for patient outcomes. When AI contributes to clinical decisions, accountability becomes distributed across clinicians, developers, institutions and regulators.Opacity in AI systems, often described as the “black box” problem, further complicates accountability. If clinicians can’t understand how an algorithm reached a conclusion, their ability to critically evaluate its output is diminished. This concern has influenced regulatory approaches. For example, the United States Food and Drug Administration has historically approved only so-called “locked” AI models that do not change after deployment, prioritising predictability over adaptability. While this stability supports safety and accountability, it also limits learning. Locked systems can’t adapt to new data or correct for emerging biases in real-world use. The challenge for healthcare leaders is to balance the need for reliable, auditable systems with the potential benefits of carefully governed adaptive AI. Globally, regulatory strategies vary. The European Union’s AI Act introduces risk-based obligations for healthcare AI, while the United Kingdom has adopted a more flexible, innovation-friendly approach through regulatory sandboxes – engaging firms to test products or services that challenge existing legal frameworks. These frameworks reflect an ongoing effort to balance patient safety, innovation and ethical responsibility. However, legal systems continue to lag behind technological progress, particularly in addressing harms related to bias or systemic design flaws.The path forwardAI has already begun to reshape the landscape of healthcare diagnostics, and avoiding it due to fear of error or liability risks forfeiting substantial benefits. The solution lies in responsible implementation: rigorous validation on diverse populations, continuous monitoring after deployment, clear accountability frameworks, transparency with clinicians and patients, and sustained human oversight.Ultimately, AI should be understood not as a replacement for clinical expertise, but as an intelligent partner. When embedded thoughtfully within organisational structures and guided by ethical principles, it can help reduce diagnostic error and support clinicians in their work. Governed by adaptive regulation, it also has the potential to extend specialist care to underserved populations and support more sustainable healthcare systems.The challenge for future healthcare leaders isn’t simply to adopt AI, but to design systems where humans and machines work together – safely, ethically and effectively – in the service of patient care.]]></description>
                  <pubDate>Mon, 02 Mar 2026 01:00:00 +0000</pubDate>
                  <guid isPermaLink="false"> 48381 at https://knowledge.insead.edu</guid>
                  <comments> https://knowledge.insead.edu/responsibility/ai-healthcare-diagnostics-promises-pitfalls-and-path-forward#comments</comments>
                <enclosure url="https://knowledge.insead.edu/sites/knowledge/files/styles/panoramic_large/public/2026-02/shutterstock_1627208287_1_1.jpg?itok=FadNn2e6" type="image/jpeg" length="207671" /><dc:creator>Sophie Delaye</dc:creator><dc:creator>N. Craig Smith</dc:creator></item><item><title>INSEAD Insights: Strong Cultures, Supply Chains and Surprise</title>
                  <link>https://knowledge.insead.edu/leadership-organisations/insead-insights-strong-cultures-supply-chains-and-surprise</link>
                  <description> <![CDATA[From understanding the role of surprise in organisations to finding ways to improve disease tracking and analysis, this month’s selection of recently published research by INSEAD faculty spans a diverse array of topics. Other papers explore how context shapes the effectiveness of fiscal rules; how market-based incentives can drive the energy transition; and how firms with less hierarchical structures manage to get their employees pulling in the same direction.The role of surprise in organisationsFrom Aristotle to Charles Darwin, surprise has been a topic of fascination and the source of many questions in philosophy, the social sciences and beyond. However, a history of inconsistent definitions and fragmented perspectives has led to conceptual confusion, limiting our understanding of how surprise affects individuals in organisations.In a paper published in the Journal of Applied Psychology, Spencer Harrison and his co-authors blend insights from psychology, management and other related fields to provide a comprehensive understanding of surprise in organisational contexts. They explore the cognitive and emotional mechanisms that underlie surprise and identify how key factors – such as organisational memory and emotional capabilities – shape how it is experienced and managed within organisations.Read the full paperImproving disease surveillance in Sub-Saharan AfricaPathogen genomic sequencing is central to disease surveillance, enabling laboratories to track the spread of diseases and inform public health responses. A study by Luk Van Wassenhove and his co-authors evaluates two types of donor interventions aimed at improving underdeveloped pathogen genomic sequencing supply chains in Sub-Saharan Africa: in-kind donations and supply chain management capability-building. The study, published in the International Journal of Operations & Production Management, revealed that although in-kind donations can mitigate acute shortages, frequent use risks creating dependency and suppressing learning. In contrast, supply chain management capability-building brings more sustainable improvements, particularly for laboratories that are unlikely to improve without external support.Read the full paperWell-designed fiscal rules are no silver