Managerial Mindset and AI Adoption in SMEs. A Systematic Review of Cognitive, Behavioural, and Institutional Foundations
Managerial Mindset and AI Adoption in SMEs. A Systematic Review of Cognitive, Behavioural, and Institutional Foundations

Summary/Abstract: Purpose: This study examines how managerial mindsets shape the adoption of artificial intelligence (AI) in small and medium-sized enterprises (SMEs). While existing research often highlights resource or capability constraints, this review shows that deeper cognitive, behavioral, and institutional foundations strongly influence how managers interpret AI and decide whether to engage with it. Design, Methodology, and Approach: A systematic literature review (SLR) was conducted using established protocols. Thirty influential studies across managerial cognition, behavioral strategy, institutional theory, and technology adoption were identified, screened, and synthesized. Their insights were integrated into a multilayered conceptual model explaining how mindsets shapes AI adoption in SMEs, with particular attention to post-transitional economies. Findings: The review shows that a layered mindset architecture shapes AI adoption. Institutional imprints provide the historical and cultural backdrop for managerial assumptions, cognitive schemas influence how managers attend to and interpret AI, and behavioral dispositions determine how they act under uncertainty. Technology adoption constructs (such as perceived usefulness, ease of use, and social influence) reflect these deeper layers rather than operate as independent drivers. Originality: The study offers the first integrated model linking institutional imprints, cognitive schemas, behavioral tendencies, and technology adoption constructs. It reframes AI adoption as a psychologically and institutionally embedded process rather than operating as independent drivers.

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