Document Type
Journal Article
Publication Title
Information Technology and Management
Publisher
Springer
School
School of Business and Law
RAS ID
71723
Abstract
The adoption of artificial intelligence (AI) systems is on the rise owing to their many benefits. This study conducted a bibliometric analysis to identify (1) how the literature on AI adoption has evolved over the past few years, (2) key themes associated with AI adoption in the literature, and (3) the gaps in the literature. To achieve these objectives, we utilised the Biblioshiny of R-package bibliometric analysis tool to analyse the AI adoption literature. A total of 91 articles were reviewed and analysed in this study. Four major themes were identified: AI, machine learning, the unified theory of acceptance and use of technology (UTAUT) model and the technology acceptance model (TAM). Using a content analysis of the identified themes, the study gained additional insight into the studies on AI adoption. Previous studies have been limited to specific industries and systems, and adoption theories like the UTAUT and TAM have also been utilised to a limited extent. Directions for future studies were provided.
DOI
10.1007/s10799-024-00435-0
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Comments
Khanfar, A. A., Kiani Mavi, R., Iranmanesh, M., & Gengatharen, D. (2024). Determinants of artificial intelligence adoption: Research themes and future directions. Information Technology and Management. Advance online publication. https://doi.org/10.1007/s10799-024-00435-0