Bridging the Gap: Barriers and Adoption Patterns of AI in Radiological Practice

Artificial Intelligence (AI) is increasingly integrated into radiological practice, yet real-world adoption remains unstable. This mixed-methods study examined AI use within the Israeli radiological workforce through 32 interviews and a survey of 133 professionals. AI was largely perceived as a supportive "second reader," while concerns focused on reliability, workflow integration, and medico-legal responsibility. Adoption patterns were heterogeneous, with higher reported use among specialists and hospital-based staff. Attitudes reflected conditional acceptance, emphasizing physician responsibility, institutional policies, and human verification. Leading barriers included limited institutional budget, doubts in AI outputs and absence of medico-legal protocols. Findings suggest that trust, governance, and institutional support are central to sustainable AI implantation.