IDEAS home Printed from https://ideas.repec.org/a/bla/bstrat/v34y2025i7p9188-9202.html

Artificial Intelligence (AI) Adoption and Green Investment: Driving Corporate Environmental Responsibility

Author

Listed:
  • Rabia Akram
  • Xiaojing Shi
  • Fahad Khalid
  • Mohit Srivastava

Abstract

Extant research has provided initial evidence on the application of artificial intelligence (AI) for corporate sustainable development. However, a research gap remains in understanding how AI specifically drives corporate green development, particularly in the realm of green investments. This research investigates the impact of AI adoption on corporate green investment (CGI) based on the sample of China's A‐share listed companies (2008–2022). By employing econometric techniques to examine panel data, an instrument variable with a two‐stage least squares approach, the Heckman selection model, and a series of robustness tests, this research finds that AI adoption positively correlates with CGI. The mechanism analysis reveals that AI adoption curbs managerial myopia and enhances technological resources to drive green investment levels. Moreover, the impact of AI adoption on CGI is pronounced when companies are headed by younger CEOs, those with higher education qualifications, and those with global exposure. This research enhances our overall comprehension of how digital innovation may be strategically utilized to promote sustainable development. It also provides significant insights for managers and policymakers who seek to facilitate environmentally friendly economic growth.

Suggested Citation

  • Rabia Akram & Xiaojing Shi & Fahad Khalid & Mohit Srivastava, 2025. "Artificial Intelligence (AI) Adoption and Green Investment: Driving Corporate Environmental Responsibility," Business Strategy and the Environment, Wiley Blackwell, vol. 34(7), pages 9188-9202, November.
    • Handle: RePEc:bla:bstrat:v:34:y:2025:i:7:p:9188-9202
    DOI: 10.1002/bse.70069
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/bse.70069
    Download Restriction: no
    File URL: https://libkey.io/10.1002/bse.70069?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
    ---><---

    More about this item

    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:bla:bstrat:v:34:y:2025:i:7:p:9188-9202. 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: Wiley Content Delivery (email available below). General contact details of provider: http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1099-0836 .

    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.