Unlocking green potential: How does artificial intelligence affect the sustainability of green innovation?

Against the backdrop of the digital economy's development and the advancement of the "dual carbon" goals, how artificial intelligence can continuously empower corporate green innovation has become a critical issue. This study uses A-share listed companies on the Shanghai and Shenzhen stock exchanges from 2010 to 2023 as its sample and employs a fixed-effects model to empirically examine the impact of artificial intelligence on the sustainability of corporate green innovation and its underlying mechanisms. The findings reveal that AI significantly enhances the sustainability of corporate green innovation, indicating that it not only promotes increased green innovation output but also strengthens enterprises' capacity for sustained innovation through data processing, intelligent decision-making, and resource optimization. Test results obtained using instrumental variables, replacing the dependent variable, adding industry-year fixed effects, and excluding samples from specific years all support this conclusion. Mechanism analysis indicates that AI primarily exerts its effects by improving credit availability, increasing external attention, and raising total factor productivity. Moderation analysis reveals that human capital levels, internal control levels, and the degree of market competition can amplify the positive effects of AI on green innovation. Heterogeneity analysis further finds that this effect is more pronounced in state-owned enterprises, non-high-polluting enterprises, enterprises in regions with better digital infrastructure, and growth-stage enterprises. This study expands the research on the relationship between AI and green innovation, providing references for corporate digital transformation and government policy-making tailored to specific sectors.