How does AI exposure affect wages across occupational earnings levels?
Core argument: Using observed AI usage data from the Anthropic Economic Index across 321 matched occupations from 2015–2025, the authors estimate that high-exposure occupations saw a 6.7% decline in real wage growth after 2023, with no detectable employment effects.
We examine the wage and employment effects of AI adoption across U.S. occupations using observed usage data from the Anthropic Economic Index rather than the theoretical exposure measures that dominate prior work. Using a difference-in-differences design with occupation and year fixed effects across 321 matched occupations from 2015 to 2025, we find that high-exposure occupations experience a 6.7% decline in real wage growth post-2023 with no detectable employment effects. The effect is concentrated among the lowest earners: service workers face a 24.3% decline and the bottom wage quartile a 10.7% decline, while top earners show no significant effect.Today, 5.8 million workers are affected, but as AI adoption deepens across corporate America, this figure is likely to grow substantially, with significant implications for income inequality and labor market policy in the years ahead. Only 321 of roughly 800 BLS occupations were matched, and the post-2023 period may be partially confounded by post-pandemic labor market dynamics. [Editor’s note: Figure 3 shows both wage and employment growth and decline among high-exposure workers, but the exposure measure combines automated and augmentative use, and thus cannot distinguish substitution from complementarity.]

