A major new study involving researchers from the Federal Reserve Bank of Chicago, Yale, Stanford, and the University of Pennsylvania reveals a significant shift in expert consensus on artificial intelligence's impact on employment. The research, which surveyed 69 economists, 52 AI specialists, and 38 superforecasters, concludes that faster AI progress directly correlates with lower labor force participation—a polite term for fewer people working.
Under a "rapid" scenario where AI surpasses human performance in most cognitive and physical tasks by 2030, economists forecast the U.S. labor force participation rate could plummet from 62% to 54% by 2050. Approximately half of this decline, equating to roughly 10 million lost jobs, would be directly attributable to AI, rather than demographic trends. This scenario, described as not science fiction, envisions AI capable of negotiating contracts, assisting in factories, and replacing freelance software engineers, paralegals, and customer service agents.
Paradoxically, the same rapid AI scenario projects strong economic growth, with economists forecasting annual GDP growth hitting 3.5% by 2045-2049. AI experts are even more bullish, predicting 5.3% growth. However, this wealth creation is expected to be highly concentrated. The study warns that the wealthiest 10% of households could hold 80% of total wealth by 2050, surpassing pre-World War II inequality levels.
The debate has fundamentally shifted. The core question is no longer whether powerful AI will arrive, but what happens to the economy once it does. Economists are now grappling with whether AI, unlike past technologies, automates the very task of inventing new jobs. While aggregate employment data remains stable—a late-2025 Yale and Brookings study found no mass unemployment signal—the leading edge shows strain. Research cited in the new paper documents a 13% relative employment drop among workers aged 22-25 in AI-exposed occupations.
Supporting this trend, a recent Goldman Sachs report cited by Fortune indicates AI has eliminated 16,000 jobs per month over the past year, particularly collapsing hiring for entry-level roles. A 2025 SignalFire study found new graduate hiring in tech had dropped 50% compared to pre-pandemic levels.
A stark divide exists between executive optimism and on-the-ground reality. While 80% of leaders report weekly AI use with positive returns, 43% of workers say their jobs have become more frustrating. A Workday report found that for every 10 hours of efficiency gained through AI, nearly 4 hours are lost fixing its output, with only 14% of users consistently achieving net-positive outcomes.
On policy, economists favor targeted retraining programs (71.8% support) but largely reject job guarantees (13.7%) and universal basic income (37.4%), a stance that diverges sharply from the general public. OpenAI has acknowledged the disruption, releasing exploratory policy proposals to expand healthcare and retirement savings, warning that "unless policy keeps pace with technological change, the institutions and safety nets needed to navigate this transition could fall behind."