bulletFiscal rules have been shown to improve government budget balances and restrain debt growth. But while they generally improve a country’s cyclically adjusted primary balance, their impact depends on both the time horizon and the context in which they are adopted, according to research by Antonio Fatás and his co-authors published in the Journal of International Money and Finance.In advanced economies and countries with strong political institutions, the effects strengthen over time. But in emerging markets and developing economies – especially those with weaker institutions – their impact tends to fade as time passes. This suggests that fiscal rules introduced during periods of economic hardship or under highly concentrated political power are often less effective in the medium term.Read the full paperHow firms redeploy assets in response to industry shocksHow should firms respond when a core industry experiences a downturn? Research by Aldona Kapačinskaitė, published in the Strategic Management Journal, examines how energy giants reacted to the 2014 oil price crash. Focusing on oil and gas companies that diversified into wind power, she shows that these firms reduced investment in oil and gas – especially in offshore projects – while increasing investment in wind power.Importantly, firms were more likely to invest in newer, higher-capacity wind technologies when these could be co-located with existing offshore oil and gas assets. This shows how firms facing industry shocks redeploy resources into more promising sectors. However, their willingness to do so may depend on the possibility of leveraging existing assets – meaning that market-based incentives alone may be insufficient to drive the switch to renewable energy sources.Read the full paperThe ties that bind less hierarchical firmsInstead of depending on traditional forms of managerial hierarchy to align the work of employees, can strong cultures – made up of systems of widely shared beliefs and values – do the job? To investigate this, Phanish Puranam and his co-author analysed 1.5 million Glassdoor employee reviews and 42 million professional social media profiles from 23,000 American firms.Their research, published in the Strategic Management Journal, found that organisations with stronger cultures do indeed have a lower proportion of managers to total employees. This suggests that attempts to flatten organisational hierarchies by eliminating layers of managers is more likely to succeed if accompanied by efforts to build strong cultures. This can be facilitated in various ways, including the careful selection and socialisation of employees.Read the full paper]]></description>
                  <pubDate>Mon, 16 Feb 2026 01:10:00 +0000</pubDate>
                  <guid isPermaLink="false"> 48336 at https://knowledge.insead.edu</guid>
                  <comments> https://knowledge.insead.edu/leadership-organisations/insead-insights-strong-cultures-supply-chains-and-surprise#comments</comments>
                <enclosure url="https://knowledge.insead.edu/sites/knowledge/files/styles/panoramic_large/public/2026-02/shutterstock_2100721102.jpg?itok=afP9-t-x" type="image/jpeg" length="1008987" /><dc:creator>Lily Fang</dc:creator></item><item><title>Diversity in the Workplace: An Unexpected Side-Effect</title>
                  <link>https://knowledge.insead.edu/responsibility/diversity-workplace-unexpected-side-effect</link>
                  <description> <![CDATA[It’s no secret that enthusiasm for DEI (diversity, equity and inclusion) programmes has waned in certain corners of the corporate world. Despite this, and although the jury is still out on diversity’s ultimate impact on a company’s financial performance, many still acknowledge that a diverse workforce yields important benefits.Prior research suggests that exposure to counter-stereotypically successful minority employees – those who defy social stereotypes about their group’s ability to thrive in professional settings – weakens prejudice in the workplace. This also applies to members of stereotyped groups: Seeing women in leadership roles, for example, can reduce women’s own beliefs about gender stereotypes, while Black Americans may exhibit less racial self-stereotyping after exposure to successful Black Americans.Counter-stereotypically successful minorities are generally viewed as having a positive impact on workplace perceptions, attitudes and behaviours. But in our research published in the Journal of Applied Psychology, my co-authors (Daniela Goya-Tocchetto from University at Buffalo and Shai Davidai) and I point to a potential drawback: The presence of such individuals can lead others to believe that an organisation is more diverse than it actually is, and so reduce their support for future diversity-enhancing policies.Standing out from the crowdAccording to the stereotype content model, women and racial minorities are often perceived as less competent than other social groups, and therefore less likely to achieve professional success. As a result, when individuals from these groups do succeed – for instance, by earning high salaries or holding senior leadership positions – they tend to stand out as particularly salient.This matters because people often rely on salience as a shortcut for judging prevalence, a process known as attribution substitution. A classic example is how the vividness of shark attacks leads people to believe they happen quite frequently. In reality, you’re more likely to be the victim of a lightning strike or fireworks.Because counter-stereotypically successful women and racial minorities tend to be highly visible in corporate settings, we hypothesised that their mere presence would inflate perceptions of