Artificial Intelligence as a Catalyst for Sustainable Digital Transformation in Small and Medium-Sized Enterprises: A Systematic Literature Review
DOI:
https://doi.org/10.53273/7fd8bw76Abstract
Small and medium-sized enterprises (SMEs) face critical imperatives to adopt artificial intelligence (AI) to enhance competitiveness while simultaneously adhering to environmental and social sustainability targets. This systematic literature review synthesizes empirical evidence on AI-driven digital transformation within SMEs through an integrated theoretical framework combining the Resource-Based View (RBV), Dynamic Capabilities (DC), and the Triple Bottom Line (TBL). Following PRISMA 2020 guidelines, we systematically identified, screened, and analyzed 34 peer-reviewed primary empirical studies published between 2016 and 2026 across Scopus, Web of Science, IEEE Xplore, and ScienceDirect. The synthesized findings demonstrate that AI acts as an effective catalyst for sustainable transformation across economic efficiency, environmental stewardship, and social inclusion. However, value realization is heavily moderated by organizational dynamic capabilities, technological readiness, and ethical governance. We identify key implementation barriers—including financial capital limits, technical talent shortages, data quality deficits, and algorithmic transparency risks—and present an integrated conceptual roadmap to guide researchers, SME managers, and policy practitioners toward inclusive and durable AI adoption.
Keywords:
Artificial Intelligence, Small and Medium-Sized Enterprises, Sustainable Innovation, Digital Transformation, Triple Bottom Line, Dynamic Capabilities, Systematic Literature ReviewReferences
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