Patient Attitudes Towards Ambient Artificial Intelligence in Clinical Consultations

Background Ambient 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 patient-focused interactions, there remains limited evidence regarding patients' perspectives, experiences and the acceptability of ambient AI use in healthcare settings. Objective Our study aims to explore patients' awareness, attitudes, consent preferences and perceived comfort factors regarding the use of ambient AI during consultations. Methods A 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. Findings General 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. Conclusions As 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.