Accepted for/Published in: JMIR Medical Informatics
Date Submitted: Mar 26, 2026
Date Accepted: Sep 30, 2026
Implementation Evaluation of an AI Scribing Tool in the Ambulatory Setting: A Qualitative Study
ABSTRACT
Background:
Artificial intelligence (AI) scribing tools to assist healthcare providers by generating clinical notes are rapidly spreading across healthcare settings. Implementation evaluations are needed to inform practice integration, guide future adoption, and enhance effective use of this novel technology.
Objective:
To explore contextual factors influencing implementation of an AI scribe for physicians in the ambulatory setting.
Methods:
This study was a single-site qualitative implementation evaluation guided by the Practical, Robust Implementation and Sustainability Model (PRISM) and the Sociotechnical Systems Framework. Semi-structured interviews were conducted with attending physicians working in the ambulatory setting. Data collection and analysis occurred iteratively until thematic saturation was achieved. Interviews were analyzed using thematic analysis with a constant comparative method, incorporating both deductive and inductive coding.
Results:
Twenty-five physicians were interviewed. Participants represented a broad range of specialties and AI scribe use. Five themes and 15 subthemes emerged: (1) Workflow integration influences adoption: flexibility is critical to fit; (2) Tool usability influences training engagement: ease of use limits proficiency; (3) Trust and mistrust: balancing confidence in AI with professional accountability; (4) AI in medicine: ubiquitous presence of AI scribing is inevitable; and (5) Divergent perceptions: the same mechanisms are viewed as both benefits and drawbacks.
Conclusions:
Implementation of AI scribes in ambulatory care is shaped by a complex set of sociotechnical and contextual factors. Attention to deploying these tools in ways that align with the needs of clinicians and patients is critical to optimizing implementation outcomes. Clinical Trial: N/A
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