Exploring Generative AI’s Impact on Research: Perspectives from Senior Scholars in Management Information Systems

This commentary reflects on insights from a panel discussion at the 2024 Annual MIS Academic Leadership Conference, where six senior MIS scholars discussed the impact of Generative AI on scholarly research and peer review. The discussion underscored the importance of responsible use, transparency, and ethical standards, as well as the irreplaceable role of human judgment in maintaining research integrity. This commentary explores the potential of Generative AI as a collaborative tool across various stages of the research lifecycle, highlighting the "human-in-the-loop" approach to harness AI's capabilities while preserving essential human insight. This commentary synthesizes the senior scholars’ perspectives on the responsible integration of Generative AI, emphasizing opportunities to enhance research efficiency and foster interdisciplinary collaboration, while advocating for policies that ensure AI supports—rather than substitutes—human intellectual contributions in academic research.

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Publication Details

Journal
ACM Transactions on Management Information Systems
Published
2025-03-26
DOI
https://doi.org/10.1145/3721846
Citations
2
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
4.57
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article

Exploring Generative AI’s Impact on Research: Perspectives from Senior Scholars in Management Information Systems

Susan A. Brown, Hemant K. Bhargava, Alok Gupta, D. J. Wu et al.
2 citations
ACM Transactions on Management Information Systems
Big Data and Business Intelligence
4.57
article

Exploring Generative AI’s Impact on Research: Perspectives from Senior Scholars in Management Information Systems

Susan A. Brown, Hemant K. Bhargava, Alok Gupta, D. J. Wu, Dorothy E. Leidner, Anindya Ghose
article en
2 citations

Abstract

This commentary reflects on insights from a panel discussion at the 2024 Annual MIS Academic Leadership Conference, where six senior MIS scholars discussed the impact of Generative AI on scholarly research and peer review. The discussion underscored the importance of responsible use, transparency, and ethical standards, as well as the irreplaceable role of human judgment in maintaining research integrity. This commentary explores the potential of Generative AI as a collaborative tool across various stages of the research lifecycle, highlighting the "human-in-the-loop" approach to harness AI's capabilities while preserving essential human insight. This commentary synthesizes the senior scholars’ perspectives on the responsible integration of Generative AI, emphasizing opportunities to enhance research efficiency and foster interdisciplinary collaboration, while advocating for policies that ensure AI supports—rather than substitutes—human intellectual contributions in academic research.

ACM Transactions on Management Information SystemsVol. 16(2)
Georgia Institute of Technology (US), University of Arizona (US), University of Minnesota System (US), University of Virginia (US), New York University (US), University of California, Davis (US)
Openalex Percentile: Top 7%
Big Data and Business Intelligence
4.57
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Exploring Generative AI’s Impact on Research: Perspectives from Senior Scholars in Management Information Systems — Susan A. Brown, Hemant K. Bhargava, et al. · ACM Transactions on Management Information Systems (2025) | TGRS Research Map | TGRS