Can artificial intelligence empower energy enterprises to cope with climate policy uncertainty?

Qian Zhong, Qun Zhang and Jingjing Yang

Energy Economics, 2025, vol. 141, issue C

Abstract: This study investigates the effect of climate policy uncertainty (CPU) on firm-level investment and through which artificial intelligence (AI) may act upon this relationship. Using panel data from listed energy enterprises in China from 2010 to 2019, we demonstrate that CPU significantly inhibits energy enterprises' investments, mainly by exacerbating their financing constraints. This effect is more pronounced in firms with strong environmental awareness, strong internal control, high environmental, social, and governance scores, or in the traditional energy industry. Furthermore, we find that AI adoption weakens the impact of CPU on firm-level investments, primarily through two potential mechanisms: mitigating the customer concentration risk and enhancing green patent commercialization. On average, a 1 % increase in the degree of AI adoption by energy firms can boost their investment expenditure by 0.0065 %. Furthermore, AI's role in mitigating the negative impact of CPU on energy firms' investments is more significant in non-resource-based cities, cities with high economic growth rates, and cities with advanced IT infrastructure. Our findings provide a deeper understanding of the forces driving sustainable energy transitions in the evolving climate policy landscape.

Keywords: Climate policy uncertainty; Artificial intelligence; Corporate investment; Energy enterprises; Green patent commercialization (search for similar items in EconPapers)
JEL-codes: G11 G3 G38 Q43 Q55 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:141:y:2025:i:c:s0140988324007977

DOI: 10.1016/j.eneco.2024.108088

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