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The role of artificial intelligence in renewable energy development: Insights from less developed economies

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  • Zheng, Huanyu
  • Wu, Jie
  • Li, Runze
  • Song, Yanwu

Abstract

Global climate change and the growing pressure of energy transition pose complex challenges for less developed economies in achieving environmental sustainability. Artificial intelligence technology offers a promising avenue for advancing renewable energy development. This study analyzes the non-linear impact of AI technology on the renewable energy, drawing on AI patent data from 56 less developed economies from 2007 to 2022. The findings reveal a significant “inverted U-shaped” relationship. That is, AI initially drives renewable energy adoption, but as technological development reaches a certain threshold, its marginal benefits decline, potentially leading to negative effects. Moreover, institutional quality plays a crucial moderating role, with a strong rule of law enhancing AI's positive impact, while digital economic expansion exerts a weakening effect. Technological innovation acts as a key mediating mechanism, facilitating AI's influence on renewable energy adoption. Furthermore, the impact of AI varies across different renewable energy sources, with significant non-linear effects observed for biomass and wind energy, while its influence on solar and hydropower remains limited. These insights contribute to the literature on sustainable energy transitions and provide valuable policy implications for optimizing AI-driven renewable energy strategies in less developed economies.

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  • Zheng, Huanyu & Wu, Jie & Li, Runze & Song, Yanwu, 2025. "The role of artificial intelligence in renewable energy development: Insights from less developed economies," Energy Economics, Elsevier, vol. 146(C).
    • Handle: RePEc:eee:eneeco:v:146:y:2025:i:c:s0140988325003755
    DOI: 10.1016/j.eneco.2025.108551
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