The Impact of Artificial Intelligence on Total Factor Productivity of China's Specialized, Refined, Distinctive, and Innovative Enterprises: An Heterogeneity Perspective
Sang Mengjia  Zhang Zheng

Business School University of Shanghai for Science and Technology, Shanghai, 200093;

Abstract：Against the backdrop of deep integration between the digital economy and the real economy, and the national strategy to vigorously develop new quality productive forces, this study examines the impact of artificial intelligence on firm-level total factor productivity (TFP) and its heterogeneity. Using a sample of China's A-share specialized, refined, distinctive, and innovative enterprises (SRDI) from 2005 to 2023, we establish a two-way fixed effects model. Results indicate that AI significantly boosts corporate TFP, a conclusion that remains robust after controlling for proxy variables, tail trimming, and excluding exceptional years. Heterogeneity analysis further reveals structural variations in AI's enabling effects: its impact is stronger in state-owned enterprises than non-state-owned enterprises, greater in inland regions than coastal regions, and dynamically changes across different life cycle stages. The enhancement effect is most pronounced for mature-stage enterprises, while no significant impact is observed for declining-stage enterprises. This study systematically uncovers the context-dependent nature and complex mechanisms through which AI influences corporate productivity across three dimensions: ownership structure, geographic location, and development stage. It provides empirical evidence for deepening our understanding of the relationship between digital technologies and high-quality corporate development, while also offering decision-making references for promoting the intelligent transformation of enterprises through targeted approaches.

Keywords: artificial intelligence; TFP; SRDI enterprises; Heterogeneity

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