organisational diversity. We further predicted that this effect would be weaker for individuals from minority groups stereotyped as highly competent (e.g. Asian Americans, which are considered a model minority in the United States). Finally, we expected inflated diversity perceptions to be associated with lower support for initiatives aimed at improving workplace diversity.Perception vs. realityWe tested these ideas across four studies. The first examined whether firms led by women CEOs were perceived as more gender diverse. We found that participants consistently overestimated the gender diversity of a firm’s board of directors when the CEO was a woman – an effect that didn’t appear when the CEO was a man.In our second study, conducted with US residents, we compared reactions to firms with either counter-stereotypically successful Black American employees or equally successful but non-counter-stereotypical Asian American employees. Although participants overestimated the share of non-White workers in both conditions, exposure to Black American employees led to significantly higher estimates of racial diversity. This suggests that the effect of being exposed to high-performing minorities on diversity perceptions is stronger when that success contradicts prevailing stereotypes.Our third and fourth studies investigated the downstream consequences of inflated diversity perceptions. In the third study, participants reviewed information about the gender composition of each quartile of a company’s pay distribution, then estimated the organisation’s overall gender composition. Participants overestimated the true level of gender diversity when women were more heavily represented in the top salary quartile. What's more, we discovered early evidence that exposure to counter-stereotypically successful women was associated with larger gender pay gaps within the firm.In the fourth study, participants were significantly more likely to overestimate the proportion of women employees in an organisation when the latter were successful (i.e. described as earning high salaries). This, in turn, reduced participants’ willingness to hire a woman for an open role.The impact of inflated diversity perceptionsPerceptions of diversity shape a wide range of outcomes, including support for policies aimed at increasing representation. Our findings suggest that organisations with counter-stereotypically successful women or racial minorities can be perceived as more diverse than they truly are. This can foster an unrealistically rosy view of diversity that may not only discourage organisations from addressing deeper, systemic workforce issues, but could also reduce support for initiatives such as hiring additional members of underrepresented groups.The implication is clear: Without careful attention, firms may inadvertently distort perceptions of diversity and undermine support for the very individuals they aim to advance. Our results also show that “quick fix” diversity strategies, like hiring a few counter-stereotypically high-performing minority employees, can undermine motivation to invest in longer-term solutions.How can organisations that are committed to building a genuinely diverse workforce navigate these risks? Prior research suggests that providing complete, accurate statistics on gender and racial pay gaps and overall representation can help offset the distortions created by counter-stereotypical exemplars and better align perceptions with reality. This is especially important at key decision-making points, such as when firms are considering new diversity policies or hiring practices, given that inflated diversity perceptions can undermine support for such initiatives.At the same time, leaders should be mindful that some well-intentioned efforts may backfire. For instance, excessive or highly performative messaging around diversity – be it via the company’s website or social media accounts – may cause fatigue or scepticism, ultimately reducing engagement rather than building it.Success is the solution, not the problemCrucially, the solution isn’t for outstanding minority professionals to downplay their achievements or feel responsible for the unintended consequences of their success. Rather, part of the problem has to do with scarcity. Despite progress, underrepresentation persists: Black employees hold only 8 percent of top executive roles in the most valuable US public corporations, and women account for just 11 percent of Fortune 500 CEOs. As long as women and racial minorities remain underrepresented in the upper ranks of organisations, their success will continue to stand out. But as more of these individuals move into senior roles, their presence is likely to become normalised and feel less exceptional. Stereotypes about their competence should weaken, reducing the risk that a few high-profile success stories distort diversity perceptions.In that sense, while our findings highlight an important bias, they also point to a hopeful possibility: As diversity in leadership gets more common, it may also become less remarkable – laying the groundwork for broader acceptance and more equitable, inclusive organisations.]]></description>
                  <pubDate>Thu, 19 Feb 2026 02:20:00 +0000</pubDate>
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                  <comments> https://knowledge.insead.edu/responsibility/diversity-workplace-unexpected-side-effect#comments</comments>
                <enclosure url="https://knowledge.insead.edu/sites/knowledge/files/styles/panoramic_large/public/2026-02/shutterstock_2659422195.jpg?itok=d0RDrYXe" type="image/jpeg" length="993183" /><dc:creator>Asher Lawson</dc:creator></item>
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