Developing AI literacy in healthcare education: bridging the gap in competency assessment

Abstract

The rapid integration of artificial intelligence (AI) into healthcare is reshaping clinical practice and redefining the competencies required of healthcare professionals. Despite growing recognition of AI literacy as an educational priority, current efforts to assess this competency remain fragmented, lacking theoretical coherence and methodological rigour. Existing tools often rely on generic measures that fail to fully reflect the complexity and contextual specificity of AI use in healthcare settings. In this Perspective, we argue that the current absence of validated, healthcare-specific assessment frameworks represents a significant barrier to designing relevant curricula and ensuring workforce preparedness for AI-enabled care. Drawing on principles of educational assessment and professional competence, we call for the development of robust, psychometrically sound instruments that render AI literacy both teachable and measurable. We conclude by identifying key priorities for future research, including framework development, stakeholder engagement, and cross-context validation, to support the integration of meaningful AI literacy assessment into healthcare education.

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