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18 décembre 2020
- handle: 10670/1.as0a4i
- hal: hal-03701824
- doi: 10.1007/978-3-030-64849-7_9
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info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-030-64849-7_9
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Jayanthi Radhakrishnan et al., « Determinants and Barriers of Artificial Intelligence Adoption – A Literature Review », HAL-SHS : sciences de l'information, de la communication et des bibliothèques, ID : 10.1007/978-3-030-64849-7_9
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Different theories, models and frameworks have been used to study technology adoption, some explaining the determinants of adoption at the individual level, some at the organizational level and some at both. As Artificial Intelligence (AI) is gaining traction in many sectors, it will be beneficial to understand the determinants and barriers to AI adoption. In this paper, an attempt has been made to review journal articles and other reports pertaining to AI adoption and understand the adoption theories used and the factors that facilitate and those that hinder AI adoption. Articles on adoption studies of autonomous vehicles, big data analytics, robots and cognitive engagement applications dominated the list of journal articles. Diffusion of Innovation, Technology, Organization and Environment Framework and the unified theory of acceptance and use of technology (UTAUT) were some of the dominant theories/frameworks used. Factors influencing adoption at the individual level were related to trust, security, purchase price, intrinsic motivation, social influence, utilitarian benefit whereas at the organizational level, it was related to the technical competencies, strategic road mapping for AI, top management support and the digital maturity of the organization.