For the record: a narrative review of ambient voice technology in clinical documentation for dentistry and wider healthcare

Abstract

Aims We synthesise current evidence on ambient voice technologies (AVT) and generative artificial intelligence (AI) in dentistry and wider healthcare.Methods Databases were searched across AI and AI-enabled clinical documentation, large language models and summarisation, and documentation outputs. Included studies evaluated AI-generation of clinical documentation with outcome measures including accuracy, documentation time, and the clinician/patient experience.Results Evidence within dentistry is limited, with only one current study evaluating AVT speech-to-text accuracy. Performance varied between systems, with reduced accuracy for dental terminology and clinically significant errors and hallucinations observed. No dental studies evaluated AI-generation of clinical records or letters. Studies across wider healthcare reported variable performance, including errors with the potential to cause harm. Implementation studies suggest reductions in documentation time and burden with AVT; however, the magnitude of effect was inconsistent, with uptake varying between clinicians and note-length increased. Patient attitudes were favourable although conditional on the accuracy and privacy of using these tools.Conclusions Ambient AI may reduce documentation time, but clinicians remain responsible for the final record produced by these systems. Ongoing research into safety and efficiency, alongside improved AI-literacy is required to ensure that the benefits of this technology are realised without compromising record accuracy or patient trust.

The authors' abstract, as published at the source. BDJ, 2026 · DOI ↗