Type: article
Abstract: Although artificial intelligence (AI) is reshaping processes, governance structures, and value chains, its implementation in business-to-business (B2B) contexts often lags behind expectations. Existing technology adoption models typically assume linear, stage-based processes, overlooking the dynamic and intersection-based nature of AI adoption. Based on 36 semi-structured interviews, this study examines the intersections of the technological, organizational, and environmental dimensions of the TOE framework. Focusing on TOE intersections, we identify 19 mechanisms – nine constraining and ten reinforcing – that shape AI adoption trajectories. Building on these insights, we develop an intersection-based spiral model, conceptualizing AI adoption as continuous cycles of alignment and reconfiguration, moving beyond linear stage-based frameworks. By doing so, we advance a holistic understanding of AI adoption dynamics and reposition TOE research from isolated dimensions toward their intersections.
Authors: Smirnova, Maria M., Henkel, Dominik A.
Institution: University of Bamberg
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7222988768