An AI-enabled micro-level analysis of organizational and technological paths to green upgrading

With global warming and escalating environmental pollution, governments worldwide have committed to promoting traditional manufacturing industries’ green transformation and upgrading. What role does artificial intelligence (AI) have in this effort? Herein, we construct a micro-level theoretical model to analyze how AI affects firms’ green transformation, adopting a two-way fixed effects (TWFE) model to examine panel data from Chinese A-share listed traditional manufacturing enterprises from 2011 to 2022 for empirical analyses. The results reveal that AI significantly promotes enterprises’ green transformation efficiency (GTI). Mechanism analyses demonstrate that AI promotes corporate organizational innovation, including adjusting organizational and employee structures and promotes technological innovation by accelerating technical progress and reducing energy intensity. Heterogeneity analysis of enterprises’ internal management and external environment shows that AI can effectively improve firms’ GTI when executives have technological backgrounds, engage in long-term decision-making, and the region has strong intellectual property rights protection, high environmental regulation intensity, and an elevated degree of social trust. Overall, this study elucidates the influence and conditions of AI in the traditional manufacturing industry’s green transformation and upgrading and has significant the implications for relevant policy development.