Driving corporate artificial intelligence applications: evidence from intelligent manufacturing projects

This study addresses the research gap regarding how government-led industrial policies catalyse micro-level technological transformation in emerging markets. Drawing on the resource-based view and the knowledge-based view, we empirically investigate the impact of intelligent manufacturing projects on corporate artificial intelligence innovation applications. Using a comprehensive sample of A-share listed companies in China from 2010 to 2023, we employ a staggered difference-in-differences framework and a double machine learning approach to ensure methodological robustness and mitigate high-dimensional selection bias. The findings reveal that the implementation of intelligent manufacturing projects significantly enhances artificial intelligence innovation levels within firms, with a 28.85% improvement compared with the average level. Mechanism analysis indicates that this promoting effect operates through the enhancement of data element utilization, the facilitation of cross-domain knowledge integration, and the expansion of research and development investment. Heterogeneity analysis further shows that the impact is more pronounced in non-state-owned enterprises, firms with higher degrees of digital transformation, and those in high-tech industries. This research clarifies the causal pathways of policy-driven innovation and offers practical guidance for the precise promotion of intelligent manufacturing initiatives and the efficient implementation of corporate transformation.