Authors
Matthew Bell
Published in
JAAPA : official journal of the American Academy of Physician Assistants. Volume 39. Issue 11. Pages 36-44. Nov 01, 2026. Epub Oct 27, 2026.
Abstract
Ambient artificial intelligence (AI) scribes, which record patient encounters and automatically draft clinical notes, are rapidly entering frontline practice. They rely on large language models to convert recorded conversations into structured documentation and are marketed as a way to reduce the documentation burden that contributes to clinician burnout. Early evidence from multicenter studies, randomized trials, systematic reviews, and international research suggests that ambient AI scribes may reduce documentation time and improve clinician well-being. However, most available studies are observational, reliant on small samples, and limited to short-term follow-up. At the same time, studies consistently raise concerns about new risks, including AI-generated "hallucinations" (fabricated content that appears confident), errors in draft notes (with omissions being the most common error type), documentation drift toward generic language, racial disparities in speech recognition accuracy, the use of unauthorized "shadow" AI tools with HIPAA and security implications, and unresolved questions about clinical safety outcomes. For physician associates (PAs), who are high-volume users of electronic health records and whose notes frequently serve as the primary communication channel with collaborating physicians, these risks carry particular weight. This review explains how ambient AI scribes work in accessible terms, synthesizes the current evidence base, and offers concrete strategies that PAs can use to ensure that these tools support safe, efficient, patient-centered practice.
PMID:
42934911
Bibliographic data and abstract were imported from PubMed on 27 Oct 2026.
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