Reconciling how clinical reasoning is learned in the age of artificial intelligence

Artificial intelligence (AI) is becoming increasingly ubiquitous, both in daily life and in healthcare settings. Narrow AI health technologies are gradually being introduced into clinical practice across multiple specialties 1 , 2 . Since ChatGPT was publicly released in November 2022, large language models (LLMs) have also captured the collective imagination, resulting in ambient scribes, specialized clinician-facing platforms that ground LLM-generated responses in the peer-reviewed literature (e.g. OpenEvidence), and a growing ecosystem of innovative applications. Ease of access also means that some of these tools are increasingly being used as personalized “pocket tutors” without supervision or institutional scaffolding 3 , 4 .