Addressing Organizational Barriers in AI Implementation: Evidence from Italian Companies

This study examines how Italian organizations navigate socio-technical barriers to AI implementation through the lens of Socio-Technical Systems Theory. Based on a two-phase survey of 109 Executive MBA graduates, we identify critical implementation barriers and evaluate effective governance structures and integration strategies. Our findings reveal that Italian firms predominantly adopt incremental approaches to AI implementation, with skills gaps, centralized decision-making, and data quality issues emerging as primary challenges. Successful implementation requires comprehensive capability development integrating technical and business expertise, evolution from centralized to inclusive governance structures, incremental deployment strategies enabling iterative learning, and robust data management frameworks. This research advances understanding of the interplay between technical systems and organizational dynamics in AI adoption, offering practical guidance for organizations navigating digital transformation challenges in the distinctive Italian business landscape characterized by family-owned enterprises and traditionally craft-oriented sectors.