AI is playing a significant role in present-day education, healthcare, research, and clinical decision-making (1). Generative artificial intelligence (AI) tools like ChatGPT have been getting a lot of buzz lately thanks to their capacity to produce human-like text, answer questions, explain complex topics, summarize information, and help with academic writing. These tools may be useful to assist students in learning and revising the large amount of complex medical science and clinical information that they are expected to know in medical education (2, 3).

ChatGPT is a language-based artificial intelligence system capable of engaging in conversations with users based on their input (4). It can be used by medical students for understanding complex topics, for preparing assignments, for making summaries, for creating multiple choice questions, for revision before examinations and for the discussion of clinical scenarios. ChatGPT offers direct explanations in plain terms, a feature that can aid student learning independently and effectively and speed up the understanding of concepts, unlike traditional search engines. That means it can be a helpful educational resource for students who require speedy academic help outside of class hours (5).

There are also opportunities for teachers and institutions with generative AI. It can help in creating teaching materials, case based questions, quizzes, feedback and enable student based learning. With its proper use, it can enhance access to learning materials and promote active learning. AI-powered learning in medical education can support students in refining their knowledge of basic sciences, grasp clinical reasoning, and build confidence in academic work. The benefits demonstrate that ChatGPT can help as a supplementary teaching aid to lectures, textbooks, clinical teaching, and teacher supervision (3).

However, there are potential risks to consider when using ChatGPT in medical education. Computer-generated answer can be missing, inaccurate, biased or incorrect. In medicine where wrong information can be detrimental, students can form a wrong understanding of clinical concepts. The plagiarism issue is also significant, since students might generate content with AI and plagiarize without grasping or crediting the source. Relying on AI can also result in a decline in critical thinking, independent reading, problem-solving, and original academic writing. Ethical practice and evidence-based reasoning are critical in medical education, where these concerns are paramount (6).

The issue of ethics is also relevant in the context of medical learning and research with Generative AI. Students can input patient information into AI tools without being aware of the risk of confidentiality and privacy breaches. References generated by AI can also be misleading or even incorrect, potentially impacting the quality of academic work. Thus, students must be guided on verifying information produced by AI, using sources appropriately, safeguarding patient information, and responsibly using AI. If not managed by appropriate institutional policies, using ChatGPT can lead to misunderstandings about acceptable and unacceptable use of the technology in academic settings (2).

While there is increasing attention for ChatGPT as a tool for students, there are relatively few local data on the use of ChatGPT by medical students and their views on the opportunities and risks of its use. Awareness, use, attitudes and concerns of students are critical to formulating appropriate educational guidelines. The medical colleges should be informed whether the students are using AI tools in a responsible manner or they should be given formal training to increase the awareness of AI.

Therefore, the present study was conducted to assess the awareness, academic use, perceived opportunities, and risks of ChatGPT and generative artificial intelligence in medical education among medical students. The study also aimed to identify students’ attitudes toward integration of AI in the medical curriculum and the need for institutional guidance regarding responsible AI use.A

This study was designed as a descriptive cross-sectional study to assess the use, perceived opportunities, and potential risks of ChatGPT and generative artificial intelligence in medical education. The study focused on exploring students’ awareness, academic use, perceived benefits, ethical concerns, and attitudes toward the integration of generative AI tools in medical learning. A cross-sectional design was selected because it was suitable for collecting data from participants at a single point in time and for identifying patterns of knowledge, perception, and practice regarding ChatGPT use among medical students.

This descriptive cross-sectional study was conducted among 92 medical students at HBS Medical and Dental College from February 2025 to august 2025. Under-graduate medical students enrolled in MBBS or related medical education during the period of this study were considered as the target population. Both pre-clinical and clinical students were included to compare differences in exposure, academic needs, and use of AI tools at various phases of medical training.

There were 92 medical students involved in the study. The number of eligible participants available within the study period was used to determine the number of samples. All students who met inclusion criteria and agreed to participation were included until the desired sample size was achieved, and a non-probability consecutive sampling technique was employed. The sampling method was adopted because it was practical to recruit students from the school population during the short period of the study.

The inclusion criteria were undergraduate medical students who were available during the period of data collection, willing to participate, and able to understand and fill the questionnaire. Those who did not produce consent, incomplete forms and students who were not present when data was collected were excluded from the study. Participants were told that the participation was voluntary and that the information they provide would only be used for academic and research purposes.

The structured questionnaire designed based on literature search on the topics of artificial intelligence, ChatGPT, digital learning and medical education was used to collect the data. The questionnaire consisted of various parts addressing demographics, awareness of ChatGPT and generative AI, usage frequency, usage purpose, perceived educational opportunities, perceived risks, ethical concerns, and attitude toward using AI in the medical curriculum. Demographic data comprised prior experience with AI tools, gender, year of study, and age. Awareness-related questions were designed to determine if students had heard of ChatGPT, their self-reported understanding of AI, and the primary source of information.

