The AI dilemma in Healthcare: Towards the multidimensional AI literacy framework

The rapid adoption of Artificial Intelligence (AI) in medicine has generated both enthusiasm and challenges among healthcare professionals and students. While AI promises transformative benefits in diagnostics, treatment, and healthcare management, its integration into clinical practice reveals a critical gap in adequate training and understanding. This chapter explores the digital dilemma in medicine: the tension between the opportunities AI offers and the need for structured education to ensure responsible adoption. Through an empirical study involving 105 Italian healthcare professionals and medical students, we investigate AI literacy, attitudes, and educational needs. Results highlight a multidimensional framework of AI literacy, encompassing technical, applied, critical, ethical, and collaborative competencies, as well as significant disparities in adoption based on seniority, specialization, and exposure to AI. Findings indicate that while professionals recognize AI’s potential, there is a pressing need for targeted training programs addressing technical proficiency, ethical considerations, and critical evaluation of AI systems. The proposed Multidimensional AI Literacy Framework (MALF) offers a theoretical foundation for developing tailored educational interventions to bridge the knowledge gap. By fostering inclusive and responsible AI adoption, this framework hopes to equip healthcare professionals with the skills required to harness AI’s potential while mitigating risks in contemporary medical practice.