Artificial Intelligence for Sustainable SMEs: A Bibliometric Analysis of Trends and Future Directions

This study investigates the surprisingly limited adoption of artificial intelligence (AI) among small and medium-sized enterprises (SMEs) in the context of sustainable development, particularly within developing countries. Despite the transformative potential of AI to enhance competitiveness and sustainability, SMEs continue to face structural barriers, including low digital literacy, inadequate policy support, and limited access to technology. Addressing this gap, the research aims to systematically map the evolving landscape of academic studies at the intersection of AI, sustainability, and SMEs. Using a Systematic Literature Review (SLR) approach, the study analyzed 36 relevant articles published between 2018 and 2025, sourced from the Scopus database. Tools such as RStudio (Bibliometrix) and VOSviewer were employed for bibliometric and content analysis. Descriptive statistics revealed an increasing trend in scholarly output, collaborative research, and diverse thematic focus. Thematic and conceptual analyses identified three dominant clusters: digitalization of SMEs, AI-driven sustainable innovation, and organizational performance. Temporal evolution mapping revealed a maturing research focus, transitioning from foundational themes to policy-aligned applications, such as the Sustainable Development Goals (SDGs). The study contributes to theory by uncovering thematic shifts and conceptual structures that guide AI adoption in SMEs. Practically, it highlights strategic areas for policy intervention, collaborative innovation, and digital readiness. While the study is limited to literature indexed in Scopus, future research may expand the scope by utilizing additional databases and incorporating qualitative insights to validate and further develop the current findings. Keywords: Artificial Intelligence (AI), AI-driven sustainable innovation, Sustainability, Sustainable Development Goals (SDGs), SMEs