Exploring the Barriers and Enablers of Artificial Intelligence Adoption Among SMEs in the Apparel Industry in the Western Province of Sri Lanka : A qualitative study on how Apparel SMEs owners and managers perceive the adoption of Artificial Intelligence

Sammanfattning

Artificial intelligence in recent years has become a transformative force in the future of business.However, the adoption of these AI technologies does not happen in an equal level among differentbusinesses. For small and medium-sized enterprises operating in labor-intensive sectors across thedeveloping world, the gap between AI's promise and its practical reality remains wide and not wellunderstood. This study takes that gap as its starting point.Specifically, it focuses on owner-managers in the apparel industry of Sri Lanka's Western Province.This setting combines significant economic weight with acute resource constraints and asks howthey make sense of AI adoption. The study informed by the Technology Organization Environmentand framework and Diffusion of Innovation theory.The research follows a qualitative and interpretivist orientation. The study has conducted ten semistructuredinterviews with SME owners and managers. The resulting data were analyzed throughreflexive thematic analysis, following Braun and Clarke's (2006) six-step framework. Theemphasis throughout was on staying close to participants' own accounts rather than fitting themprematurely into theoretical boxes.The research has resulted in five themes from the analysis. The first concerns financial constraints.These constraints include not only the upfront cost of AI tools, but also the broader economicuncertainty within which these businesses operate. The second theme addresses workforcereadiness. Most participants described a workforce with uneven digital skills, and several notedoutright employee resistances to technology led change. Third, the study examines currenttechnological infrastructure and data readiness. Both of these factors were found to be fragmentedand poorly matched to the demands of AI implementation. Fourth, and perhaps most strikingly,decision-making in these firms is deeply centralized around the owner-manager figure and theirpersonal risk of tolerance. The fifth theme captures the pull side of the equation. The competitivepressure from international buyers, market expectations around digital standards, and the growingdigital confidence of younger employees all emerged as meaningful, if sometimes insufficient,drivers toward adoption.Collectively, the research findings reveal that while participants broadly acknowledged the longtermstrategic value of AI, actual adoption remains limited and uneven. What they expressed wasnot skepticism about the technology itself, but a very practical uncertainty about whether theconditions for AI adoption could realistically be met.This study contributes to the understanding of AI adoption among apparel SMEs operating indeveloping economies. The findings suggest that technological, organizational, and environmentalfactors collectively shape AI adoption decisions. When resource and capability constraints exist,perceived benefits alone may not be enough to drive adoption.The findings offer actionable guidance for policymakers, technology providers, and industrystakeholders seeking to support inclusive digital transformation within resource constrained SMEenvironments.