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Inventing with Machines: Generative AI and the Evolving Landscape of IS Research

Summary

An ISR editorial by the senior-editor team arguing that generative AI is not merely changing how IS research is done but what it can be. Authors frame this as "a pivotal moment where machines can help generate hypotheses, synthesize vast literatures, and identify patterns that would take human researchers" much longer, and lay out how this shift reshapes the IS research landscape across methods, theorising, and the role of researchers themselves.

Contribution

A statement-of-direction editorial that situates IS as the discipline charged with theorising and shaping the human-machine partnership in research practice, and positions itself as the operational successor to Susarla et al. (2023) "Janus Effect" responsible-conduct agenda.

Method

Editorial / agenda-setting piece authored by the ISR senior editorial team and IS thought leaders.

Relevance to RISE

Together with 1 and 2, this is the ISR-side anchor for the RISE programme's claim that the IS discipline should lead inquiry into agentic research pipelines. The "machines generate hypotheses … synthesize vast literatures … identify patterns" framing is exactly the capability map RISE catalog projects (e.g. storm, open-scholar, research-town) are built around.

Critique / open questions

As an editorial, claims are programmatic rather than empirically substantiated; the visible excerpt does not yet specify which methodological practices need to change or how to evaluate machine-assisted IS research.

Key quotes

"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" much longer.

  1. Susarla, A., Gopal, R., Thatcher, J. B., & Sarker, S. (2023). The Janus effect of generative AI: Charting the path for responsible conduct of scholarly activities in information systems. Information Systems Research, 34(2). https://doi.org/10.1287/isre.2023.ed.v34.n2 ↩

  2. Schwartz, D., & Te’eni, D. (2024). AI for knowledge creation, curation, and consumption in context. Journal of the Association for Information Systems, 25(1), 37–47. https://doi.org/10.17705/1jais.00862 ↩