A Pilot Study of Junior Medical Officers in Sydney, Australia: Knowledge and Attitudes Towards Artificial Intelligence.

Introduction Artificial intelligence (AI) use is growing generally and specifically in healthcare. It has multiple applications across medicine, including summarising patient consultations, interpreting investigations and improving patient flow. Junior Medical Officers (JMOs) working in Northern Sydney Local Health District (NSLHD), in New South Wales (NSW), are amongst the first generations of clinicians to experience the broadest expansion of the use of AI and are likely to determine the guidelines for its use. However, they remain an underrepresented group in the literature. Aim This study assesses and evaluates the knowledge and attitudes of JMOs towards AI, thoughts on applications of AI and willingness to incorporate it into future practice. Methods An online survey was sent to JMOs in two hospitals in the Northern Sydney Local Health District in Sydney, Australia. Responses were analysed qualitatively and quantitatively. Results Of the JMOs surveyed, 37.5% rated their knowledge of AI generally as good or very good, 33.3% rated it as average and 29.2% rated it as poor. Knowledge of AI in healthcare was self-reported as good by 23.3%, average by 33.3%, poor by 36.7% and very poor by 6.7% of respondents. When responding to questions about frequency of use of AI in clinical work, 10% of JMOs responded that they use AI daily, 30% weekly, 3% fortnightly and 23% monthly, with 34% never using AI. JMOs expressed broadly positive attitudes towards AI, with 10.3% viewing it very positively, 55.3% positively, 10.3% negatively and 3.4% very negatively, with 20.7% holding neutral views. JMOs felt the main advantages of AI were "freeing time from documentation", "processing large amounts of data" and "searching through data for best practice". The main concern identified was the output of incorrect information by AI. Respondents felt the future roles for AI were scribing and summarising notes, real-time translation, medical education and interpreting medical imaging. Amongst those surveyed, 76% were open to using AI in the future, and 83% said they would be more likely to use AI if the programme was endorsed by the local health district. JMO responses indicated that they felt that AI should be included in medical education curricula, with 84% responding in the affirmative. Conclusion This study found that JMOs in Northern Sydney Local Health District have varying levels of understanding of AI but broadly view the technology positively. Although current use of AI is relatively limited, participants identified significant potential for AI to reduce administrative workload, particularly through clinical documentation tasks such as scribing and summarising patient notes. Many respondents indicated they would be more likely to use AI in both clinical and non-clinical settings if it were formally endorsed by the local health district. Participants also expressed a strong interest in further AI education and supported its inclusion in medical training. Human oversight was consistently regarded as essential. The current lack of clarity remains a key barrier to implementation. As AI technologies continue to evolve, healthcare organisations, policymakers, and clinicians, namely, JMOs, share responsibility for ensuring their safe, ethical, and effective integration into practice.