Economists and AI Experts Urge Global Leaders to Prepare for Economic Shifts

Economists and AI Researchers Issue Urgent Call for Economic Preparation as AI Capabilities Surge

More than 200 leading economists and AI researchers, including 16 Nobel laureates, released a joint statement on July 13, 2026, titled We Must Act Now: A Statement on AI’s Transformation of the Economy. The group is calling on global leaders, policymakers, and technology industry executives to immediately prepare for the sweeping economic disruption posed by increasingly capable artificial intelligence systems.

An Unprecedented Coalition

The statement, organized by economists Erik Brynjolfsson, Ajay Agrawal, Anton Korinek, and Tom Cunningham, warns that AI’s rapid development threatens to trigger an economic transformation potentially larger than the Industrial Revolution, yet one that will unfold over a “much shorter” timeframe. The signatory list is notable for its breadth, featuring Nobel laureates and core researchers from major AI powerhouses, including OpenAI, Anthropic, and Google (GOOGL).

The initiative, organized through Stanford University’s Digital Economy Lab, emphasizes that human society is currently operating on institutional structures that may be ill-equipped for the pace of change. Erik Brynjolfsson, the Jerry Yang and Akiko Yamazaki Professor at Stanford University and Director of the Stanford Digital Economy Lab, noted the disparity between technical progress and economic policy: “AI capabilities are advancing far faster than our understanding of the economic implications. In that gap lie the greatest opportunities of our era. We must act now to guide AI to complement humans rather than simply imitate them — and to generate prosperity for the many, not just the few.”

The Narrowing Window for Institutional Action

Anton Korinek, a University of Virginia professor who helped organize the initiative, stressed that the window for action is narrowing. “We cannot improvise our strategy and institutions,” Korinek stated, emphasizing that the group is demanding leaders create “incentives, guardrails, and institutions” that ensure AI is complementary to humans and beneficial to society. The statement warns that this breakneck pace of change will pose severe challenges for workers, businesses, and public institutions, leaving society with virtually no buffer period to adjust.

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Economic Interventions and Policy Disagreements

While the experts agree on the urgency of the situation, the path forward remains a subject of intense internal debate. A survey of the field highlighted a sharp divide regarding the most effective safety nets for a workforce facing potential automation. The policy with the broadest support among economists—71.8 percent in favor—is targeted retraining support: grants of up to $25,000 per year for workers displaced from high-automation industries, combined with career counseling and relocation assistance. Economists expected this to have a modest positive effect on both GDP growth and labor force participation.

Universal basic income, by contrast, was opposed by 38 percent of economists and supported by only 37 percent, primarily due to concerns that unconditional cash payments would reduce the incentive to work and further depress labor force participation. The general public, however, holds a different view. A majority of ordinary Americans support both job guarantee programs and universal basic income—policies that most economists view skeptically. This divergence suggests that if significant automation-driven displacement occurs, employers and policymakers may face political pressure that outpaces current expert consensus.

The Data Integrity Challenge

Experts caution that AI is only a valuable tool when it is well-trained with ample data. Monica Medina, who served as NOAA’s principal deputy undersecretary of commerce for oceans and atmosphere from 2009 to 2012, highlighted the risks of declining data collection in the United States. While the National Oceanic and Atmospheric Administration (NOAA) launched a suite of AI-powered global weather forecast models to improve speed, efficiency, and accuracy, Medina noted that under the Trump administration, climate and weather data collection has declined.

This creates a significant paradox for the broader AI sector: while the technology is touted as a tool for efficiency, it requires massive, accurate datasets to function effectively. As the researchers behind the We Must Act Now statement conclude, the core challenge remains that AI capabilities are advancing far faster than our understanding of their systemic implications. With no consensus on how to balance rapid innovation with systemic protection, the ability of global institutions to adapt before the next phase of AI development remains the primary uncertainty for policymakers and industry leaders alike.

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