Beyond IT Adoption: The Evolving Boundaries of Diffusion Research in the AI Era

Communications of the Association for Information Systems Volume 57 Paper in press 2025 Beyond IT Adoption: The Evolving Boundaries of Diffusion Research in the AI Era Saeed Akhlaghpour University of Queensland, Elena Karahanna University of Georgia Eivor Oborn University of Warwick Hamed Qahri-Saremi Colorado State University Azadeh Savoli Université Côte d’Azure See next page for additional authors Follow this and additional works at: https://aisel.aisnet.org/cais Recommended Citation Akhlaghpour, S., Karahanna, E., Oborn, E., Qahri-Saremi, H., Savoli, A., Scott, S., & Tarafdar, M. (In press). Beyond IT Adoption: The Evolving Boundaries of Diffusion Research in the AI Era. Communications of the Association for Information Systems, 57, pp-pp. Retrieved from https://aisel.aisnet.org/cais/vol57/iss1/ 42 This material is brought to you by the AIS Journals at AIS Electronic Library (AISeL). It has been accepted for inclusion in Communications of the Association for Information Systems by an authorized administrator of AIS Electronic Library (AISeL). For more information, please contact . Beyond IT Adoption: The Evolving Boundaries of Diffusion Research in the AI Era Authors Saeed Akhlaghpour, Elena Karahanna, Eivor Oborn, Hamed Qahri-Saremi, Azadeh Savoli, Susan Scott, and Monideepa Tarafdar This article is available in Communications of the Association for Information Systems: https://aisel.aisnet.org/cais/ vol57/iss1/42 C ommunications of the A ssociation for I nformation S ystems Accepted Manuscript Beyond IT Adoption: The Evolving Boundaries of Diffusion Research in the AI Era Saeed Akhlaghpour The University of Queensland Australia 0000-0001-5305-8677 Elena Karahanna Eivor Oborn University of Georgia USA 0000-0002-1975-9231 University of Warwick UK 0000-0003-0566-4327 Hamed Qahri-Saremi Azadeh Savoli Colorado State University USA 0000-0002-4933-834X SKEMA Business School Université Côte d’Azure France 0000-0002-2879-5795 Susan Scott Monideepa Tarafdar Imperial College London UK 0000-0002-8775-9364 University of Massachusetts Amherst USA 0000-0003-2831-1364 Please cite this article as: Akhlaghpour, S., Karahanna, E., Oborn, E., Qahri-Saremi, H., Savoli, A., Scott, S., & Tarafdar, M. (in press). Beyond IT Adoption: The Evolving Boundaries of Diffusion Research in the AI Era. Communications of the Association for Information Systems. This is a PDF file of an unedited manuscript that has been accepted for publication in the Communications of the Association for Information Systems. We are providing this early version of the manuscript to allow for expedited dissemination to interested readers. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered, which could affect the content. All legal disclaimers that apply to the Communications of the Association for Information Systems pertain. For a definitive version of this work, please check for its appearance online at http://aisel.aisnet.org/cais/. Accepted Manuscript C ommunications of the A ssociation for I nformation S ystems Panel Report ISSN: 1529-3181 Beyond IT Adoption: The Evolving Boundaries of Diffusion Research in the AI Era Saeed Akhlaghpour The University of Queensland Australia 0000-0001-5305-8677 Elena Karahanna Eivor Oborn University of Georgia USA 0000-0002-1975-9231 University of Warwick UK 0000-0003-0566-4327 Hamed Qahri-Saremi Azadeh Savoli Colorado State University USA 0000-0002-4933-834X SKEMA Business School Université Côte d’Azure France 0000-0002-2879-5795 Susan Scott Monideepa Tarafdar Imperial College London UK 0000-0002-8775-9364 University of Massachusetts Amherst USA 0000-0003-2831-1364 Abstract: Artificial intelligence (AI), digital platforms, and algorithmic infrastructures are transforming the adoption and diffusion processes studied in Information Systems (IS) research. This panel report synthesizes and extends discussions from the 28th Annual DIGIT Workshop, highlighting critical shifts in diffusion research driven by AI advancements. The panel was hosted by the Special Interest Group on the Adoption and Diffusion of Information Technology (SIG ADIT), one of the longest-running groups affiliated with the Association for Information Systems (AIS). It convened senior scholars to explore how IS research must evolve to address these changes. The discussion centered on four key themes: rethinking traditional diffusion frameworks, embedding responsible and human-compatible AI design, navigating methodological innovation, and supporting early-career researchers in a rapidly changing landscape. The panel identified three interrelated tensions—innovation versus unintended consequences, scale versus ethical considerations, and speed versus deliberation—that amplify the importance of studying AI diffusion. These tensions call for IS researchers to adopt multi-level, longitudinal frameworks, integrate ethical governance considerations, responsibly leverage computational-qualitative methods, and embrace reflexive, value-sensitive theorizing. The report introduces an integrative model that captures these themes and tensions, and offers five pathways for future research to guide responsible and impactful AI adoption. Keywords: Diffusion Research, Artificial Intelligence (AI), Responsible Innovation, Human-Compatible AI, Reflexive Theorizing, Methodological Innovation, SIG ADIT. This manuscript underwent [editorial/peer] review. It was received xx/xx/20xx and was with the authors for XX months for XX revisions. [firstname lastname] served as Associate Editor.] or The Associate Editor chose to remain anonymous.] Accepted Manuscript Beyond IT Adoption: The Evolving Boundaries of Diffusion Research in the AI Era 1 Introduction Information systems (IS) research has long examined how innovations are adopted, diffused, and institutionalized (Burton-Jones, Stein, et al., 2020; Fichman, 2004; Hirschheim, 2007; Lucas Jr et al., 2008). More recently, the emergence of artificial intelligence (AI), digital platforms, and algorithmic infrastructures has transformed the scale, speed, and complexity of innovation processes, raising fundamental questions about what constitutes adoption, how value is distributed, and whose outcomes are measured. Scholars have begun to argue that traditional models of diffusion and impact are no longer sufficient (Madan & Ashok, 2023; Marabelli et al., 2021). In particular, the rise of AI technologies—ranging from predictive analytics and generative AI to conversational agents and decision automation—introduces new adoption logics and patterns of use. These developments have prompted growing calls to rethink the theoretical, methodological, and normative foundations of IS research in ways that foreground the evolving boundaries of diffusion and adoption in the context of i (...truncated)