A coalition of over two hundred researchers and economists, spanning academia, artificial intelligence companies and policy circles, has made an urgent appeal to world governments and technology leaders to establish frameworks addressing the profound economic consequences of artificial intelligence. The statement, released this week, brings together fifteen Nobel Prize winners alongside researchers from frontier AI organisations OpenAI, Anthropic and Google, creating a rare convergence of voices demanding immediate institutional and policy responses to what they characterise as an unprecedented economic transition.
The signatories warn that artificial intelligence represents a transformation of economic scale comparable to the Industrial Revolution, yet compressed into a vastly shorter timeframe. Unlike previous technological upheavals that unfolded across generations, allowing societies extended periods for workforce adaptation and institutional evolution, AI development may force comparable or greater economic restructuring within merely years rather than decades. This acceleration creates acute challenges for labour markets, corporate strategies and the public institutions responsible for managing social welfare and economic stability.
The underlying concern centres on the velocity mismatch between technological change and societal adaptation capacity. Historical technological revolutions—the steam engine, electricity, computing—each granted societies roughly a decade or more to adjust employment patterns, retrain workers and recalibrate economic policy. AI's trajectory suggests no such luxury. This compressed timeline fundamentally alters the stakes for policymakers, who typically operate on longer planning horizons and must navigate political constraints that slow institutional change.
Anton Korinek, an economics professor at the University of Virginia and organiser of the initiative, articulated the core risk with particular force. "Steam, electricity, and computers each gave societies decades to adapt. AI may give us only a few years," he stated, emphasising that improvisation during transformation carries unacceptable costs. Waiting for complete certainty about AI's impacts, he argued, guarantees arriving at policy solutions too late to prevent severe disruption. This framing rejects the familiar argument that nations should observe technological change before responding, instead positioning proactive governance as essential.
Korinek, who joined Anthropic's economic research division in March, coordinated the statement with fellow economists Erik Brynjolfsson, Ajay Agrawal and Tom Cunningham. This partnership between academic researchers and those embedded within AI laboratories reflects an emerging recognition that understanding AI's economic effects requires collaboration across traditional institutional boundaries. Anthropic's decision to expand economic research capacity signals growing awareness within leading AI companies that their technologies carry consequences extending far beyond technical performance metrics.
The statement prioritises three interconnected objectives. First, it calls for substantially increased research into AI's economic ramifications, moving beyond speculation toward evidence-based understanding of displacement patterns, wage pressure, capital reallocation and sectoral disruption. Second, it demands proactive institutional development, arguing that existing regulatory structures, labour frameworks and social safety nets were architected for previous technological environments. Third, it insists on policy construction informed by potential risks including large-scale job displacement, concentrated economic gains and systemic inequalities.
Notable signatories include Sarah Friar, Chief Financial Officer of OpenAI; Jeff Dean, Chief Scientist at Google DeepMind; and Jack Clark, Anthropic co-founder. Their participation demonstrates that senior figures within AI companies themselves acknowledge the urgency of addressing economic externalities their technologies generate. Including economists embedded within these firms alongside external researchers creates potential for translating policy recommendations into corporate practices that might mitigate harmful outcomes.
Among the Nobel laureates backing the initiative are Michael Spence, Daron Acemoglu and Simon Johnson, economists renowned for analysing technological change, institutional development and inequality. Their involvement carries particular weight given their scholarship on how societies manage transformative economic transitions and the critical role institutions play in determining whether technological progress generates broad-based prosperity or concentrated advantage.
For Malaysia and Southeast Asia, this initiative carries specific relevance. The region's emerging tech sectors and manufacturing bases face particular vulnerability to AI-driven automation, while labour-intensive industries that employ millions remain inadequately protected by existing social safety mechanisms. The call for urgent policy development aligns with regional interests in ensuring that AI adoption enhances rather than undermines development trajectories. The coalition's emphasis on research into AI's concrete economic impacts addresses a critical knowledge gap in developing economies, where sophisticated economic modelling of technological disruption remains limited.
The statement effectively challenges the narrative of inevitability that often surrounds AI deployment, asserting instead that deliberate institutional choices will determine outcomes. Whether societies experience inclusive or extractive AI transitions depends substantially on policy decisions made in coming years. This framing demands immediate action rather than continued observation, positioning governments and multilateral institutions as active agents capable of shaping technological outcomes rather than passive recipients of technological change.
The coalition's emergence reflects deepening concerns among economists and technologists that current institutional responses remain dangerously inadequate. By assembling this broad coalition and issuing a public statement, these figures are attempting to break through the inertia that typically delays policy responses to emerging challenges. Their success in generating concrete policy responses, however, remains uncertain and will depend on whether governments prioritise economic security and inclusion as central considerations when developing AI governance frameworks.
