Prediction, hype, and fear: Advancing Information Systems research in “the AI age”
Journal
Journal of InfoTrmation Technology (JIT)
Type
journal article
Date Issued
2026-06-12
Author(s)
Research Team
IWI6
Abstract
Information Systems (IS) research is well-positioned but under-equipped to study technological futures at a time when claims about artificial intelligence (AI) are reshaping investment, policy, and public discourse. This perspective advances three arguments. First, IS scholarship should engage more systematically with digital futures, drawing on approaches for reasoning under uncertainty, such as Bayesian methods and established Futures Studies techniques, to distinguish prediction, projection, possibility, and hype. Second, technology hype is itself a legitimate object of IS research, and widely used frameworks such as the Gartner Hype Cycle appear limited in their ability to inform practice. Third, AI serves as a critical test case, combining heavy supply-side investment with unproven demand-side impact and unresolved questions of value and consequence. We propose four analytically distinct lenses for studying AI, namely, capability, adoption, value, and consequence, and identify two underexamined blind spots: bad actors deploying AI at scale and structural over-dependence on imperfect AI. We invite contributions to the Journal of Information Technology that examine how claims about technological futures are produced, circulated, institutionalized, resisted, and realized.
Language
English
Keywords
digital futures
futures studies
technology hype
S-curve
Gartner Hype Cycle
artificial intelligence
IS research agenda
HSG Classification
contribution to scientific community
Refereed
Yes
Subject(s)
Division(s)