Our conversation revolved around a deceptively simple but profoundly important question:

How can India avoid the social shocks of the Industrial Revolution while fully harnessing the transformative power of Artificial Intelligence?

The answer, as our discussion unfolded, lay not simply in developing better AI, but in building better institutions around it.

Learning from the First Industrial Revolution

As the 2025 Nobel Laureate in Economic Sciences, economic historian Joel Mokyr reminds us in The Lever of Riches, technological creativity has been the principal engine of economic progress throughout human history. Yet history also teaches us that technological revolutions generate shared prosperity only when they are accompanied by institutions that enable innovation to flourish and its benefits to be broadly distributed The Industrial Revolution represented perhaps the most dramatic expression of this creative force, transforming how societies produced goods, organized work, generated wealth, and interacted with the world.

Building on this perspective, Robert C. Allen, in The British Industrial Revolution in Global Perspective, argues that Britain’s industrial take-off was not accidental. It emerged from a unique combination of technological ingenuity, entrepreneurial enterprise, abundant energy resources, favourable institutions, and economic incentives. Together, these conditions enabled mechanization to move production from dispersed workshops into factories, creating economies of scale that fundamentally altered the organization of business and society.

The economic gains were extraordinary. Mechanized manufacturing dramatically increased productivity, lowered production costs, expanded trade, stimulated financial markets, and gave rise to modern corporations. Yet the transformation also came at considerable human cost. Traditional artisans and cottage industries declined as machines replaced manual craftsmanship. Millions migrated into rapidly growing industrial cities where overcrowding, poor sanitation, unsafe working conditions, child labour, and widening inequality became defining features of early industrial society.

The first century of industrialization illustrates an enduring paradox: technology creates wealth, but it does not automatically create shared prosperity. The remarkable productivity gains of industrialization accrued unevenly, benefiting factory owners and investors long before they improved the lives of ordinary workers. Only after decades of social and political struggle did governments introduce labour legislation, public education, factory regulation, public health systems, and other institutional reforms that enabled the gains of industrialization to be more broadly shared.

This lesson remains profoundly relevant today. Every technological revolution requires a parallel process of institutional innovation. New technologies reshape economies, but new institutions determine whether those transformations ultimately strengthen or weaken society.

India’s Experience: A Different Historical Trajectory

India’s encounter with industrialization followed a very different path. As economic historian Tirthankar Roy observes, India’s nineteenth-century experience unfolded largely under colonial rule, integrating the country into the global economy primarily as a supplier of raw materials and a market for British manufactured goods. While investments in railways, ports, telegraphs, and modern administration transformed infrastructure and connected India to global markets, many of its celebrated handicraft and textile industries suffered a prolonged decline.

Yet India’s story is not merely one of deindustrialization. The late nineteenth and early twentieth centuries also witnessed the emergence of visionary Indian industrialists such as Jamsetji Tata, whose enterprises laid the foundations of indigenous industrial development. India’s economic history therefore demonstrates both the disruptive consequences of technological and institutional change and the remarkable capacity of entrepreneurial leadership to create new pathways of growth and opportunity.

This historical perspective offers an important insight for the present. Technological revolutions are never solely about machines or inventions; they are equally about the institutions, policies, entrepreneurs, and educational systems that determine who benefits from innovation.

India’s AI Moment

It is precisely this historical lens that makes Ravi Venkatesan’s perspective so compelling. He argues that India stands today at a moment comparable in significance to the Industrial Revolution—not because AI will simply automate existing work, but because it has the potential to reshape the country’s developmental trajectory.

For Venkatesan, however, the opportunity is accompanied by an equally significant responsibility. History teaches us that technological revolutions do not automatically produce equitable outcomes. Left entirely to market forces, they often concentrate wealth, widen inequalities, and erode the pathways through which ordinary people improve their lives. The challenge before India is therefore not merely to become an AI leader, but to ensure that AI becomes a force for inclusive prosperity, entrepreneurship, and social mobility.

As our conversation progressed, one idea emerged repeatedly as the central thread connecting technology, markets, education, and public policy: the need to preserve—and indeed strengthen—the mobility ladder. Every generation must be able to climb higher than the one before it. If AI removes the first rungs of that ladder by eliminating entry-level opportunities without creating new ones, it risks undermining not only employment but aspiration itself.

This insight provided the foundation for the rest of our discussion. The challenge of India’s AI moment is not simply technological; it is institutional. The question is no longer whether AI will transform society, but how society chooses to shape AI.

