AIHealthcare Analytics

Regulatory Foundation

The EU AI Act obliges providers, deployers, and users to ensure an appropriate level of AI literacy. Healthcare professionals must understand the functioning, limitations, and risks of AI systems and use them critically. Responsibilities are distributed: providers ensure transparency and validation; deployers establish governance and training; healthcare professionals apply contextual interpretation.

Core Competency Areas

AI literacy in healthcare encompasses understanding of predictive models and generative AI, including pitfalls such as bias, confounding, hallucinations, and automation bias. Training must address both basic knowledge and practical application, from initial training to specialist practice. Early and structural investment in AI literacy is identified as essential for safeguarding human oversight and patient safety.

Current State of Training

A US cross-sectional study of a public Minority Serving Institution found 83.2% of respondents had used GenAI, but only 7.9% had received formal training. Faculty were more likely to have conducted substantial independent research on GenAI (48.5%) versus students (24.3%). Most relied on free tools (90.6%) and internet-sourced information (77.3%). Concerns were substantial (70.3%) and challenges in GenAI use were widespread (84.7%).

Emotional Readiness

Emotional readiness — not merely technical competency — is identified as the central determinant of GenAI adoption among health professions educators. Fear of obsolescence, uncertainty about ethical use, and threats to professional identity undermine engagement. A six-week online course integrating emotionally responsive pedagogy with a structured FAIR framework (Familiarization, Application, Interpretation, Recalibration) demonstrated a shift from anxiety to confidence and from resistance to leadership among healthcare educator participants.