Does artificial intelligence improve energy efficiency? Evidence from provincial data in China

Xin Li, Shiyuan Li, Jifeng Cao and Andrei Cristian Spulbar

Energy Economics, 2025, vol. 142, issue C

Abstract: As global energy demand rises and environmental awareness increases, improving energy efficiency (EE) has become crucial to achieving sustainable development. This paper employs a two-way fixed effects panel model using data from 30 provinces in China, from 2000 to 2021, to investigate the impact of artificial intelligence (AI) on EE. The research results reveal that advancements in AI have greatly facilitated the improvement of EE. Furthermore, green technology innovation capability plays a positive moderating role between AI and EE. A heterogeneity analysis indicates that the impact of AI on EE is more significant in economically-developed regions. In energy-deficient regions, AI can significantly improve EE, whereas conversely, in energy-abundant regions, AI's impact on EE is negative. Further analysis using a spatial Durbin model (SDM) confirms the presence of spatial effects in the impact of AI on EE. This paper aims to expand the scholarly understanding of the relationship between AI and EE and provides empirical evidence for decision-makers during this critical period of energy transition. By delving into the potential of AI to enhance EE, the paper seeks to illuminate specific strategies and approaches for policymakers and industry participants.

Keywords: Artificial intelligence; Energy efficiency; Green technology innovation (search for similar items in EconPapers)
JEL-codes: C33 O13 Q55 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:142:y:2025:i:c:s0140988324008582

DOI: 10.1016/j.eneco.2024.108149

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