Abstract
While Artificial Intelligence (AI) is a transformative technology, its organizational adoption remains a major socio-technical challenge. To structure the fragmented discourse relevant to Information Systems (IS) Engineering, this paper conducts a bibliometric analysis of 1,575 Web of Science publications (2019–2026). The analysis identifies four foundational strands: acceptance theories, strategic firm-level adoption, human-AI trust, and innovation diffusion. Thematic mapping reveals technical infrastructure, organizational readiness, Human-AI Interaction and Governance, and contextual concerns as central dimensions. A comparison with socio-technical frameworks and recent reviews suggests that current research remains fragmented across these dimensions. Interpreted through Requirements Engineering literature, these findings indicate that adoption concerns such as trust, explainability, and ethics can inform non-functional requirements (NFRs) and socio-technical design considerations for more adoption-aware IS Engineering.
Paper Type
Full Paper
DOI
10.62036/ISD.2026.6
Mapping the Landscape of AI Adoption: A Bibliometric Analysis of its Intellectual Structure and Thematic Evolution
While Artificial Intelligence (AI) is a transformative technology, its organizational adoption remains a major socio-technical challenge. To structure the fragmented discourse relevant to Information Systems (IS) Engineering, this paper conducts a bibliometric analysis of 1,575 Web of Science publications (2019–2026). The analysis identifies four foundational strands: acceptance theories, strategic firm-level adoption, human-AI trust, and innovation diffusion. Thematic mapping reveals technical infrastructure, organizational readiness, Human-AI Interaction and Governance, and contextual concerns as central dimensions. A comparison with socio-technical frameworks and recent reviews suggests that current research remains fragmented across these dimensions. Interpreted through Requirements Engineering literature, these findings indicate that adoption concerns such as trust, explainability, and ethics can inform non-functional requirements (NFRs) and socio-technical design considerations for more adoption-aware IS Engineering.
Recommended Citation
Scheuerer, P. & Westner, M.(2026). Mapping the Landscape of AI Adoption: A Bibliometric Analysis of its Intellectual Structure and Thematic Evolution. In M. Valenta, B. Mannová, R. Pergl, A. Przybylek, M. Lang, H. Linger, C. Schneider, N. Iivari, & E. Insfran (Eds.), Making ISD Sustainable: Reloaded with AI and Automation (ISD2026 Proceedings). Prague, Czech Republic: Czech Technical University in Prague. ISBN: 978-80-01-07585-2. https://doi.org/10.62036/ISD.2026.6