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

  • Hemant K. Bhargava
  • , Susan Brown
  • , Anindya Ghose
  • , Alok Gupta
  • , Dorothy Leidner
  • , D. J. Wu

Research output: Contribution to journalArticlepeer-review

1 Scopus 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.

Original languageEnglish (US)
Article number19
JournalACM Transactions on Management Information Systems
Volume16
Issue number2
DOIs
StatePublished - May 8 2025

Keywords

  • Generative Artificial Intelligence (GenAI)
  • Large Language Models (LLMs)
  • peer review
  • research integrity

ASJC Scopus subject areas

  • Management Information Systems
  • General Computer Science

Fingerprint

Dive into the research topics of 'Exploring Generative AI's Impact on Research: Perspectives from Senior Scholars in Management Information Systems'. Together they form a unique fingerprint.

Cite this