Adoption of Artificial Intelligence in Micro Small and Medium Enterprises
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Abstract:
Background of study: Artificial Intelligence (AI) is transforming business operations globally, yet its adoption in Micro, Small, and Medium Enterprises (MSMEs) remains limited, particularly in developing economies. MSMEs face multiple constraints, including limited digital infrastructure, lack of awareness, and resistance to change, making it challenging to integrate AI technologies effectively.
Aims and scope of paper: This paper aims to explore the enabling factors and barriers to AI adoption among MSMEs, with a focus on the mediating role of accounting automation and the influence of institutional support. The study also highlights the importance of organizational readiness and external policy frameworks in driving digital transformation at the MSME level.
Methods: A qualitative exploratory approach was adopted, incorporating data from in-depth interviews with MSME owners, government representatives, and technology experts. The study also utilized secondary sources such as policy reports, prior academic research, and case studies. Thematic content analysis was used to extract key themes from the data.
Result: Findings indicate that while awareness of AI benefits is increasing, practical adoption remains low due to cost concerns, inadequate infrastructure, and limited technical expertise. Government support programs are inconsistently accessed, and accounting automation acts as both a driver and a challenge depending on the firm’s digital maturity.
Conclusion: The adoption of AI in MSMEs requires a multi-dimensional strategy that includes targeted policy interventions, awareness campaigns, and capacity-building efforts. Organizational culture, leadership commitment, and access to affordable digital tools are essential to accelerating AI integration in the MSME sector.
Keywords: Artificial Intelligence, Barriers , Government Initiatives, MSMEsv
Copyright (c) 2025 Abdul Jamal. M, Hanh Thi Pham, Shahul Hameed. M, Sadique Ahmed. R
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
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