Artificial intelligence exposure and occupational wages: Evidence from the United States

OpenAlex İngilizce

Purpose This paper investigates the relationship between occupational exposure to artificial intelligence (AI) and wage structures in the United States. While much of the literature focuses on the displacement effects of AI, less attention has been given to its implications for wage outcomes across occupations. Design/methodology/approach The study uses occupation-level data for 671 occupations, combining wage information with an AI exposure index that captures the extent to which occupations are affected by AI technologies. Cross-sectional regression models with robust standard errors are employed, controlling for employment size and occupational characteristics. Quantile regression is also used to examine variation across the wage distribution. Findings The results indicate a positive and statistically significant association between AI exposure and wages. Occupations with higher exposure tend to have higher wage levels. This pattern is consistent across model specifications and across the wage distribution. The findings are broadly consistent when using an instrumental variable approach. The association is stronger in occupations with higher cognitive skill intensity. Research limitations/implications This study is based on occupation-level data rather than individual-level observations, which limits the ability to capture within-occupation wage heterogeneity. In addition, the AI exposure index reflects potential exposure rather than actual adoption at the firm level. Future research could extend this analysis using firm-level or longitudinal data. Practical implications The findings suggest that occupations with higher exposure to artificial intelligence tend to exhibit higher wages, highlighting the importance of skill upgrading and targeted workforce policies. Policymakers and organizations should focus on enhancing digital skills and supporting workforce transition to maximize the benefits of AI. Social implications The results indicate that artificial intelligence may contribute to wage differences across occupations by enhancing productivity in certain roles. This highlights the need to ensure equal access to skills and training opportunities so that the benefits of AI are distributed more evenly across the labor market. Originality/value This study contributes by providing occupation-level evidence on the relationship between AI exposure and wages, shifting attention from employment effects to wage structures. It also highlights that this relationship is partly explained by occupational skill composition, while a residual association remains.