IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v147y2025ics0140988325003901.html
   My bibliography  Save this article

The two-way street: How AI and clean energy affect each other

Author

Listed:
  • Lyu, Jiayi
  • Gao, Zixuan
  • Li, Yanfeng
  • Zhang, Qiang

Abstract

In an era characterized by rapid advancements in artificial intelligence (AI) and a significant shift towards clean energy (CE), this study investigates the symbiotic relationship between AI and CE, examining how each influences the other. Utilizing both both full-sample and sub-sample analyses, the research delineates the evolving interplay between AI technologies and CE within the Chinese context. The empirical results indicate that AI exerts a dual influence on CE: it not only provides substantial technological support for the development and transition towards CE but also potentially increases overall energy consumption due to its intensive energy requirements. Conversely, China's intensified focus on CE presents new avenues for the expansion and deployment of AI technologies. These findings shed light on the dynamic interconnection between AI and CE and offer strategic recommendations to facilitate the global progression towards sustainable energy.

Suggested Citation

  • Lyu, Jiayi & Gao, Zixuan & Li, Yanfeng & Zhang, Qiang, 2025. "The two-way street: How AI and clean energy affect each other," Energy Economics, Elsevier, vol. 147(C).
    • Handle: RePEc:eee:eneeco:v:147:y:2025:i:c:s0140988325003901
    DOI: 10.1016/j.eneco.2025.108566
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988325003901
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2025.108566?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    Artificial intelligence; Clean energy; Time-varying interrelationship; China;
    All these keywords.

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:147:y:2025:i:c:s0140988325003901. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.