Generative artificial intelligence (AI) is defined as a class of AI models that generate synthetic outputs based on learning acquired from the datasets used to train the model [1]. Among these, ChatGPT, one of the most well-known models, has gained explosive popularity, reaching 100 million users within just two months of its release in 2022 [2]. In recent years, generative AI has brought transformative changes to a wide range of fields, including scientific research, creative arts, customer service, personalized learning, and healthcare. However, research on the actual use of generative AI in medical education in Japan has been limited.

Recently, medical students are increasingly believed to use AI for various academic tasks, such as attending lectures and writing reports. Conversely, faculty members are thought to use generative AI for preparing teaching materials and drafting documents. Despite its benefits, the use of AI in medical education presents several challenges. First, AI systems are not always accurate and may provide outdated or incorrect information, which can mislead students and hinder their learning [3]. Additionally, excessive reliance on AI tools may impair the development of critical thinking and problem-solving skills by encouraging dependency on automated answers [3]. Ethical concerns also arise, particularly regarding privacy and data security, as AI systems often require access to sensitive personal information [4]. Moreover, AI algorithms can reflect biases in their training data, potentially reinforcing unfairness or misinformation in educational content. Finally, overuse of AI may reduce meaningful human interaction between students and instructors, which is vital for nurturing communication skills and professional judgment [5].

Given this social context, the present study aimed to investigate the current use of AI among medical students and faculty members, as well as to identify potential concerns or challenges, in order to help determine the future direction of medical education.

Between April and May 2025, a cross-sectional survey was conducted among medical students and faculty members at the Oita University Faculty of Medicine. The questionnaire comprised 9 items each for students and faculty. It was created using Google Forms and administered online. This survey was distributed via email, participation was voluntary, and responses were collected anonymously. No incentives were provided for completing the questionnaire. The questionnaire was developed based on a literature review and under the supervision of experts in medical education and AI (TT and YM), and is provided as a Supplementary file. To ensure content validity, all items were reviewed for clarity and relevance. Although a formal pilot test was not conducted, the questionnaire was refined through internal discussion among the authors and reviewed by domain experts to ensure clarity and relevance.

The student questionnaire included items on prior experience using AI, specific applications used, purposes for which AI was employed, perceptions of AI use in university classes and assignments, experience attending classes incorporating AI, and opinions on the appropriateness of such AI-integrated classes.

This cross-sectional study investigated the current status of AI utilization and awareness among medical students and faculty members at a single Japanese university. Sami et al. conducted a survey of 702 medical students in Pakistan and found that the majority perceived AI as an effective and credible learning tool, highlighting its potential to optimize study time, improve conceptual understanding, and provide accurate medical information [6]. Also, Abdelhafiz et al. reported that Egyptian medical students showed strong interest and trust in using ChatGPT and similar chatbots for academic purposes [7]. Reports from individual countries worldwide reported to date are summarized in Table 1 [6–14]. Many surveys reported favorable attitudes toward the use of AI in medical education. To the best of our knowledge, our study is the first report from Japan. Moreover, there have been no reports that clarify the use of AI or attitudes toward it among not only medical students but also faculty members at medical schools. Consistent with prior findings, Japanese medical students have already been utilizing AI in their studies and expressed a desire to continue using it in the future. On the other hand, a study involving 4,313 medical students from 48 countries also reported similarly positive attitudes toward the use of AI in healthcare and medicine, and found no significant regional differences among the countries [15].

The findings revealed that a high proportion of both students (82.1%) and faculty members (73.4%) had prior experience using AI, particularly generative AI tools. These results suggest that AI technologies have already become familiar tools in academic settings and that their integration into medical education is progressing rapidly. On the other hand, the faculty group showed a slightly lower usage rate than students, possibly reflecting generational differences in digital literacy or concerns over accuracy, ethics, and educational validity. Moreover, younger faculty members with experience using AI tended to approve of the introduction of AI into medical education. It is anticipated that as the number of young faculty members with AI experience increases, the implementation of AI in medical education will be further promoted.

As mentioned above, there were many positive opinions regarding the use of AI in medical education. However, there are also several risks associated with integrating AI into medical education. The first issue is ethical considerations and the risk of leakage of personal information [3]. Medical education, in particular, frequently involves handling real patient information, making it essential to carefully consider the risk of personal data leakage through the careless use of AI. In our survey of faculty members, concerns about personal information leakage and ethical risks were the most frequently cited, with 257 respondents (73.4%) expressing such concerns. In their scoping review, Gordon et al. also emphasized the need to establish ethical guidelines in this area [4]. Moving forward, it is crucial to develop clear ethical standards for the use of AI in medical education. On the other hand, concerns have been raised about skill deterioration due to overreliance on AI and the widening digital divide among educational institutions [3]. It is essential to explore effective ways to utilize AI to ensure the delivery of high-quality medical education.

This study has several limitations. First, it was conducted at a single institution, which may limit the generalizability of the findings. In addition, statistical analyses were not conducted for various items. Second, the survey relied on self-reported data, which may be subject to bias or inaccuracies. Also, the response rate among medical students was low, at 40%. Lastly, the rapidly evolving nature of AI technology means that perceptions and usage patterns may change over a short period. Multicenter or longitudinal studies are warranted to better understand the trends and impacts of AI in medical education across diverse settings.

In conclusion, the use of AI in medical education is advancing, and both students and faculty members generally support its implementation under certain conditions. However, unresolved issues, particularly in the realm of ethics, must be addressed to ensure its responsible and effective implementation.