Use and perceptions of AI tools among Australian general practice registrars: a national survey
Year: 2026
Type: article
Study design: Observational Study
Abstract: Introduction Artificial intelligence (AI) tools are increasingly used in health care, yet little is known about how often Australian general practitioner trainees (GP registrars) use them or how they perceive the impact of AI on training and clinical care. Aim This study aimed to examine how frequently registrars use AI tools for clinical care and education, types of AI used, the perceived benefits and risks, and training needs. Methods A national cross-sectional online survey conducted from 7 May to 4 June 2024 invited 3743 Australian General Practice Training or Fellowship Support Program registrars to participate. The survey assessed frequency and context of AI use, practice-level adoption, perceived impacts, training exposure, and ethical-legal concerns. Analyses were descriptive. Results Among the 727 respondents (19.5%), frequent use (weekly or more) was uncommon; 7.3% for clinical tasks, 5.0% for education. Practice-level adoption was low, with 10.8% reporting subscription to AI tools. Most registrars anticipated benefits, particularly learning efficiency and administrative workload reduction. However, 25.0% perceived increased medicolegal risk. Formal training was rare, with most relying on self-directed learning, though many rated AI education as important. Among clinical users, common tools included large language models (32.5%), remote patient monitoring devices (28.6%), and voice-to-text tools (26.2%). Large language models predominated in education (63.5%). Discussion In May–June 2024, AI tool use among registrars was limited, although most perceived potential benefit. Enthusiasm was tempered by concerns about safety, ethics, and legal risks. Structured training and guidelines are needed to support safe, effective integration into GP registrars’ practice and education.
Source: Journal of Primary Health Care
DOI: 10.1071/hc26166
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4416673592