Academic Publishing in the Age of Generative AI

Academic peer-reviewed journals turn a growing universe of ideas into credible scientific signals (Yoo 2024 ), based on shared norms about what counts as a contribution. This task rests on three limited resources: editorial attention, reviewer time, and audience attention to read and digest the results. However, Generative AI (GenAI) is reshaping each of them. GenAI reduces the effort required to create manuscripts. It even enables increasingly engineered research workflows that automate entire parts of the research process, including literature search, programming/implementation, analysis, and writing (Lund et al. 2024 ). This trend is no exception in the information systems (IS) community, which, however, usually recognizes the disruptive nature of this development faster than many other disciplines. For example, a current special issue of the Information Systems Research journal explicitly seeks papers that demonstrate “ novel research capabilities enabled by GenAI ” (Abbasi et al. 2026 ). However, from a journal’s perspective, these changes present tremendous challenges: When the costs of producing submission-ready manuscripts decrease substantially, the work on the reviewers’ side increases inversely.