Factors influencing the adoption of artificial intelligence systems: A systematic literature review

Author Identifier

Ahmad A. Khanfar: https://orcid.org/0000-0002-2696-4604

Reza Kiani Mavi: https://orcid.org/0000-0002-9998-1296

Mohammad Iranmanesh: https://orcid.org/0000-0001-6964-6238

Denise Gengatharen: https://orcid.org/0000-0003-3412-3028

Document Type

Journal Article

Publication Title

Management Decision

Publisher

Emerald

School

School of Business and Law

Comments

Khanfar, A. A., Kiani Mavi, R., Iranmanesh, M., & Gengatharen, D. (2025). Factors influencing the adoption of artificial intelligence systems: A systematic literature review. Management Decision. Advance online publication. https://doi.org/10.1108/MD-05-2023-0838

Abstract

Purpose: Despite the potential of artificial intelligence (AI) systems to increase revenue, reduce costs and enhance performance, their adoption by organisations has fallen short of expectations, leading to unsuccessful implementations. This paper aims to identify and elucidate the factors influencing AI adoption at both the organisational and individual levels. Developing a conceptual model, it contributes to understanding the underlying individual, social, technological, organisational and environmental factors and guides future research in this area. Design/methodology/approach: The authors have conducted a systematic literature review to synthesise the literature on the determinants of AI adoption. In total, 90 papers published in the field of AI adoption in the organisational context were reviewed to identify a set of factors influencing AI adoption. Findings: This study categorised the factors influencing AI system adoption into individual, social, organisational, environmental and technological factors. Firm-level factors were found to impact employee behaviour towards AI systems. Further research is needed to understand the effects of these factors on employee perceptions, emotions and behaviours towards new AI systems. These findings led to the proposal of a theory-based model illustrating the relationships between these factors, challenging the assumption of independence between adoption influencers at both the firm and employee levels. Originality/value: This study is one of the first to synthesise current knowledge on determinants of AI adoption, serving as a theoretical foundation for further research in this emerging field. The adoption model developed integrates key factors from both the firm and individual levels, offering a holistic view of the interconnectedness of various AI adoption factors. This approach challenges the assumption that factors at the firm and individual levels operate independently. Through this study, information systems researchers and practitioners gain a deeper understanding of AI adoption, enhancing their insight into its potential impacts.

DOI

10.1108/MD-05-2023-0838

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