The Impact of Artificial Intelligence Development on Firms’ Educational Composition of Labor
DOI:
https://doi.org/10.54097/b49e5w74Keywords:
artificial intelligence, labor educational structure, technological innovation, firm labor demand, skill bias.Abstract
As a strategic technology driving a new wave of scientific and technological revolution and industrial transformation, artificial intelligence (AI) is profoundly reshaping firms’ factor allocation and labor demand structure. Using Chinese A-share listed firms in Shanghai and Shenzhen from 2014 to 2024 as the research sample, this study constructs firm-level AI development indicators through text analysis and machine learning methods, and empirically examines the effect of AI development on firms’ labor structure from the perspective of educational composition, while further exploring its heterogeneity. The results show that, first, AI development significantly reshapes firms’ educational composition of labor. For each one-unit increase in AI development, the share of low-educated labor decreases by 0.007 units, whereas the share of high-education labor increases by 0.006 units, revealing a typical pattern of “substituting for low-educated labor while complementing high-educated labor.” Second, firms’ technological innovation capability plays a significant mediating role between AI development and adjustments in labor educational structure. By enhancing firms’ technological innovation capability, AI development reduces demand for low-educated labor and increases demand for high-education labor. Third, the effect of AI on labor educational structure exhibits significant regional and industrial heterogeneity. The substitution effect is stronger in developed regions, whereas the complementarity effect is more pronounced in less developed regions; moreover, the effect in high-technology industries is approximately 2.5 times as large as that in non-high-technology industries. This study reveals the micro-level logic of firms’ labor allocation under the technological shock of AI, provides empirical evidence for understanding the application of skill-biased technological change theory in the AI era, and offers a scientific basis for governments to formulate differentiated talent policies, guide the smooth transformation of the labor market, and promote the coordinated development of technological progress and employment structure optimization.
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