That question led naturally to our next discussion: Can markets alone ensure that AI benefits everyone, or must governments, businesses, educational institutions, and civil society collectively redesign the institutions that govern technological change?

How do we ensure that AI strengthens rather than weakens the mobility ladder?

Markets, Institutions, and the Mobility Ladder

History teaches us that technological revolutions do not fail because of technology. They falter when societies fail to adapt their institutions to new technological realities. The Industrial Revolution was not simply an engineering revolution; it was ultimately an institutional revolution. Labour laws, compulsory education, public health systems, financial institutions, and modern corporations evolved alongside new technologies, enabling industrial societies to convert productivity gains into broader social prosperity.

AI presents India with a similar institutional challenge.

When I asked Ravi Venkatesan what worried him most about India’s AI future, his answer was immediate. The greatest danger, he argued, was not artificial intelligence itself but our assumptions about how its benefits will be distributed.

“There are two major risks,” he observed. “The first is that we assume markets alone will do the right thing.”

This is not an argument against markets. Throughout history, markets have been among humanity’s most powerful engines of innovation, entrepreneurship, and economic growth. But, as Nobel Laureate Joseph Stiglitz argues in The Price of Inequality, is not an inevitable result of free market forces. Instead, it is a deliberate consequence of political decisions, regulations, and market distortions created by moneyed interests. Markets do not operate in isolation. Their outcomes are shaped by laws, institutions, incentives, and public policy. Left entirely to themselves, markets are remarkably efficient at generating wealth, but far less reliable at determining how that wealth is distributed.

Ravi expressed a similar concern in practical terms. Companies adopting AI will naturally seek greater productivity and profitability. Unless appropriate incentives and safeguards exist, they may capture most of the productivity gains while transferring the costs of workforce transition onto workers, communities, and governments. Reskilling displaced employees, financing social protection, and supporting new livelihoods cannot simply become society’s burden while shareholders capture the rewards of automation.

This perspective aligns closely with Mariana Mazzucato’s influential argument that governments are not merely regulators correcting market failures after the fact. In The Entrepreneurial State, she demonstrates that many of today’s foundational technologies—from the Internet and GPS to touchscreen interfaces and biotechnology—originated through sustained public investment long before private markets recognized their commercial value. Markets, she argues, are not simply discovered; they are actively created and shaped through institutions, public investment, and long-term policy.

If Stiglitz reminds us that markets alone cannot guarantee equitable outcomes, Mazzucato shows that governments have an essential role in shaping innovation ecosystems. Together, their work suggests that India’s AI future cannot be left either to the state or to the market alone. It requires an active partnership between government, business, academia, and civil society.

Extending this line of thinking, Daron Acemoglu and Simon Johnson (2023) argue in Power and Progress that technological progress has no predetermined social outcome. The critical question is not whether technology advances, but whose interests it serves, who captures its benefits, and how its gains are distributed. Throughout history, societies that successfully translated innovation into shared prosperity were those that developed institutions capable of directing technological change toward the public good.

Taken together, these scholars offer a powerful progression of ideas. Stiglitz reminds us that markets alone do not produce equitable outcomes. Mazzucato demonstrates that governments actively shape markets and innovation. Brynjolfsson cautions that market incentives can direct AI toward replacing rather than empowering people. Acemoglu and Johnson conclude that institutions ultimately determine whether technology deepens inequality or broadens prosperity.

The central lesson is therefore clear: innovation creates wealth, but institutions determine how that wealth is created, governed, and shared.

The deeper challenge posed by every technological revolution is not simply whether it increases productivity and national wealth, but whether it preserves and strengthens the ladder of social and economic mobility. Throughout history, technological progress has expanded opportunities for many while simultaneously leaving others behind. When innovation disproportionately rewards those who already possess capital, education, or digital capabilities, the rungs of the mobility ladder become increasingly difficult to climb. Left unchecked, technological revolutions risk creating societies in which prosperity becomes more concentrated and upward mobility more elusive.

The real test of public policy is therefore not merely to maximize innovation but to ensure that technological progress expands opportunity rather than narrows it. The objective is not to slow innovation or suppress markets, but to build institutions that keep the ladder of opportunity sturdy, accessible, and inclusive. Investments in education, skills, digital public infrastructure, competition policy, entrepreneurship, and social protection are not simply redistributive measures; they are investments in preserving the pathways through which individuals and communities can improve their lives.

Escaping the Turing Trap

The conversation then turned to a more subtle but equally important challenge.

