IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v189y2025ics0148296324006647.html
   My bibliography  Save this article

Generative artificial intelligence (GenAI) revolution: A deep dive into GenAI adoption

Author

Listed:
  • Kumar, Aman
  • Shankar, Amit
  • Hollebeek, Linda D.
  • Behl, Abhishek
  • Lim, Weng Marc

Abstract

This study examines key reasons (for and against) that influence business-to-business (B2B) managers’ intention to adopt generative artificial intelligence (GenAI). We also investigate how GenAI adoption influences firm performance, along with the moderating effect of ethical leadership. Study 1 undertakes a series of in-depth interviews, yielding a set of hypotheses that are tested in Study 2. A total of 277 responses was collected from respondents in the USA, the UK, Canada, India, Australia, Malaysia, and Japan to test the proposed model using structural equation modeling. The findings highlight that need for uniqueness, information completeness, convenience, and deceptiveness significantly impact GenAI adoption. The results also highlight that GenAI adoption boosts firm performance. Finally, ethical leadership was found to moderate the effect of GenAI adoption on firm performance. This study enriches the GenAI, technology adoption, and behavioral reasoning theory literatures while also providing pertinent insights for firms intending to adopt GenAI.

Suggested Citation

  • Kumar, Aman & Shankar, Amit & Hollebeek, Linda D. & Behl, Abhishek & Lim, Weng Marc, 2025. "Generative artificial intelligence (GenAI) revolution: A deep dive into GenAI adoption," Journal of Business Research, Elsevier, vol. 189(C).
    • Handle: RePEc:eee:jbrese:v:189:y:2025:i:c:s0148296324006647
    DOI: 10.1016/j.jbusres.2024.115160
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296324006647
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jbusres.2024.115160?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.

    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:jbrese:v:189:y:2025:i:c:s0148296324006647. 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/jbusres .

    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.