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Here, There and Everywhere: On the Responsible Use of Artificial Intelligence (AI) in Management Research and the Peer‐Review Process

Author

Listed:
  • Caroline Gatrell
  • Daniel Muzio
  • Corinne Post
  • Christopher Wickert

Abstract

This editorial introduces and explains the Journal of Management Studies’ (JMS) new policy on artificial intelligence (AI). We reflect on the use of AI in conducting research and generating journal submissions and what this means for the wider JMS community, including our authors, reviewers, editors, and readers. Specifically, we consider how AI‐generated research and text could both assist and augment the publication process, as well as harm it. Consequentially, our policy acknowledges the need for careful oversight regarding the use of AI to assist in the authoring of texts and in data analyses, while also noting the importance of requiring authors to be transparent about how, when and where they have utilized AI in their submissions or underlying research. Additionally, we examine how and in what ways AI's use may be antithetical to the spirit of a quality journal like JMS that values both human voice and research transparency. Our editorial explains why we require author teams to oversee all aspects of AI use within their projects, and to take personal responsibility for accuracy in all aspects of their research. We also explain our prohibition of AI's use in peer‐reviewers’ evaluations of submissions, and regarding editors’ handling of manuscripts.

Suggested Citation

  • Caroline Gatrell & Daniel Muzio & Corinne Post & Christopher Wickert, 2024. "Here, There and Everywhere: On the Responsible Use of Artificial Intelligence (AI) in Management Research and the Peer‐Review Process," Journal of Management Studies, Wiley Blackwell, vol. 61(3), pages 739-751, May.
    • Handle: RePEc:bla:jomstd:v:61:y:2024:i:3:p:739-751
    DOI: 10.1111/joms.13045
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    References listed on IDEAS

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    1. Paul M. Leonardi, 2021. "COVID‐19 and the New Technologies of Organizing: Digital Exhaust, Digital Footprints, and Artificial Intelligence in the Wake of Remote Work," Journal of Management Studies, Wiley Blackwell, vol. 58(1), pages 249-253, January.
    2. Michael Haenlein & Andreas Kaplan & Chee-Wee Tan & Pengzhu Zhang, 2019. "Artificial intelligence (AI) and management analytics," Journal of Management Analytics, Taylor & Francis Journals, vol. 6(4), pages 341-343, October.
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    Cited by:

    1. Martin Obschonka & Denis A. Grégoire & Boris Nikolaev & Frédéric Ooms & Moren Lévesque & Jeffrey M. Pollack & Tara S. Behrend, 2025. "Artificial Intelligence and Entrepreneurship: A Call for Research to Prospect and Establish the Scholarly AI Frontiers," Entrepreneurship Theory and Practice, , vol. 49(3), pages 620-641, May.
    2. Gazi Islam & Michelle Greenwood, 2024. "Generative Artificial Intelligence as Hypercommons: Ethics of Authorship and Ownership," Journal of Business Ethics, Springer, vol. 192(4), pages 659-663, July.
    3. Zhong, Xi & She, Jianquan & Wu, Xiaojie, 2024. "Tech for social good: Artificial intelligence and workplace safety," Technology in Society, Elsevier, vol. 79(C).
    4. Andrew Delios & Rosalie L. Tung & Arjen Witteloostuijn, 2025. "How to intelligently embrace generative AI: the first guardrails for the use of GenAI in IB research," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 56(4), pages 451-460, June.
    5. Felix Lorenz & Solvej Lorenzen & Matheus Franco & Julius Velz & Thomas Clauß, 2026. "Generative artificial intelligence in management research: a practical guide on mistakes to avoid," Management Review Quarterly, Springer, vol. 76(1), pages 157-177, February.

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