Drawing on the work of Erik Brynjolfsson, Ravi cautioned against what Brynjolfsson calls the “Turing Trap.” For decades, artificial intelligence has largely been evaluated by its ability to imitate human intelligence—to pass Alan Turing’s famous test by performing tasks previously associated with human cognition. The unintended consequence, Brynjolfsson argues, is that innovation becomes disproportionately directed toward automation—building machines that replace people—rather than toward augmentation, where intelligent systems enhance human capabilities.

This distinction is especially important for India.

If AI is deployed primarily to eliminate jobs, it risks widening inequality and weakening the very pathways through which millions aspire to improve their lives. But if AI is designed to complement workers—to make farmers more productive, artisans more competitive, teachers more effective, nurses more capable, and entrepreneurs more innovative—it can dramatically expand human potential.

For Ravi, this is not merely a technological choice. It is a societal choice. The question is not whether AI becomes more intelligent, but whether it makes people more capable.

The Threat of Mobility Collapse

Perhaps the most compelling idea to emerge during our conversation was Ravi’s concern about what might be called a “mobility collapse.”

Every successful economy depends upon a functioning mobility ladder—the set of educational, occupational, and entrepreneurial pathways through which individuals improve their economic circumstances across generations. India’s information technology revolution created precisely such a ladder. For several decades, millions of young Indians from modest backgrounds entered engineering colleges, acquired software skills, joined the IT industry, and moved into the middle class. Technology became not merely a source of employment but an engine of aspiration.

AI now threatens to alter that equation.

Many of the entry-level knowledge jobs that traditionally served as the first rungs of the mobility ladder—software coding, customer support, routine financial analysis, legal research, and documentation—are among those most susceptible to AI-assisted automation. If these entry points disappear before new opportunities emerge, India risks weakening one of the most powerful engines of upward mobility in its modern history.

This concern extends beyond employment statistics. It touches something deeper: hope. A society flourishes when each generation believes that effort, education, and enterprise can lead to a better future. If young people begin to perceive that the traditional routes to advancement are disappearing, the consequences are not merely economic; they are social, psychological, and political.

This insight echoes the work of economist Raj Chetty, whose research on intergenerational mobility demonstrates that the long-term health of an economy depends not only on the wealth it generates but also on the opportunities it creates for individuals to move upward. Prosperity is sustainable only when people believe that the ladder of opportunity remains open and accessible. In 2020, in collaboration with the U.S. Census, Chetty worked with Hendren and Friedman to construct the Opportunity Atlas.

For Ravi, preserving that ladder is the defining policy challenge of India’s AI moment.

Learning Faster Than History

The Industrial Revolution eventually corrected many of its excesses, but only after nearly a century of hardship. Labour rights were recognized. Factory legislation improved working conditions. Child labour was restricted. Public health systems expanded. Universal education became a societal priority. These institutional innovations ensured that the benefits of industrialization gradually reached much larger sections of society.

Ravi argues that India cannot afford to repeat that timeline.

“We have to learn in ten years what history took a hundred years to learn.”

That means anticipating disruption rather than merely reacting to it. It means redesigning education before careers disappear. It means building digital infrastructure before inequalities widen. It means creating mechanisms for reskilling before displacement becomes widespread. And it means ensuring that businesses, governments, and educational institutions share responsibility for managing technological transitions rather than leaving individuals to bear the burden alone.

The challenge is therefore not to slow technological progress but to accelerate institutional adaptation.

Yet institutional reform alone is not enough. Even if governments regulate wisely and businesses behave responsibly, a deeper question remains.

How can millions of ordinary Indians become active participants in creating the AI economy rather than merely adapting to it?

That question led our conversation toward an idea that lies at the centre of Ravi Venkatesan’s life’s work—and one that echoes Nobel Laureate Edmund Phelps’s vision of mass innovation.

From Mobility to Mass Innovation and Human Flourishing

If preserving the mobility ladder is the central challenge of India’s AI moment, the next question is even more fundamental:

How do we create millions of new opportunities rather than merely protect existing ones?

For Ravi Venkatesan, the answer lies not in slowing technological change, nor in attempting to preserve jobs that technology will inevitably transform. Instead, it lies in expanding society’s capacity to innovate. Prosperity, he argues, must be created by enabling millions of people to become entrepreneurs, problem-solvers, innovators, and value creators.

This idea finds a powerful intellectual foundation in the work of Nobel Laureate Edmund Phelps. In Mass Flourishing, Phelps challenges the conventional belief that economic progress is driven primarily by a handful of exceptional inventors or breakthrough technologies. Instead, he argues that the world’s most prosperous societies are those in which innovation becomes widespread rather than concentrated—where ordinary people across every sector of society are encouraged to experiment, improve products and processes, identify opportunities, and create new enterprises.

