This multicenter survey of 4,596 medical, dental, and veterinary students from 192 faculties in 48 countries reveals an optimistic outlook of medical students about the future role of AI in healthcare practice. However, this optimism is mixed with concerns, with a majority foreseeing increasing ethical and legal challenges as AI technologies become more integrated into medical practice and feeling inadequately prepared to use AI in their later careers. In terms of AI knowledge and education, our results demonstrate that most students report no or little AI knowledge and favor the inclusion of AI teaching in their curriculum, while over three-quarters did not have any events on AI as part of their studies. The subgroup analyses revealed regional differences in perceptions, although predominantly with small effect sizes.

To date, multiple studies have examined healthcare students’ attitudes towards AI in medicine [22]. Focusing on studies with large sample sizes of at least 500 medical or dental students, predominantly positive attitudes toward the application of AI in medicine were reported [24, 38–42]. For instance, a 2021 study by Bisdas et al., spanning 2,495 medical and 638 dental students in 63 countries, most of whom studying in Libya (N=790), Jordan (N=450), and the United Kingdom (N=331), found that 88.2% (N=2,766) of respondents either strongly or somewhat agree that AI will generally enhance medical practice, while about half (N=1,655, 52.8%) indicated that they would usually or always incorporate AI in their future practice [24]. Similarly, a 2022 survey of 2,981 medical students in Turkey by Civaner et al. demonstrated that 85.8% (N=2,558) of participants acknowledge AI’s role in facilitating physicians’ access to information, while 74.4% (N=2,218) of students affirm that widespread AI usage would make them better physicians and 70.5% (N=2,102) believe that AI application would lead to reduced errors [38]. Another large-scale survey conducted in 2020 among 1,103 dental students in Turkey by Yüzbaşıoğlu et al. demonstrated a significant agreement (N=945, 85.7%) on the prospective major advancements in dentistry and medicine through AI, which was similar to a 2022 study by Swed et al., comprising a cohort of 1,251 medical students and 243 physicians in Syria, with 1,317 respondents (87.4%) either strongly agreeing or agreeing on the crucial role of AI in the medical field [39, 40]. These findings are consistent with those of our study, in which most participants generally expressed positive attitudes toward the use of AI in medicine, the increase in efficiency of healthcare processes through AI, the positive impact of AI on the medical profession, and the availability of AI as a second opinion on medical issues.

Despite these positive attitudes, our study revealed a pronounced deficit in both self- reported AI knowledge and the integration of AI education into the medical curriculum, with about three-quarters of participants reporting little or no AI knowledge, no curricular events on AI, and the desire for AI teaching, respectively. However, the lack of AI knowledge and education among medical and dentistry students is not a novel phenomenon. Depending on the study and item design, self-reported AI knowledge in the literature ranges from 2.8% of 2,981 medical students in Turkey in 2022 who reported feeling informed about the use of AI in medicine to 51.8% of 900 medical students in Jordan in 2021 who indicated having read articles about AI or machine learning in the past two years [24, 38–42]. On the other hand, the reported prevalence of AI training in the medical curriculum ranges, for instance, from 9.2% in a 2020 survey of 484 medical students in the United Kingdom up to 24.4% in a 2022 study among 2,981 medical students in Turkey, although variations in item designs and demographic contexts hinder a comprehensive longitudinal analysis [25, 38, 40, 41, 43]. In our study, less than 18% (N=5) of countries with a sample size of 50 or more participants had a higher or equal proportion of students reporting any duration of AI teaching, pointing to a persistent deficit in medical AI education across various demographic landscapes.

Consequently, the incorporation of AI into medical education on a broader national or international scale is limited, and the adoption of frameworks, certification programs, interdisciplinary collaborations, modules, and formal lectures seems still to be at an early stage [18, 44–46].

In terms of educational preferences, most of the participants in our study indicated their interest in learning practical skills, followed by future perspectives and legal and ethical aspects of medical AI. On the other hand, the majority rather or completely agreed with the item that AI will increasingly lead to legal and ethical conflicts in the medical profession.

Similarly, a 2021 survey by Mehta et al. of 321 medical students at four medical schools in Canada found that 95% of medical students surveyed believe AI would introduce new ethical and social challenges, whereas Civaner et al. reported in 2022 that 93.8% of 2,981 medical students in Turkey consider AI training to address the ethical dilemmas raised by AI a necessary component of their education [38, 47]. This underscores the great potential of AI education to not only improve medical students’ oversight, knowledge, and practical skills in using AI but also to educate about ethical, legal, and societal implications — topics that are also addressed in other AI education frameworks, such as the United Nations Educational, Scientific and Cultural Organization K-12 AI curricula report [48].

In our subgroup analysis of respondents across continents, two items displayed moderate to large effect sizes. First, participants from South America were less likely to agree that the use of medical AI will increase ethical and legal conflicts compared to participants from Northern/Western Europe and Australia. Yet, students’ median responses in these regions were identical. Thus, the level of effect size primarily reflects outliers rather than a uniform regional disparity in opinion. Second, Asian students reported being better prepared to work with AI in their future careers. Although these differences in perceived preparedness could be driven by different national AI policies and educational strategies as well as macroeconomic factors, our study design and varying sample sizes across regions complicate a causal analysis [49, 50]. However, it is noteworthy that three of four countries in which more than 50% of medical students reported receiving AI training were located on the Asian continent, which may have contributed to Asian students indicating a higher preparedness towards applying AI in their future profession.

Finally, we observed a strong preference among medical students for AI systems that are explainable rather than highly accurate. This mirrors the growing emphasis on ’Explainable AI’ in the medical field and underscores the urgent need for developing AI algorithms that transparently disclose their decisions and limitations, especially when applied to the medical domain, to promote trust and acceptance among healthcare students, professionals, and patients [51–54].

This study has limitations. First, the uneven regional distribution of participants potentially biased results in favor of overrepresented regions. Additionally, the online design and language availability in either English or Spanish may have introduced selection bias, precluding students without internet access, as well as students who are not proficient in either language. Another potential source of selection bias could be that respondents with a specific interest in or experience with AI were more likely to participate in the survey.

Furthermore, the calculated response rate appeared to be rather low due to the lack of data on the number of students enrolled in each medical discipline for most participating institutions. Consequently, we derived the response rate using the total student enrollment numbers, which significantly underestimated the true rate of participation among medical students as it assumes that all students within each institute received an invitation to participate. Moreover, the presence of 20 institutions with fewer than 50 student respondents has skewed the response rate further downward.

In conclusion, our study —the currently largest survey of medical students’ perceptions towards AI in healthcare education and practice—reveals a broadly optimistic view of AI’s role in healthcare. It draws on insights from students with diverse geographical, sociodemographic, and cultural backgrounds, underlining the critical need for AI education in medical curricula around the world and identifying a universal challenge and opportunity: to adeptly prepare healthcare students for a future that integrates AI into healthcare practice.