A study on the impact of artificial intelligence applications on corporate green technological innovation: A mechanism analysis from multiple perspectives

Lusi Chen, Shinan Li and Zhili She

International Review of Economics & Finance, 2025, vol. 103, issue C

Abstract: This paper investigates the impact of artificial intelligence (AI) applications on corporate green technological innovation using a comprehensive panel dataset of Chinese A-share listed firms. AI application is measured by constructing a firm-level index based on the frequency of AI-related keywords in annual reports, while green technological innovation is proxied by the number of green invention and utility model patents filed. The empirical results show that AI adoption significantly promotes firms’ green innovation. This finding remains robust after addressing potential endogeneity through lagged variables, propensity score matching (PSM), and the Heckman two-step method. Mechanism analysis reveals that AI enhances green innovation by alleviating financing constraints, stimulating R&D investment, and reducing managerial overconfidence. Furthermore, heterogeneity tests indicate that the positive effects of AI are more pronounced in high-tech and non-high-pollution industries and in the economically advanced Eastern region of China. These findings contribute to the literature on digital transformation and environmental sustainability and offer policy implications for promoting AI-enabled green transitions in emerging economies.

Keywords: Artificial intelligence; Green technological innovation; Financing constraints; R&D investment; Managerial overconfidence (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reveco:v:103:y:2025:i:c:s1059056025006537

DOI: 10.1016/j.iref.2025.104490

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