Prosperity, in other words, is not simply the result of technological breakthroughs; it emerges when innovation becomes part of the culture of a society.

For Ravi, this insight is especially relevant to India.

The country’s greatest opportunity is not merely to produce world-class AI researchers or globally competitive technology companies. It is to create conditions in which millions of ordinary Indians use AI to solve everyday problems, build businesses, improve productivity, and create livelihoods.

The question, he suggests, is not:

“How many AI engineers can India produce?”

but rather,

“How many AI-enabled entrepreneurs can India empower?”

That subtle shift transforms AI from a technology agenda into a societal agenda.

Mass Entrepreneurship: Democratizing Innovation

This philosophy lies at the heart of the Global Alliance for Mass Entrepreneurship (GAME), an initiative Ravi chairs.

Unlike conventional entrepreneurship programs that celebrate a relatively small number of high-growth start-ups, GAME focuses on enabling millions of micro and small entrepreneurs across India. Its objective is simple but ambitious: to make entrepreneurship an accessible pathway for ordinary citizens rather than an opportunity reserved for a privileged few.

This vision complements Phelps’ idea of mass innovation perfectly. Innovation is no longer viewed as something that happens exclusively in research laboratories or technology companies. It also occurs in neighborhood workshops, family businesses, rural enterprises, women’s self-help groups, farms, artisan communities, and local service businesses. Every improvement in productivity, every new customer reached, every better product designed, and every enterprise sustained contributes to the broader innovation ecosystem.

AI has the potential to democratize this process even further.

During our conversation, Ravi described how GAME is already experimenting with AI tools among nearly one lakh women-owned micro-enterprises. Activities that previously required weeks of effort—writing product descriptions, generating images, translating content, pricing products, or creating online catalogues—can now be completed within hours using generative AI. Delivered through familiar platforms such as WhatsApp and increasingly through voice interfaces in Indian languages, these technologies dramatically lower the barriers to entrepreneurship.

For these entrepreneurs, AI is not replacing work. It is creating capability.

It enables a small business owner with limited formal education to perform tasks that previously required professional marketing agencies, designers, translators, or consultants. AI thus becomes a force multiplier, extending human capability rather than substituting for it.

In this sense, the debate shifts decisively away from automation versus employment towards augmentation and empowerment.

Building an AI Society, Not Just an AI Industry

This distinction is critical. Many countries measure AI success through metrics such as research publications, patents, unicorns, investment flows, or foundation models.While important, Ravi believes these are incomplete measures of national success.

The more meaningful question is whether AI enables broad-based participation in economic growth.

• Can a farmer use AI to improve crop yields?
• Can an ASHA worker deliver better healthcare?
• Can a schoolteacher personalize learning?
• Can a street vendor understand customer demand?
• Can a rural artisan reach global markets?
• Can a small manufacturer compete more effectively?
• Can a young graduate from a Tier-3 town create a business rather than wait endlessly for a formal job?
• If the answer to these questions is yes, AI becomes not merely an engine of productivity but an instrument of social mobility.
• This is where India’s experience with Digital Public Infrastructure (DPI) offers an extraordinary advantage.

Over the past decade, India has built one of the world’s most extensive public digital infrastructures through Aadhaar, UPI, DigiLocker, Account Aggregator, and the broader India Stack. These platforms dramatically reduced the cost of identity, payments, and digital transactions, enabling hundreds of millions of citizens to participate in the digital economy.

Ravi argues that India now needs a comparable AI Stack—a public digital infrastructure that makes trustworthy AI capabilities accessible to everyone, not just large corporations. Just as UPI democratized digital payments, an AI Stack could democratize access to intelligence itself, allowing farmers, teachers, healthcare workers, artisans, and small entrepreneurs to harness AI as a tool for productivity and innovation.

The objective is not merely to build more sophisticated AI systems. It is to build an AI society.

Towards Human Flourishing

Underlying Ravi’s vision is a much deeper philosophical idea. Economic development should ultimately be judged not by GDP alone, but by whether people are able to live more creative, meaningful, productive, and fulfilling lives. This brings the conversation back to Edmund Phelps.

For Phelps, flourishing is not synonymous with consumption or material prosperity. It reflects the satisfaction people derive from solving problems, exercising creativity, building enterprises, contributing to society, and experiencing purpose in their work. Innovation matters not simply because it creates wealth, but because it enables individuals to realize their potential.

