HOW ARTIFICIAL INTELLIGENCE AFFECTS THE EXPORT TECHNOLOGICAL COMPLEXITY OF MANUFACTURING ENTERPRISES

School of Economics & Management, Shanghai Polytechnic University, China
China

School of Economics & Management, Shanghai Polytechnic University, China
China


Abstract

This study examines the annual reports of A-share-listed manufacturing companies from 2014 to 2023. Using machine learning and text analysis, it constructs firm-level indicators of AI application and assesses their effect on export technological complexity. The results show that AI significantly boosts firms’ export technological complexity. AI also empowers export competitiveness through three pathways: improving total factor productivity, optimizing the human capital structure, and stimulating technological innovation. Threshold effect analysis reveals that the impact of AI is not linear. It is significantly constrained by firms’ internal resource endowments. Only when the quality of human capital exceeds a certain threshold, and total factor productivity rises to a high level, does AI's enabling effect shift from weak to strong, or even from negative to positive. Heterogeneity research reveals that the effect is larger in eastern regions, among non-state-owned firms, and in places with strong intellectual property protection. These findings offer important insights into employing "AI+" to support high-quality development in the manufacturing sector

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