Exploring Challenges For Artificial Intelligence Readiness in SMEs in Sri Lanka

Abstract

AI technology adoption looks pretty challenging for the SME sector. Studies explain the challenges and barriers; AI readiness is context-based, and there is limited context-specific research on how Sri Lanka’s socioeconomic and infrastructural conditions shape these issues. Existing global models of AI readiness often fail to capture these localised realities, making them less applicable in the Sri Lankan Context. The study aims to identify and analyse challenges to AI adoption in Sri Lankan SMEs and assess AI-readiness among SMEs in Sri Lanka. The researcher applied qualitative research methodology to analyse the key factors. A purposive sampling method was used to select the research respondents. An in-depth interview was conducted to collect primary data from the subject. The researcher utilised coding and thematic analysis to analyse the data. The findings revealed three key factors, namely AI knowledge, macro environment, and microenvironment, that influence the artificial intelligence readiness of SEMs. The challenge of AI knowledge consists of AI awareness, AI benefits, and AI technology implementation. Macro environmental factors include AI ethics, AI society, economic, political, legal (Regulation), competition, and technological factors. The micro environment includes organisational structure, culture, financial, human resources, and data strategy. The result of the study reveals that Small and Medium Enterprises (SMEs) in Sri Lanka face considerable challenges in adopting AI technology; most SMEs in Sri Lanka are not fully ready to embrace AI technology. In addition, the researcher found that AI applications vary for specific sectors, and most SMEs do not have explicit knowledge about AI applicationsThis finding emphasised the need for academic inquiry into the role of education and training programs to address gaps in AI knowledge and awareness, which are foundational for SMEs' successful adoption of AI technologies. Furthermore, the findings underscore the importance of studying external factors such as AI ethics, AI society, Economic, Political, and legal (Regulation) challenges, Data Strategy, Competition, and Technological challenges to understand better how macro-environmental conditions shape SMEs' AI strategies.