Artificial Intelligence and Low-Carbon Energy Transition: From the Perspectives of Green Innovation Resilience and Green Finance

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Authors: Le Yan, Shizheng Tan, Wei Li, Mengxin Wang
Cited by: 1
References: 44

Abstract

Achieving the low-carbon transformation of energy consumption structure is central to carbon-neutral development, yet how artificial intelligence (AI) contributes to sustained structural change remains insufficiently understood. Addressing this gap, this study examines not only whether AI facilitates the green and low-carbon transformation of energy consumption structure in China, but also through which mechanisms and under what conditions this effect is sustained. Using provincial panel data for 2013–2022, we estimate the direct effect of AI and test the mediating role of green innovation resilience and the moderating role of green finance. The results show that AI significantly promotes the low-carbon transformation of energy consumption structure. Green innovation resilience serves as an important transmission mechanism, while green finance strengthens this relationship. These findings deepen understanding of the AI-energy transition nexus and provide policy implications for effectively coordinating digital technology, green innovation, and green finance.

Fields of Study & Subjects

Energy Environment Economic Growth COVID-19 impact on air quality Market Dynamics and Volatility

Publication details

Journal / source
The Journal of Environment & Development
Publisher
SAGE Publications
Publication date
18 June 2026
Language
EN