The impact of artificial intelligence on energy environmental performance: Empirical evidence from cities in China

Qingbin Guo, Yanqing Peng and Kang Luo

Energy Economics, 2025, vol. 141, issue C

Abstract: As a form of the next-generation intelligent information technology, artificial intelligence (AI) is anticipated to unleash an “intelligence dividend”, playing a pivotal role in driving efficiency transformation and realizing green development objectives. Based on data from 223 cities in China for 2008 to 2021, this research evaluates the AI level from the three dimensions of intelligent infrastructure, intelligent practical applications, and intelligent technology development. It also delves into AI's impact and mechanisms on urban energy environmental performance (EEP). The findings show that AI enhances urban EEP and influences EEP by advancing urban green innovation capabilities, improving urban human capital, and optimizing energy consumption structure. Specifically, AI has a notably heightened effect on EEP in the eastern region, large urban areas, and non-resource-based cities. Subsequent analyses reveal a significant siphoning effect of AI's impacts across geographical distances and indicate that AI does not have a rebound effect on urban energy. In sum, countries and regions should fully seize the strategic opportunities presented by rapid AI development, shape new advantages in technological competition through open integration and innovation, and thus drive the transformation of energy development.

Keywords: Artificial intelligence; Energy environmental performance; Spatial siphon effect; Energy rebound (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:s0140988324008454

DOI: 10.1016/j.eneco.2024.108136

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