Heterogeneous effects of artificial intelligence orientation and application on enterprise green emission reduction performance

Abstract

The utilization of frontier technologies by firms to foster synergy between environmental governance and high-quality development has emerged as a pivotal concern in light of the intensifying global initiative for sustainable development and the transition to a green economy. This study carefully analyzes the influence of artificial intelligence on the green governance performance of Chinese firms from 2009 to 2023, utilizing micro-level data and investigating the underlying causes. The results indicate that artificial intelligence markedly improves green governance performance at the enterprise level, and this benefit persists even after controlling for potential endogeneity. Mechanism analysis indicates that artificial intelligence facilitates green transformation via a dual-path mechanism of “cognition–behavior,” by enhancing environmental inclination and augmenting environmental investment. Subsequent heterogeneity analysis reveals that the beneficial benefits are more significant in non-heavy polluting sectors and state-owned businesses, indicating that industry characteristics and ownership structure influence the impact of artificial intelligence on green governance. This study enhances the theoretical framework of research at the convergence of digital technology and green governance, offering empirical data and policy insights to facilitate AI-driven green transformation in practice.