Patient Attitudes Towards Ambient Artificial Intelligence in Clinical Consultations

BackgroundAmbient Artificial Intelligence (AI) technologies are increasingly being integrated into clinical practice to support documentation.These systems employ speech recognition, talk-to-text technology, generative intelligence and large language models (LLMs) to automatically transcribe and summarise clinician-patient consultations into structured clinical notes.While it may reduce documentation burden and enable patientfocused interactions, there remains limited evidence regarding patients' perspectives, experiences and the acceptability of ambient AI use in healthcare settings. ObjectiveOur study aims to explore patients' awareness, attitudes, consent preferences and perceived comfort factors regarding the use of ambient AI during consultations. MethodsA cross-sectional anonymous questionnaire survey was conducted among 55 adult patients attending an orthopaedic fracture clinic.The questionnaire included demographic items, Likert-scale questions (Q9-Q21; scored 1-5) assessing attitudes towards ambient AI use, closed-ended preference questions and open-ended free-text responses.Quantitative data were analysed using descriptive statistics, while qualitative free-text responses were analysed using thematic analysis to identify recurring themes and perspectives. FindingsGeneral awareness of AI in healthcare was high (72.7%),but detailed knowledge of ambient AI remained limited, with only 10.9% reporting a strong understanding.Participants showed moderate acceptance and trust in clinicians, while expressing concerns about transparency, privacy, consent, openness, accuracy and preservation of patient-clinician relationships during AI use. ConclusionsAs the adoption of AI in healthcare continues to expand, its implementation strategies should prioritise clinician-led explanation and transparency, active and ongoing consent processes, appropriate human oversight and strong data governance safeguards.Recognising variation in patient attitudes, preferences and concerns, accessible and meaningful opt-out mechanisms are essential to maintain patient autonomy, trust and acceptability.

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Publication Details

Journal
Cureus
Published
2026-09-05
DOI
https://doi.org/10.7759/cureus.115822
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Patient Attitudes Towards Ambient Artificial Intelligence in Clinical Consultations

Gavin Schaller, Sam Kathiramalai, Theodore Davis
Cureus
Artificial Intelligence in Healthcare and Education
article

Patient Attitudes Towards Ambient Artificial Intelligence in Clinical Consultations

Gavin Schaller, Sam Kathiramalai, Theodore Davis
article en

Abstract

BackgroundAmbient Artificial Intelligence (AI) technologies are increasingly being integrated into clinical practice to support documentation.These systems employ speech recognition, talk-to-text technology, generative intelligence and large language models (LLMs) to automatically transcribe and summarise clinician-patient consultations into structured clinical notes.While it may reduce documentation burden and enable patientfocused interactions, there remains limited evidence regarding patients' perspectives, experiences and the acceptability of ambient AI use in healthcare settings. ObjectiveOur study aims to explore patients' awareness, attitudes, consent preferences and perceived comfort factors regarding the use of ambient AI during consultations. MethodsA cross-sectional anonymous questionnaire survey was conducted among 55 adult patients attending an orthopaedic fracture clinic.The questionnaire included demographic items, Likert-scale questions (Q9-Q21; scored 1-5) assessing attitudes towards ambient AI use, closed-ended preference questions and open-ended free-text responses.Quantitative data were analysed using descriptive statistics, while qualitative free-text responses were analysed using thematic analysis to identify recurring themes and perspectives. FindingsGeneral awareness of AI in healthcare was high (72.7%),but detailed knowledge of ambient AI remained limited, with only 10.9% reporting a strong understanding.Participants showed moderate acceptance and trust in clinicians, while expressing concerns about transparency, privacy, consent, openness, accuracy and preservation of patient-clinician relationships during AI use. ConclusionsAs the adoption of AI in healthcare continues to expand, its implementation strategies should prioritise clinician-led explanation and transparency, active and ongoing consent processes, appropriate human oversight and strong data governance safeguards.Recognising variation in patient attitudes, preferences and concerns, accessible and meaningful opt-out mechanisms are essential to maintain patient autonomy, trust and acceptability.

Cureus
Brunel University of London (GB)
Openalex Percentile: Top 14%
Artificial Intelligence in Healthcare and Education
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