Exploring general practitioners’ perceptions of the utility of AI-powered voice-to-text technology for clinical documentation during video consultations in Danish general practice: a qualitative study

Background Clinical documentation is crucial for maintaining continuity and quality of care; however, it has become increasingly time-consuming and complex in general practice, leading to administrative overload and burnout. Artificial intelligence-powered voice-to-text technologies (AIVT) have emerged as potential solutions to reduce this burden by automatically transcribing and organizing consultations into clinical notes. This study assesses perceptions of the utility of an AIVT tool for clinical documentation during video consultations. Methods A qualitative study was conducted using triangulation of observations, think-aloud sessions, and semi-structured interviews. A total of 18 general practitioners from 14 clinics across all five Danish regions tested Autonotar, a use case for an AIVT tool that generates draft clinical notes during video consultations. Data were analyzed deductively using predefined criteria: demand, acceptability, and perceived future efficacy. Results The findings indicate: (1) structural drivers of demand show how increasing regulatory and defensive documentation pressures create a perceived need for technological support; (2) conditions for acceptable use highlight where general practitioners emphasize the importance of clinical accuracy, alignment with workflow, and robust data protection; and (3) perceived future value demonstrates how participants view AIVT as a way to reduce administrative workload, improve work-life balance, and enhance patient engagement—provided the tool delivers reliable output and is responsibly integrated into clinical systems. Conclusions Based on the study use case, AIVT may offer a practical means of supporting clinical documentation in Danish general practice, but its utility is conditional rather than inherent. GPs expressed cautious optimism about its potential to reduce documentation burden, improve work–life balance, and support patient engagement. However, adoption will depend on reliable output, workflow integration, clear accountability, robust data protection, and adaptation to different consultation modalities. Sustainable implementation requires technological maturity and sociotechnical alignment among clinicians, decision-makers, and technology providers.