Artificial Intelligence in Small and Medium-Sized Enterprises: Mapping Research Evolution and Future Directions

The rapid diffusion of artificial intelligence (AI), particularly following the emergence of generative AI and large language models, has accelerated digital transformation among small and medium-sized enterprises (SMEs), leading to a substantial increase in academic research. Despite this growth, the literature remains fragmented regarding its intellectual foundations, conceptual evolution, and organizational implications. This study aims to systematically map and synthesize the scientific literature on AI in SMEs by integrating bibliometric analysis with a systematic literature review (B-SLR). Bibliographic data were retrieved exclusively from the Web of Science Core Collection (WoSCC). Following the PRISMA 2020 protocol, 345 peer-reviewed journal articles published between 2018 and 2026 were retained for analysis. Bibliometric performance analysis and science mapping were conducted using Bibliometrix (Biblioshiny), including publication trends, thematic evolution, co-occurrence analysis, thematic mapping, country collaboration and Three-Fields Plot synthesis of the literature. The findings reveal a rapid expansion of AI research in SMEs, particularly after 2023, accompanied by a gradual shift from technology-oriented studies toward organizational value creation, strategic management, innovation, and sustainability. Machine learning emerged as the dominant and most persistent research theme, while generative AI, human–AI collaboration, AI governance, and employee-centered perspectives were identified as promising but underexplored research directions. By integrating bibliometric science mapping with systematic evidence synthesis, this study provides a comprehensive overview of the intellectual, conceptual, and social structures of the field and proposes a future research agenda that contributes to organizational behavior, strategic management, and AI adoption research in SMEs.