Ravi sees AI as an opportunity to expand that possibility.

If deployed wisely, AI can reduce drudgery, amplify creativity, democratize knowledge, and enable millions of people to participate more fully in economic and social life. But this outcome is not inevitable. It depends on the choices societies make about technology, institutions, education, and entrepreneurship.

It also requires a new kind of collaboration. Governments must build enabling policies and digital public infrastructure. Businesses must invest in responsible innovation and workforce transitions. Universities must cultivate creativity, judgment, adaptability, and entrepreneurial thinking. Civil society must ensure that the benefits of AI reach those traditionally excluded from technological revolutions. Only when these actors work together does technology become a catalyst for human flourishing rather than merely economic efficiency.

As our conversation drew to a close, it became clear that Ravi was describing something much larger than an AI strategy.

He was describing a new social compact—a formal agreement or shared commitment among governments, businesses, and communities to achieve common social goals, such as reducing poverty or improving education.

A compact in which technological progress is measured not only by the intelligence of machines, but by the opportunities created for people.

The conversation therefore arrived at its final and perhaps most important question:

If mass innovation and mass entrepreneurship are to become the engines of inclusive prosperity, what kind of education will prepare people to thrive in such a world?

Reimagining Education for Human Flourishing

If mass innovation and mass entrepreneurship are to become the engines of inclusive prosperity, one institution assumes unparalleled importance: education.

Throughout history, education has been the great engine of social mobility. It has enabled individuals born into modest circumstances to acquire knowledge, develop capabilities, and improve their lives. During the Industrial Revolution, compulsory education became one of the most significant institutional innovations, equipping successive generations with the skills required for an industrial economy and ensuring that economic progress translated into broader social advancement.

The AI Revolution demands an equally fundamental rethinking.

For nearly two centuries, education systems around the world have largely reflected the needs of the Industrial Age. Their implicit social contract was straightforward: acquire an education, secure stable employment, and build a lifelong career. Increasingly, that promise no longer holds.

The twenty-first century is characterised by what leadership scholars describe as a VUCA world—a concept introduced by the U.S. Army War College in the early 1990s to describe environments marked by Volatility, Uncertainty, Complexity, and Ambiguity. In such a world, knowledge rapidly becomes obsolete, occupations evolve continuously, and careers become increasingly non-linear. Success depends less on mastering static bodies of knowledge than on the ability to adapt, reinvent oneself, and continue learning throughout life.

Education must therefore move beyond preparing students for their first job. It must prepare them for their fifth career. This changing reality has prompted scholars around the world to rethink the very purpose of education.

Klaus Schwab, in The Fourth Industrial Revolution, argues that the convergence of digital, biological, and physical technologies is transforming every industry and every profession. As routine cognitive and physical tasks become increasingly automated, the capabilities that distinguish human beings—creativity, ethical judgment, systems thinking, empathy, collaboration, and leadership—become even more valuable.

Similarly, Yuval Noah Harari argues that because nobody can predict what the labour market will look like twenty or thirty years from now, education should place far greater emphasis on cultivating curiosity, resilience, creativity, critical thinking, communication, and emotional intelligence. The greatest challenge facing future generations, he suggests, is not merely learning new skills but continually reinventing themselves.

Building on these ideas, Joseph Aoun, President Emeritus of Northeastern University, proposes a new educational paradigm that he calls Humanics, in his book Robot-Proof. In a world increasingly shaped by artificial intelligence, Aoun argues, education must integrate three complementary literacies: technological literacy, data literacy, and human literacy. Together, these prepare graduates not merely to use intelligent technologies but to collaborate with them—to combine computational power with human imagination, ethical reasoning, empathy, and leadership.

This vision aligns closely with Ravi Venkatesan’s own perspective.

Throughout our conversation, he repeatedly returned to a simple but profound observation: the traditional idea of education leading to a stable lifelong career is rapidly disappearing. That does not imply a future with fewer opportunities. It implies a future with different opportunities.

Young people must therefore learn not only how to solve problems but how to identify them; not only how to seek employment but how to create it; not only how to adapt to change but how to lead it.

Entrepreneurial thinking, in this context, extends far beyond creating start-ups. It is fundamentally a mindset—characterised by curiosity, experimentation, resilience, opportunity recognition, responsible risk-taking, and the confidence to create value under conditions of uncertainty. Whether one becomes an entrepreneur, engineer, teacher, doctor, policymaker, artist, or scientist, these qualities will increasingly define success.

