The potential impact of artificial intelligence (AI) on the global labor market has sparked a range of predictions, from optimism about job creation to concerns about widespread displacement. Three labor economists—a professor at the Massachusetts Institute of Technology, a University of Virginia academic, and the director of Yale University’s Budget Lab—recently offered varied perspectives on the future of work in an AI-driven economy.

Anton Korinek of the University of Virginia said AI could fundamentally reshape economic structures similar to the Industrial Revolution, which shifted the scarcity in production from land and capital to labor. He warned that with AI capable of performing both cognitive and physical tasks at human levels, the labor share of income, currently about 60%, could drop below 50% within a generation, potentially leading to profound market and social changes.

David Autor of MIT expressed a more tempered view. He emphasized that AI will alter jobs rather than eliminate them entirely, noting the enduring value of human qualities such as judgment, moral reasoning, empathy, and expertise. “The idea that AI will trigger a wholesale collapse of human employment is an oversimplification,” he said, adding that AI could help address pressing challenges in sectors like healthcare and education.

Martha Gimbel of Yale highlighted the complexities of integrating AI into the job market, pointing to the unpredictability of technological disruption and the slower pace of automation in occupations involving human interaction. She cautioned against Silicon Valley’s overly optimistic assumptions, noting that many real-world jobs are difficult to mechanize due to their nuanced, less defined nature.

When asked about unemployment rates, Autor suggested that with a well-managed transition, AI might not cause a significant rise in unemployment, although participation in the workforce could decline. Gimbel underscored the influence of macroeconomic factors, suggesting the timing and extent of AI’s effects remain uncertain. Korinek added that the rapid evolution of AI could lead to significant employment volatility even in the short term.

Regarding which jobs face the most risk, Korinek identified white-collar professions—such as those in law, finance, accounting, and consulting—as particularly vulnerable to automation. Autor noted that information-intensive service roles, including call-center workers, translators, and certain middle managers, especially in developing countries, could be displaced by AI. Gimbel stressed that older workers might bear the brunt of economic disruptions, while younger workers may better adapt due to their familiarity with new technologies.

The economists also discussed factors that could slow AI adoption. Gimbel highlighted the persistent demand for human contact, especially in caregiving roles, while Korinek pointed out that AI currently struggles with dynamic learning and physical tasks. Autor mentioned professional resistance in some fields, where established groups may block automation of expert functions to protect job security.

Looking ahead, the panelists diverged on long-term outcomes. Korinek suggested that as AI progresses, traditional models based on labor market economics might become obsolete, potentially requiring new income distribution systems independent of labor market participation. Autor expressed confidence in human creativity and decision-making as buffers against total economic upheaval. Gimbel emphasized the resilience of economies and human adaptability, noting that new forms of work and consumer preferences will continue to emerge.

Collectively, their insights underscore the complexity of forecasting AI’s impact on employment and highlight the need for adaptive policies to manage the transitions ahead.