Greening through AI? The impact of Artificial Intelligence Innovation and Development Pilot Zones on green innovation in China

Razia Mijit, Qianlin Hu, Jingxuan Xu and Guangrong Ma

Energy Economics, 2025, vol. 146, issue C

Abstract: With increased adoption of artificial intelligence (AI) technologies, firms’ green innovation is expected to advance significantly. Using data from Chinese A-share listed firms, we employ a heterogeneity-robust staggered difference-in-differences model to evaluate the impact of AI on firms’ green innovation, leveraging the Artificial Intelligence Innovation and Development Pilot Zones (AIIDPZ) policy in selected Chinese cities as an exogenous shock. The results demonstrate that AIIDPZ policy implementation has significantly enhanced the quantity and quality of firms’ green innovation. Further analysis reveals notable heterogeneity in the policy’s effects in which low-polluting firms are more inclined to increase the quantity of green innovations, whereas capital-intensive and labor-intensive industries tend to prioritize improving innovation quality. Mechanism analysis reveals that increased AI adoption induced by the AIIDPZ policy significantly enhances firms’ operational efficiency, which subsequently fosters advanced green innovation. Based on these findings, we recommend promoting the further integration of AI across industries, with particular emphasis on leveraging AI-driven efficiency gains to advance green development.

Keywords: Artificial intelligence; Green innovation; Heterogeneity-robust staggered DID; Operational efficiency (search for similar items in EconPapers)
JEL-codes: C21 C23 H23 O33 Q55 Q58 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:146:y:2025:i:c:s0140988325003317

DOI: 10.1016/j.eneco.2025.108507

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