The academic use section involved determining if participants used ChatGPT for academic tasks like learning new medical concepts, doing homework, revision for exams, creating summaries, producing MCQs, discussing cases, and aiding research writing. Uses was rated as daily, weekly, occasionally, rarely, or never. The concept of perceived opportunities was measured by questions concerning time saving, concept clarification, self-directed learning, exam preparation, self-confidence and academic tasks.

The risk and ethical issues area contained questions about incorrect information, plagiarism, overreliance on AI, diminished critical thinking, inadequate referencing, surface learning, patient confidentiality and assignment or research misuse. Students' attitudes toward ChatGPT were examined through questions related to potential for enhancing medical learning, the necessity of AI in medical training, the need for formal training, and the need for policies to guide its use. Perception and attitude items were answered using a Likert scale, and then coded into agree/strongly agree, neutral, and disagree/strongly disagree for analysis.

The purpose of the study was explained to all participants before data were collected. An informed consent, either written or verbal, was obtained from each participant. Participants were assured their identity would not be disclosed and that no personal identifying information will be disclosed. They were also told that they could drop out of the study at any time without it affecting their studies in any way.

The data that were collected were entered and analyzed in SPSS version 26. The Quantitative variables (age) were reported as Mean and Standard Deviation. Qualitative variables like gender, year of study, awareness, frequency, perceived opportunities, perceived risks and attitudes were displayed as frequency and percentages. The results were organized in a clear and systematic way using tables. A bar graph was created to illustrate the top opportunities and threats identified by ChatGPT and generative AI in medical education. The chi-square test was used for inferential analysis to determine the association of selected variables and positive attitude toward the use of ChatGPT.

Gender, year of study, previous use of AI, and self-rated knowledge of AI were compared to the attitude toward generative AI. A p-value of ≤0.05 was considered statistically significant. The results were presented in the context of the study's goals, highlighting the educational value as well as the ethical issues of generative AI usage in medical education.

There were 92 subjects in the study. The majority of students were in the age group of 21–23 years, with a mean age of 22.4 ± 1.8 years. There were slightly more female than male participants. The majority of respondents were from clinical years of medical education, potentially accounting for this, and thus might have had higher exposure to digital learning tools and academic use of ChatGPT.

Table 1: Demographic Characteristics of Participants

The participants had a high level of awareness about ChatGPT and generative AI. Prior to the study, most students were familiar with ChatGPT and over two thirds of them had used AI-based tools. But a lesser share assessed their knowledge of AI as good, indicating that awareness was greater than skilful understanding.

Table 2: Awareness and Knowledge of ChatGPT and Generative AI

Medical students were more likely to be using ChatGPT for academic purposes.Medical students were more likely to use ChatGPT for academic purposes. The most common applications were to clarify concepts, prepare for assignments, prepare for examinations, and create learning resources like summaries and MCQs. This indicates that students primarily employed ChatGPT as an aid tool to assist them in learning rather than a replacement for formal instruction.

Table 3: Academic Use of ChatGPT Among Participants

When asked about how often they use ChatGPT, almost half of respondents said they used it occasionally, and a smaller portion said it was used every day. This points towards the use of generative AI by students, however, without daily use.

Table 4: Frequency of ChatGPT Use

Students shared a number of learning experiences about ChatGPT and generative AI. The greatest consensus was around the ability to explain difficult concepts quickly, save time, facilitate self-directed learning and aid exam preparation. The results indicate that students found ChatGPT an academic aid when used responsibly.

Table 5: Perceived Opportunities of ChatGPT and Generative AI

At the same time, there were key risks that were identified. The most frequent complaints were inaccurate information, plagiarism, overdependence and decrease in critical thinking. Many students also worried about infringement on patient privacy and ethical abuse particularly with regard to clinical and research activities.

Table 6: Perceived Risks and Ethical Concerns

The overall sentiment towards ChatGPT was primarily positive, with a strong need for guidance and regulation highlighted by many participants. A majority of students were in favor of incorporating AI education into the medical curriculum, indicating a desire for systematic learning about the safe and responsible use of generative AI in healthcare.

Table 7: Attitude Toward Integration of Generative AI in Medical Education

Association analysis was done to identify factors associated with the use of ChatGPT and attitude towards generative AI. A strong association was found between previous use of AI tools and positive attitude towards ChatGPT as well as year of study. The students who had used AI tools were more likely to say that they were positive about the use, and the clinical years students were more likely. There was no significant association between gender and ChatGPT use.

Table 8: Association of Selected Variables with Positive Attitude Toward ChatGPT

The findings demonstrated that medical students' awareness of generative AI and ChatGPT was high, as was their awareness of generative AI in general, with 91.3% having heard about ChatGPT and 72.8% having used AI tools previously. The common use cases for ChatGPT were: understanding complex concepts, preparing assignments, revision for exams, and creating summaries. Time saving and better understanding of concepts and evaluation of self-directed learning were the perceived opportunities that were major. Important risks, however, were also identified by students as inaccurate information, plagiarism and over-dependence, diminished critical thinking and ethical issues. The majority of the participants were supportive of the integration of formal AI training into the medical curriculum, with positive attitude being significantly associated with the clinical year of study, as well as previous AI usage and higher self-rated knowledge of AI.

