Inventing with Machines: Generative AI and the Evolving Landscape of IS Research
Authors: Gopal, Ram D.; Li, Jingjing; Riemer, Kai; Sarker, Suprateek; Singh, Param Vir; Susarla, Anjana; Bichler, Martin; Thatcher, Jason Bennett
Journal: Information Systems Research (2025)
DOI: 10.1287/isre.2025.editorial.v36.n4
<jats:p>Generative artificial intelligence (AI) is not merely changing how information systems (IS) research gets done—it is reshaping what research can be. We stand at a pivotal moment where machines can help generate hypotheses, synthesize vast literatures, and identify patterns that would take human researchers months to uncover. Yet, this unprecedented capability presents equally unprecedented risks to scholarly integrity. Because the field is uniquely positioned to understand sociotechnical transformations, IS research faces an extraordinary opportunity to pioneer “inventing with machines” while preserving the human insight and oversight that gives scholarship, as currently defined, its meaning. This transformation demands more than tool adoption. It requires a reimagination of scholarly infrastructure, norms, and practice. However, this transformation of research tooling creates a dangerous paradox: Powerful AI tools are now accessible to researchers who lack the technical literacy to understand and use them responsibly, threatening everything from citation accuracy to theoretical validity. Yet within this paradox lies the potential for revolutionary advances in how we craft…