AI Scribe Use in Residency Training: A Call for Specialty Society Guidance in Graduate Medical Education
Year: 2026
Type: article
Abstract: Artificial intelligence (AI) is increasingly used for documentation purposes in clinical practice, yet guidance for resident use is limited. Given the substantial documentation burden on medical trainees, AI-powered scribing tools may offer benefits, but their integration into residency training raises educational, supervisory, and patient safety considerations. This study aimed to assess the availability of resident-specific guidance on AI scribe use from major medical and specialty organizations and to summarize current evidence on AI scribes in residency. We reviewed five major medical and specialty society websites (AAD, AMA, ACGME, AAMC, ABMS) via website searches and direct emails and conducted a PubMed search for residency-focused studies. No organization provided resident-specific guidelines; the AMA noted the need for safe, accurate, and non-discriminatory AI use, and the AAMC issued general principles for the use of AI in medical education, none of which specifically address resident documentation. Literature review identified two studies evaluating AI-assisted documentation in the residency context. The studies suggest reduced documentation burden and cognitive load, with documentation quality comparable to resident physicians. These findings highlight the need for residency-specific AI scribe consensus guidelines that address resident review, note sign-off, accountability, patient consent, and scope of use to ensure safe and effective integration into training.
DOI: 10.2147/amep.s578656
Authors: Julia Giordano, Elizabeth Jones
Institution: University of Pennsylvania
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,320
OpenAlex ID: W7128549581