AI adoption in Malaysian SMEs: Barriers, enablers, and outcomes from a qualitative study

Abstract

AI adoption by Micro, Small, and Medium-sized Enterprises (MSMEs) in Malaysia remains low despite the wide availability of artificial intelligence (AI) tools, as well as government support initiatives. This study investigates barriers, enablers, and outcomes of AI adoption with emphasis on human and organizational factors. Using a qualitative research method, this study conducted interviews with decision makers from manufacturing, technology, and professional services to get insights on AI adoption. The results reveal that a low level of AI adoption among MSMEs is primarily a result of cost and technology barriers, showing instead that people, knowledge, and organizational culture deficits are more prominent contributors to the findings. Alternatively, AI illiterate (in terms of conceptual knowledge, lack of strategic vision, prompting capabilities) is the ultimate block. As for key enablers, great contributing factors are targeted training initiatives, the presence of a top management “AI-first” mindset, and the use of incremental learning pathways. Nonetheless, inconsistencies in policy implementation and limited trust in external vendors weaken institutional support mechanisms. The findings emphasise that successful AI adoption depends more on organizational AI literacy for a firm than on technology investment, and suggest that policymakers should prioritise capability building initiatives, educators develop curricula on AI targeted towards specific job roles, and MSME leaders should focus on upskilling human resources before they consider acquiring any technologies.