Abstract: This paper studies the impact on wages and worker mobility of generative artificial intelligence. We use occupation-by-industry data from the Occupational Employment and Wage Statistics (OEWS) and data on postings and matched employer-employee data from Revelio. We find that moving from the 10th percentile to the 90th percentile of GenAI exposure is associated with a wage decline of 4.9% in OEWS data, with no statistically detectable change in employment. In Revelio data, moving from the 10th to the 90th percentile of exposure is associated with a decline of 8.71% in posted wages, and of 10.76% in starting wages. More exposed workers experience significantly lower job-to-job transition rates, but no change in transitions to persistent non-employment. Wage declines are largest among junior workers and occur across all age groups within junior positions. Finally, we find that AI exposure is associated with a decline in the elasticity of separation with respect to wages, which suggests that firms’ labor market power has increased in occupations that are exposed to automation by GenAI. The combined evidence indicates that generative AI exposure has so far negatively affected workers’ wages, mobility, and outside opportunities in the labor market
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