TOE-Framework in AI adoption: a qualitative analysis of Sicilian SMEs

This research examines the enablers and barriers to artificial intelligence (AI) adoption among small and medium-sized enterprises (SMEs) in Sicily, foregrounding how technolo-gical, organizational, and environmental factors interact in a peripheral regional context. Adop-ting a qualitative design, we conducted eight semi-structured, in-depth interviews with mana-gers from digitally oriented and traditional SMEs. Data were analysed abductively through the Technology-Organization-Environment (TOE)framework. Findings reveal a pronounced divide: digital SMEs treat AI as a strategic asset already embedded in daily workflows (e.g., code analysis, marketing, administrative support), reporting productivity gains and a shift toward higher value-added tasks; while traditional SMEs view AI as distant or overly complex, citing low awareness and unclear use cases. Organizational culture and leadership are pivotal–entrepreneurial, experimentation-friendly settings (often with dedicated "creative techno-logist"roles) accelerate adoption, whereas resistance among incumbent staff and weak change communication hinder progress. Envi-ronmental constraints specific to Sicily-frag-mented incentives, uneven digital infrastructure, and limited knowledge networks-further dampen uptake, creating a risk of widening digital divides. The research offers actionable implica-tions: staged, use-case-driven pilots with clear governance; leadership development and inter-nal champions; continuous, modular training; and ecosystem interventions (innovation hubs, cluster initiatives, targeted vouchers/grants). Theoretically, we advance a socio-technical view of AI consolidation that links micro-organi-zational dynamics with territorially embedded conditions. Overall, the research contributes context-sensitive evidence andpractical guidance to foster inclusive AI-enabled trans-formation in SMEs.