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The impact of artificial intelligence on energy resilience: Empirical evidence from China

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Listed:
  • Zhou, Kunlu
  • Liu, Yuanhong
  • Liao, Qidong
  • Xu, Jiuping

Abstract

Enhancing energy resilience is an effective way to guarantee energy security and stability, and the rapid development of AI presents an unprecedented opportunity to do so. Investigating how China's level of AI affects energy resilience will provide an extremely valuable reference for the rest of the world as well. Thus, this study explores the impact of AI on energy resilience using data from 236 cities in China. The results show that AI makes a significant contribution to improving energy resilience, and the results remain robust after robustness check and endogeneity treatment. Further analysis indicates that this effect is heterogeneous across cities with different geographic locations, resource types, human capital levels, and manufacturing types. Additionally, mechanism analysis reveals that AI contributes to energy resilience by increasing energy efficiency, fostering technological innovation and upgrading industrial structure. Overall, this study confirms the contribution of AI to energy resilience and provide empirical references for paradigm shift in world energy governance.

Suggested Citation

  • Zhou, Kunlu & Liu, Yuanhong & Liao, Qidong & Xu, Jiuping, 2026. "The impact of artificial intelligence on energy resilience: Empirical evidence from China," Energy Economics, Elsevier, vol. 153(C).
    • Handle: RePEc:eee:eneeco:v:153:y:2026:i:c:s0140988325008709
    DOI: 10.1016/j.eneco.2025.109040
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