With the rapid advancement of artificial intelligence (AI) technology, the global employment structure is undergoing profound transformations, significantly impacting social sustainability. This study utilizes panel data from 30 Chinese provinces spanning the years 2010 to 2022 and applies a two-way fixed-effects model to analyze the impact of AI development on the employment skills structure. The findings indicate that advancements in AI technology significantly suppress the demand for low-skilled labor while markedly enhancing the demand for both middle- and high-skilled labor. The threshold effect analysis reveals a nonlinear relationship between AI advancements and the demand for low-skilled workers. Mediation effect tests demonstrate that technological innovation serves as a mediating factor in AI’s impact on low- and middle-skilled labor but has no significant effect on high-skilled labor. The heterogeneity analysis further indicates that AI’s negative impact on low-skilled female employment is more severe than for males, while its positive impact on high-skilled male workers is significant. Additionally, the employment effects of AI are mainly observed in labor-intensive provinces, with minimal influence in capital-intensive areas. This study suggests harnessing AI’s potential to promote employment while proactively mitigating its disruptive effects on the labor market through enhanced research and development support, strengthened employment security, and coordinated regional economic development, thereby advancing sustainable economic and social progress.

With the rapid development of artificial intelligence (AI), its implications for income distribution have attracted increasing attention. As a key indicator of earnings differences between high- and low-skilled workers, the skill premium is important for distributional equity and sustainable economic and social development. Using AI-related patent data from Chinese listed firms, this paper constructs a firm-level measure of AI development and examines its impact on the skill premium within firms. The results show that AI development significantly increases the firm-level skill premium. Mechanism analysis suggests that AI increases the firm-level skill premium by substituting for low-skilled labor, improving firm productivity, promoting capital deepening, and facilitating technological upgrading. The main findings remain robust after addressing endogeneity using an instrumental variable approach and conducting a series of robustness checks, including alternative constructions and measures of the dependent variable, alternative measures of AI development, AI pilot zone policy shock tests, and alternative sample restrictions. Heterogeneity analysis further shows that the effect is more pronounced in non-state-owned firms, firms with higher levels of digitalization, and firms operating in industries with lower market concentration. Further analysis indicates that AI development may also reduce firms’ labor income share and widen income disparities across industries. These findings highlight the need to strengthen workers’ skills and adaptability, improve income distribution mechanisms, and promote a more balanced relationship between technological progress and social equity.