Equally important is the need to restore dignity to vocational and skilled work. Ravi observed that while artificial intelligence may transform many knowledge-intensive occupations, society will continue to depend upon skilled electricians, plumbers, technicians, healthcare workers, artisans, and countless other professionals whose work combines technical competence with human judgment. Educational systems must therefore move beyond outdated hierarchies that privilege certain professions over others and instead recognise the equal dignity and economic value of diverse forms of skilled work.

Recent evidence supports this shift. The World Economic Forum’s Future of Jobs Report 2025 identifies analytical thinking, creativity, resilience, curiosity, leadership, technological literacy, and lifelong learning among the fastest-growing capabilities required in the AI era. These are not merely employability skills; they are the foundations of adaptability in a world of continuous disruption.

This broader vision of education naturally leads to a larger institutional question.

If India is to democratize AI, foster mass innovation, strengthen the mobility ladder, and enable widespread entrepreneurship, who will help orchestrate this transformation?

Ravi’s answer is both ambitious and pragmatic.

He proposes the creation of an Institute for Human Flourishing—a national capability centre that would bring together government, academia, industry, philanthropy, and civil society to accelerate India’s transition into the AI age. Rather than functioning as another educational institution, it would serve as a catalyst for institutional innovation itself: helping businesses navigate workforce transitions, supporting the adoption of AI among small enterprises, strengthening entrepreneurship ecosystems, promoting responsible AI, and ensuring that technological progress translates into broader societal well-being.

The proposal reflects the central lesson running through our entire conversation.

Every technological revolution ultimately becomes an institutional revolution.

The Industrial Revolution gave rise to public education, labour rights, public health systems, modern corporations, and social welfare institutions. The AI Revolution calls for a similarly imaginative redesign of our institutions—not simply to regulate technology, but to ensure that technology expands human capability and opportunity.

Epilogue: Making It Happen

Looking back on our conversation, I was struck by how consistently one theme resurfaced. This was never simply a discussion about artificial intelligence. Nor was it merely a conversation about technology policy. At its heart, it was a conversation about human agency. History does not determine our future. Technology does not determine our future. Markets alone do not determine our future. Societies do.

The Industrial Revolution teaches us that technological innovation can generate extraordinary prosperity while simultaneously creating profound inequality. The lesson for the AI age is not to fear innovation, nor to slow it, but to shape it deliberately through enlightened institutions, inclusive markets, responsible businesses, entrepreneurial ecosystems, and education systems designed for lifelong adaptability.

The measure of India’s AI success will therefore not be the number of foundation models it builds, the billions invested in AI start-ups, or even the patents it generates.

• It will be whether AI strengthens the mobility ladder.
• Whether it enables a farmer to become more productive.
• Whether it empowers a woman entrepreneur to reach new markets.
• Whether it allows a graduate from a small town to build a business rather than wait for a job.
• Whether it creates opportunities for millions—not just for a privileged few.

That, ultimately, is the promise of mass innovation, mass entrepreneurship, and human flourishing.

As our conversation concluded, Ravi left me with a sentence that, in many ways, captures the spirit of this entire essay:

“We have to make it happen.”

Those five words remind us that the future of AI is not something that will simply unfold before us. It is something we must consciously create.

References

• Acemoglu, D., & Johnson, S. (2023). Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity. PublicAffairs.
• Allen, R. C. (2009). The British Industrial Revolution in Global Perspective. Cambridge University Press.
• Aoun, J. E. (2017). Robot-Proof: Higher Education in the Age of Artificial Intelligence. MIT Press.
• Bennett, N., & Lemoine, G. J. (2014). “What VUCA Really Means for You.” Harvard Business Review, 92(1/2), 27.
• Brynjolfsson, E. (2022). “The Turing Trap: The Promise and Peril of Human-Like Artificial Intelligence.” Daedalus, 151(2), 272–287.
• Harari, Y. N. (2018). 21 Lessons for the 21st Century. Jonathan Cape.
• Mazzucato, M. (2013). The Entrepreneurial State. Anthem Press.
• Mokyr, J. (1990). The Lever of Riches. Oxford University Press.
• Roy, T. (2020). The Economic History of India, 1857–2010 (3rd ed.). Oxford University Press.
• Schwab, K. (2016). The Fourth Industrial Revolution. World Economic Forum.
• Stiglitz, J. E. (2012). The Price of Inequality. W. W. Norton.
• World Economic Forum. (2025). The Future of Jobs Report 2025.