The breakthrough of artificial intelligence (AI) has unleashed enormous productivity growth potential while reshaping the labor market’s skill demand structure and income distribution pattern. Amid such technological transformation, the labor market has shown distinct polarization, which will constrain the sustainability of technological progress and social equity. Thus, exploring the coordinated development path of AI, employment, and income distribution, and resolving the structural contradiction between AI-driven productivity improvement and distributional imbalance, holds significant theoretical and practical value.

This paper uses data from online recruitment platforms and textual data from annual reports of China’s A-share listed companies. From the perspective of dynamic changes in job skill demands, it examines the impact of AI on the intra-firm income gap. The results show that AI significantly raises employees’ average wage but weakly affects the management’s, thereby narrowing the intra-firm income gap. Mechanism testing reveals that AI boosts employees’ wages by increasing the demand for high-value-added skills. Meanwhile, it reduces the management’s demand for certain professional skills, curbing their wage growth. Additionally, AI-driven productivity improvement further supports this intra-firm gap-narrowing effect. Heterogeneity analysis indicates that this effect is more pronounced in non-state-owned enterprises, low-market-concentration industries, and professional technical and service occupations.

This paper makes three marginal contributions: First, it uses online recruitment data to identify the demand-side characteristics of the labor market, providing empirical support for analyzing the relationship between AI and the intra-firm income gap. Second, it innovatively explores the mechanisms through which AI affects the income gap from the micro-perspective of “skill displacement”. Third, it offers theoretical and policy references for enhancing the technological adaptability of different employment groups. Based on the research findings, this paper suggests that governments strengthen institutional guidance for AI development to amplify its effect in narrowing the income gap, improve the dynamic early-warning mechanism for skill demands and the adaptive training mechanism, and supplement targeted employment support policies to achieve precise matching between labor skill supply and market demand.