Leveraging new-generation artificial intelligence technologies to drive corporate low-carbon transformation has become a critical approach to addressing emission reduction challenges and realizing coordinated economic and ecological development. This paper takes the policy of Artificial Intelligence Innovation and Development Pilot Zones as a quasi-natural experiment. Using the data of A-share listed companies from 2010 to 2021, this study adopts a staggered DID method to systematically evaluate the impact of the pilot zone policy on corporate carbon emission intensity. The empirical results show that the policy of artificial intelligence innovation and development pilot zones can significantly reduce corporate carbon emission intensity. Mechanism tests indicate that this policy curbs corporate carbon emissions mainly through three transmission paths: empowering enterprises via digital technologies, expanding the scale of green innovation, and improving the quality of green innovation. Heterogeneity analysis reveals that regional green financial development, government service capacity and corporate financing constraints exert prominent differentiated impacts on the policy’s emission reduction effect. The research conclusions provide theoretical references and empirical evidence for further expanding the scope of artificial intelligence innovation pilots and establishing a long-term mechanism for enabling green transformation with digital technologies.

Yang Beibei, Yuan Meng, Jiang Na. Artificial Intelligence Innovation and Development Pilot Zones and Corporate Green Low-Carbon Development: Empirical Evidence from Chinese Listed Companies. Academic Journal of Business & Management (2026), Vol. 8, Issue 8: 25-32. https://doi.org/10.25236/AJBM.2026.080804.

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