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Survey study reveals significant knowledge, cost, and governance barriers hindering AI cybersecurity adoption in small and medium enterprises, highlighting critical digital skills gaps.
Artificial intelligence (AI) offers small and medium scale enterprises (SMEs) a potentially transformative route to stronger cybersecurity, yet adoption among such firms continues to lag markedly behind that of larger organisations. This study examines the barriers that hinder AI adoption for cybersecurity among SMEs, conceptualised across three functional barrier dimensions drawn from Innovation Resistance Theory: the value barrier (cost and return-on-investment uncertainty), the usage barrier (knowledge and skills gaps), and the risk barrier (governance and trust-related concerns). Anchored on Innovation Resistance Theory, the study formulated three objectives, three research questions and three corresponding hypotheses. A descriptive survey design was adopted, involving 220 purposively sampled owner-managers and information technology personnel of registered SMEs. Data were analysed using descriptive statistics and multiple linear regression at the 0.05 level of significance. Findings show that the value, usage and risk barriers each exert a statistically significant negative influence on the extent of AI adoption for cybersecurity, jointly explaining a substantial proportion of variance in adoption outcomes, with the usage (knowledge and skills) barrier emerging as the strongest predictor. The study concludes that AI adoption resistance among SMEs is best understood as a multi-dimensional, rational response to genuine resource and knowledge constraints rather than mere technological conservatism. Recommendations are offered for SME operators, policymakers and educational institutions engaged in digital capacity-building.
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Anthony et al. (2026) studied this question.