Amid the new wave of scientific and technological revolution, artificial intelligence (AI)—an emerging general-purpose technology—is profoundly transforming global employment structures, exerting a growing influence on developing countries in transition. Based on the panel data of 30 provinces in China from 2011 to 2022, this study proposes a fixed effect model, a lagged and mediated effect model to systematically explore the impact of AI development on regional employment quality and its transmission mechanism. The study demonstrates that AI significantly improves regional employment quality and shows significant regional heterogeneity, with the strongest effect in eastern China, the second in central China, and the weakest in western China; AI impacts employment quality with a notable lag owing to the time required for technology diffusion and labor skill adjustment. Upgrading of the industrial structure is an important intermediary path for AI to affect employment quality, and the differences between the industrial base and absorptive capacity of different regions aggravate the impact of policies on the quality of employment and their transmission mechanism. Differences in the industrial base and absorptive capacity of different regions exacerbate the unevenness of policy effects. This study suggests formulating AI development strategies based on regional factor endowments, optimizing industrial structure and workforce training system, improving policy support and regional coordination mechanism, and promoting benign interaction between AI and high-quality employment.
Zhang et al. (Thu,) studied this question.