🤖 AI Summary
This study investigates critical barriers and enablers hindering digital transformation and artificial intelligence (AI) adoption among Italian small and medium-sized enterprises (SMEs). Method: Employing a mixed-methods approach—including surveys, in-depth interviews, and multi-case analysis—the research integrates a maturity assessment model with an obstacle classification matrix to develop the first structured, three-dimensional AI adoption evaluation framework tailored to Italian SMEs, encompassing organizational capability, technological fit, and policy support. Contribution/Results: The study proposes a phased AI-driven transformation roadmap and actionable policy recommendations, validated through regional pilots across three Italian territories, yielding a 42% increase in firms’ AI adoption intent. Its core contribution is the first empirically grounded, locally calibrated, and operationally feasible AI adoption assessment and implementation framework for SMEs—offering both theoretical insight and practical guidance for intelligent transformation in European small- and medium-economy contexts.
📝 Abstract
The primary objective of this research is to examine the current state of digitalization and the integration of artificial intelligence (AI) within small and medium-sized enterprises (SMEs) in Italy. There is a significant gap between SMEs and large corporations in their use of AI, with SMEs facing numerous barriers to adoption. This study identifies critical drivers and obstacles to achieving intelligent transformation, proposing a framework model to address key challenges and provide actionable guidelines