AI exposure by U.S. occupations and work tasks and the effect on wages

Authors:

Chiara Chanoi, Washington Center for Equitable Growth
Chris Bangert-Drowns, Washington Center for Equitable Growth

Abstract:

This analysis of labor market AI exposure builds on previous work from the Pew Research Center and the AI firm Anthropic as well as Equitable Growth’s own job quality series, confirming differences in AI exposure by gender, race, education, and income. Women tend to work in more exposed occupations compared to men, while White and especially Asian workers tend to work in more exposed occupations compared to other racial groups. Exposure is larger for people who work high-paying, high-education jobs, regardless of gender or race. Our research finds a small but statistically meaningful positive correlation between AI exposure and income. It additionally appears that augmentative uses of AI are associated with higher wages while automative uses are associated with lower wages.