The present study showed that medical students had a high level of awareness regarding ChatGPT and generative artificial intelligence, as 91.3% had heard about ChatGPT and 72.8% had previously used AI-based tools. This finding indicates that generative AI has rapidly entered the academic environment of medical students and is no longer limited to computer science or technology-related fields.

Similar observations were reported by Chan and Zary, who stated that AI has increasing applications in medical education, particularly in learning support and individualized feedback (7). Masters also emphasized that medical educators need to understand AI because it is gradually influencing teaching, learning, assessment, and clinical practice (8). In the present study, students mostly used ChatGPT for concept clarification, assignment preparation, examination revision, and generating summaries, which is consistent with the view of Khan et al., who described ChatGPT as a tool that can reshape medical learning by providing quick explanations, academic support, and interactive responses (9).

The most significant opportunities mentioned in the present research were saving the academic time, helping the students to understand some difficult medical concepts, facilitating self-directed learning, and helping with exam preparation. This is backed by previous studies that have emphasized the benefits of AI in personalized learning, quick access to information, and enhanced educational engagement. Topol said AI is a technology that can complement high performance medicine with human knowledge and machine aid (10). In a scoping review of AI in undergraduate medical education, Lee et al. also noted that AI can aid in the delivery of medical education curriculum, medical students' assessment, feedback, and skill development (11). Likewise, Gilson et al. and Kung et al. showed that ChatGPT can answer a significant number of USMLE-style questions and give understandable explanations, implying the potential of using ChatGPT as an auxiliary learning tool for medical students (12, 13). The results align with the current study, which found that students found ChatGPT to be useful in exam preparation and grasping academic material.

While the following benefits were found by students, the present study also identified some concerns: inaccurate information, plagiarism, weak referencing, overdependence, and decreased critical thinking. Such concerns are of clinical significance because accuracy, evidence-based reasoning and academic ethics are all essential elements of medical education. Jeyaraman et al. indicated that ChatGPT could likely be beneficial in medical education and research but suggested that there are concerns about misinformation, incorrect referrals, and inappropriate academic use (14). Arif et al also caution that ChatGPT can be a “blessing or a blight” based on its usage in medical education and research (15). Of the participants, 76.1% reported concerns about inaccurate information since AI-generated content that has not been verified could impact students' clinical knowledge and may lead to superficial learning without the proper oversight of educators.

The results of the present study also indicated an overall positive attitude toward the integration of formal AI training and institutional policies into medical education. These findings align with those of Civaner et al., who found that medical students viewed AI as an assistive technology and wanted a revision of medical curricula to equip future doctors with the skills needed to work with AI in healthcare (6). Similarly, Pucchio et al. identified that Canadian medical students identified the importance of AI education in the medical undergraduate curriculum and would prefer to have structured opportunities for learning (16). Weidener and Fischer also pointed out that there is a need to incorporate AI ethics into medical education, especially due to issues with patient autonomy, transparency, bias, privacy and accountability (17). The results of these studies back up the present one, in which students at medical schools are not just interested in having access to these tools, but also in how they can be used safely, ethically and effectively.

In the current study, the association analysis results indicated that higher clinical year, previous experience using AI and self-rated knowledge of AI were significantly correlated with the positive attitude toward ChatGPT. This indicates that experiencing and familiarity can lead to greater acceptance of AI learning tools. The same has been seen by Alkhaldi et al., where they discovered that students who had prior experience with AI had more positive perceptions of it compared to those who did not (18). Moldt et al. also reported that medical students were interested in the use of AI chatbots, but demonstrated gaps in their knowledge and also concerns that they would like to see addressed through formal education (19). There were some limitations in the present study. It was carried out with a relatively small sample size of 92 students and was a cross sectional design which means causal relationships cannot be established. The answers were self-reported, and could be emotionally affected by social desirability or differences in students' personal experiences using ChatGPT. Further multicenter research with larger numbers of subjects is needed to evaluate not only perceptions but also the impact of ChatGPT usage on academic achievement, clinical thinking, critical thinking and ethical reasoning.

The study concluded that medical students showed high awareness and frequent academic use of ChatGPT and generative AI. Students perceived ChatGPT as useful for saving time, understanding difficult concepts, preparing assignments, examination revision, and supporting self-directed learning. However, they also recognized important risks, including inaccurate information, plagiarism, overdependence, reduced critical thinking, weak referencing, and ethical concerns. Most participants supported formal AI training and institutional policies for responsible AI use in medical education. ChatGPT should therefore be used as a supportive educational tool, not as a replacement for teachers, textbooks, clinical reasoning, or evidence-based learning. Medical institutions should develop clear guidelines and structured AI literacy programs to help students use generative AI safely, ethically, and effectively.

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