IDEAS home Printed from https://ideas.repec.org/a/spr/joamsc/v53y2025i3d10.1007_s11747-024-01064-3.html
   My bibliography  Save this article

How generative AI Is shaping the future of marketing

Author

Listed:
  • Dhruv Grewal

    (Babson College
    University of Bath
    Tecnológico de Monterrey)

  • Cinthia B. Satornino

    (University of New Hampshire)

  • Thomas Davenport

    (UVA Darden School of Business)

  • Abhijit Guha

    (Florida Atlantic University
    University of South Carolina)

Abstract

Generative AI (Gen AI) is shaping the future of marketing. In the next decade, Gen AI will influence how marketers interact and communicate with customers, help create and deliver marketing content (text, images, and video), and inform methods for researching and developing new products and services. In both service and sales settings, Gen AI will affect customers directly and significantly. Therefore, marketers, researchers, and public policy makers require a clear understanding of Gen AI and its potential, as well as its limitations. To assist marketers in thinking through the adoption and implementation of Gen AI, the current article presents a four-quadrant organizing framework that highlights trade-offs in both the nature of Gen AI inputs and the extent of human augmentation needed to deliver Gen AI–generated outputs. This framework provides guidance for the selection and implementation of Gen AI tools, as well as recommendations for further research.

Suggested Citation

  • Dhruv Grewal & Cinthia B. Satornino & Thomas Davenport & Abhijit Guha, 2025. "How generative AI Is shaping the future of marketing," Journal of the Academy of Marketing Science, Springer, vol. 53(3), pages 702-722, May.
  • Handle: RePEc:spr:joamsc:v:53:y:2025:i:3:d:10.1007_s11747-024-01064-3
    DOI: 10.1007/s11747-024-01064-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11747-024-01064-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11747-024-01064-3?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:spr:joamsc:v:53:y:2025:i:3:d:10.1007_s11747-024-01064-3. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.