Artificial Intelligence Adoption, Implementation Barriers, and Business Impact in Small and Medium-Sized Enterprises: A Systematic Literature Review
TL;DR
These findings highlight the necessity of customized implementation strategies, focused capacity-building initiatives, encouraging legislative frameworks, and multi-stakeholder cooperation to promote inclusive, responsible AI integration in SMEs.
Abstract
The empirical and conceptual research on artificial intelligence (AI) adoption in small and medium-sized enterprises (SMEs) that was published between 2019 and 2025 is compiled in this systematic literature review. This evaluation incorporates information from three main research domains: AI applications in business operations, adoption enablers and barriers, and organizational performance results. It is based on fifty peer-reviewed articles that were found through searches of Scopus, Web of Science, and IEEE Xplore. Results show that in order to improve customer service, marketing automation, and operational efficiency, SMEs primarily use machine learning, natural language processing, and chatbot technologies. While financial limitations, a lack of skills, and insufficient digital infrastructure continue to be obstacles, top management support, technical preparedness, and staff capability emerge as crucial organizational facilitators. Although adoption rates are still concentrated among larger organizations, AI adoption is correlated with quantifiable increases in operational efficiency, cost reduction, customer retention, and innovation performance. There are clear regional differences, with rising nations in Latin America and Asia spearheading adoption despite more limited resources. Significant research gaps about long-term sustainability, contextual differences among developing economies, ethical governance frameworks, and the efficacy of support interventions are identified by the review. To promote inclusive, responsible AI integration in SMEs, our findings highlight the necessity of customized implementation strategies, focused capacity-building initiatives, encouraging legislative frameworks, and multi-stakeholder cooperation. For practitioners, governments, and researchers looking to close the gap in AI adoption and uncover revolutionary potential for small businesses worldwide, this paper offers practical ideas.