A Systematic Literature Review of AI, Education, and Change in Radiology Practice

Radiology is undergoing a role change as Artificial Intelligence (AI) becomes increasingly embedded in clinical workflows, reshaping the roles, responsibilities, and educational needs of radiologists.As professionals known for their autonomy and expertise, radiologists face significant transitions that require effective change management and educational support.The systematic literature review is guided by the PRISMA methodology and synthesizes findings from peer-reviewed research between 2019 and 2024 to explore how AI integration influences radiology practice and training.Anchored in the GrandFusion Framework-a novel theoretical synthesis of Dewey's Experiential Learning, Simon's Bounded Rationality, Lewin's Change Management, Davis's Technology Acceptance Model, and Rogers's Diffusion of Innovations-this review categorizes AI applications, change management strategies, and educational interventions that support radiologists during this period of technological change.The study identifies six key thematic areas and highlights the growing impact of AI in radiology.It emphasizes the need for targeted change management and education to bridge the gap between technology and practice.By identifying trends and research gaps, this study offers valuable insights for practitioners and Information Systems (IS) researchers, concluding with recommendations for future research.