The impact of artificial intelligence development on enterprise labor investment efficiency

Artificial intelligence (AI) applications have exerted a profound influence on corporate labor hiring decisions. Taking the establishment of the National Pilot Zones for Next-Generation Artificial Intelligence Innovation and Development as a quasi-natural experiment, this study empirically examines the impact of AI policy on labor investment efficiency using a sample of all A-share non-financial listed companies from 2015 to 2024. The results indicate that the establishment of these pilot zones significantly enhances corporate labor investment efficiency, effectively suppressing both over-investment and under-investment in labor. Regarding the underlying mechanisms, the pilot zones function through three primary channels: deepening AI applications helps improve firms' ability to forecast labor demand and optimize human capital investment decisions; easing financing constraints and reducing financing costs provides the necessary liquidity for firms to flexibly adjust their employment scale and avoid sub-optimal decisions driven by short-term financial pressure; and mitigating various agency costs reduces hiring distortions stemming from managerial self-interest by increasing decision-making transparency and management standardization. Heterogeneity analysis reveals boundary differences in policy effects: the positive impact is more pronounced in firms characterized by lower labor costs, higher talent recruitment intensity, severe information asymmetry, and substantial innovation subsidies, reflecting a logic of compensatory distribution of policy dividends and resource synergies. Furthermore, the study finds an empowerment effect where the pilot zones enhance the labor investment efficiency of firms located within an 80km radius. These findings provide empirical evidence from the Chinese context for understanding human capital allocation in the AI era.