The Impact of Artificial Intelligence on the Income Gap between Labor and Capital—Empirical Analysis Based on A-share Listed Companies

Abstract

Against the backdrop of artificial intelligence reshaping the income distribution pattern of enterprises, the widening gap between labor and capital income shares has raised concerns about social equity. This article empirically tests the impact of artificial intelligence applications on the income share gap between labor and capital based on data from Chinese A-share listed companies from 2010 to 2022. Research has found that the application of artificial intelligence significantly widens the income gap between labor and capital, with the core mechanisms being the capital labor substitution theory and the theory of technological progress bias; Heterogeneity analysis shows that this effect is particularly prominent in non-state-owned enterprises (expanding by 0.35%) and labor-intensive industries (expanding by 0.28%), while state-owned enterprises do not show significant expansion due to policy constraints (salary control, job stability responsibilities) and technology intensive industries due to skill technology complementarity. This article suggests alleviating distribution polarization by strengthening worker skills training and designing profit sharing mechanisms, providing policy insights for coordinating technical efficiency and income equity.