Artificial Intelligence, Cognitive Abundance, and the Multi-Layered Competence of Health Professionals

Artificial intelligence (AI) is transforming how health care professionals develop, maintain, and express competence across the span of their careers. Traditional continuing professional development has been shaped by a paradigm of what has been called cognitive scarcity (or informational resource scarcity) where clinicians had limited opportunity to find, read, synthesize, and interpret evidence, and learning systems evolved to deliver knowledge in periodic, curated updates. Emerging AI systems-large language models, multimodal analytic tools, predictive algorithms, and reflective agents-disrupt this scarcity by creating cognitive abundance (or informational resource abundance). These systems generate real-time evidence syntheses, contextual insights, adaptive learning trajectories, and continuous performance feedback. Using ten Cate et al.'s (2024, Medical competence as a multilayered construct. Med Educ, 58, 93) multilayered model of competence-canonical, contextual, and personalized-this paper analyzes how AI can both enhance existing educational processes and fundamentally reshape the developmental landscape. AI shifts clinicians from being knowledge stewards to orchestrators of distributed cognition, from experiential learners to data-informed practitioners, and from using opportunistic continuous personal development to continuous reshaping of professional identity. Continuing professional development must evolve to cultivate AI literacy, hybrid reasoning, interprofessional coherence, and ethical stewardship in work environments where cognition is abundant. The contents of long-term memory of clinicians will shift from a predominance of biomedical facts needed to steer daily clinical work, to new procedural inquiry skills needed to find, select, and evaluate the validity of information for clinical decision making.