Keywords: Artificial intelligence; General practice; Attitudes; Medical students; Digital health

Background:

Integrating artificial intelligence (AI) into healthcare poses new challenges for primary care, where human interaction is central. While AI’s potential in diagnostics and administrative support is acknowledged, little is known about the readiness of future general practitioners to use these technologies. This study offers novel insights into Hungarian medical students’ attitudes and preparedness regarding AI in general practice.

Research questions:

Our study aims to examine Hungarian medical students’ understanding of artificial intelligence and their willingness to implement it in selected tasks routinely performed by general practitioners.

Method:

A cross-sectional questionnaire-based study was carried out among fifth-year medical students at a Hungarian medical university (N = 183). Using a 5-point Likert scale, participants assessed their perceived level of knowledge regarding artificial intelligence, its anticipated role, and their preferences for AI applications in administrative, diagnostic, and human-centered domains. Statistical analysis included descriptive measures and correlation testing to explore associations between knowledge levels and willingness to adopt AI. This ongoing research will be broadened to include practicing specialists to facilitate comparative analyses.

Results:

The mean age of the respondents was 24 years. Participants reported a high level of self-perceived knowledge of artificial intelligence (mean = 4.6) and low levels of job-related insecurity (mean = 2.51). A distinct preference pattern was observed, with strong support for AI use in patient documentation and imaging diagnostics, and clear resistance to its application in empathetic or psychiatric care. Higher perceived AI knowledge was significantly correlated with greater willingness to use AI (p < 0.001). These results constitute preliminary findings of an ongoing investigation.

Conclusions:

Hungarian medical students view AI primarily as a supportive digital assistant, rather than a competitor. Our findings from a sizable sample (N=183) highlight implications for medical education and primary care, with ongoing expansion to practicing specialists facilitating comparative analyses.

Points for discussion:

How might AI adoption in primary care reshape workload distribution, patient flow, and resource utilization within healthcare systems?

How should the responsibilities between physicians and AI systems be outlined in general practice to ensure safety and accountability?

What ethical and regulatory safeguards are needed in primary care to address privacy, bias, and accountability when deploying AI tools at scale?