Abstract

The rapid diffusion of generative AI into academic workflows has created a structural tension in scholarly publishing. On one side, AI offers genuine productivity gains — literature synthesis, writing assistance, code generation. On the other hand, it introduces systemic risks that journals were never designed to manage, such as synthetic data, ghostwritten manuscripts, fabricated citations, and automated reviews that mimic but do not replicate critical scholarly judgment. Information Systems (IS), as a discipline that studies technology and organizations, occupies a uniquely reflexive position in this debate — IS scholars are simultaneously subject to these pressures and among the best-placed to theorize and respond to them.

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