The Early Impacts of AI on Employment among Recent College Graduates

Robert Fairlie () and Jane Wu ()
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Robert Fairlie: University of California, Los Angeles
Jane Wu: UCLA

No 18945, IZA Discussion Papers from IZA Network @ LISER

Abstract: The impact of AI on the employment prospects of recent college graduates is hotly debated with no consensus on the magnitude of impacts nor even the timing of those potential impacts. Using CPS microdata, we provide the first estimates of the effects of AI on the unemployment of recent college graduates in June, July and August 2026. Taking an agnostic approach to defining treatment timing, we find that unemployment rates did not spike in summer 2026 relative to summer months in previous years and did not rise in a significant way relative to older college graduates or young workers without a college degree. We also find no evidence of a statistically significant increase in summer 2026 even after adding the “sidelined unemployed.†We estimate difference-in-differences and event-study interaction models using both older college graduates and young non-college graduates as comparison groups and do not find evidence of an increase in relative unemployment rates. Finally, we estimate models in which we interact 2026 unemployment with AI exposure and remote work availability by occupation and find some evidence of a positive relationship with remote work availability.

Keywords: AI; technological change; unemployment; job loss; college graduates (search for similar items in EconPapers)
JEL-codes: J21 J24 J63 J64 (search for similar items in EconPapers)
Date: 2026-09
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