The emergence of Generative AI (GenAI) presents both vast opportunities and profound challenges for medical education. To ensure its effective and ethically sound adoption, educators, institutions, and policy-makers must look beyond efficiency gains to foster deeper, resilient learning catalyzed by productive struggle: deliberate engagement with complex issues that promotes critical thinking. We conducted a conceptual analysis exploring two intertwined dimensions: using GenAI as a pedagogical tool ('AI in Education') and teaching foundational understanding of AI itself ('Education in AI'). We mapped GenAI's affordances-expressivity, interactivity, multimodality-to educational experiences such as interactive tutoring, OSCE feedback, and simulated patient interactions. We then critically examined implications for curriculum design and learner competencies. We found that GenAI's simultaneous increase in helpfulness and complexity forces convergence of the two educational dimensions. While GenAI supports enhanced learning (e.g. multi-turn tutoring), meaningful use demands critical awareness of its operational limits, ethical boundaries, and technical mechanisms. We argue that mere use of GenAI is insufficient; effective engagement must be informed, reflective, and critical. This entanglement necessitates reimagined curricula and competencies to prepare adaptive, ethically grounded clinicians. Embracing the tension between using and understanding GenAI supports development of robust clinical reasoning in an AI-augmented healthcare landscape.
Boman et al. (2025) studied this question.