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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

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Students Are Ready for AI-But Is Medical Education?

Sholem Hack¹, Lilia Ann Crew², Armin Farzad³

¹City St. George's University London School of Medicine, Program Delivered by University of Nicosia at the Chaim Sheba Medical Center, Ramat Gan, Israel.

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|December 8, 2025

Summary

This summary is machine-generated.

Medical students show high Artificial Intelligence (AI) awareness but limited access to AI tools. There is a strong demand for structured AI training, yet institutions are unprepared, highlighting a gap in medical education.

Keywords:

AI literacy artificial intelligence curriculum development medical education medical students

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Area of Science:

Medical Education
Artificial Intelligence in Healthcare
Digital Health Literacy

Background:

Formal Artificial Intelligence (AI) instruction in medical training is limited despite AI's growing relevance.
This study investigates medical students' awareness, access to AI learning tools, and perceptions of institutional readiness for AI integration.

Purpose of the Study:

To assess medical students' awareness and access to AI-integrated learning tools.
To evaluate students' views on institutional preparedness for AI in medical education.
To identify barriers to AI adoption in medical training.

Main Methods:

A cross-sectional survey was conducted with 391 medical students from over 30 countries in January-February 2025.
Data collected included AI awareness, proficiency, tool access, institutional preparedness, and perceived barriers.
Statistical analyses (ANOVA, t-tests, χ² tests) were used to examine differences based on training stage, institution type, and country classification.

Main Results:

High AI awareness (91.6%) was reported, but only 58.1% had access to AI tools.
Student AI proficiency increased with training stage.
A significant demand for structured AI training (82.1%) contrasts with low perceived institutional preparedness (34.5%).

Conclusions:

Medical education needs structured AI training focusing on applied skills, ethics, and critical appraisal.
Aligning student demand for AI education with institutional readiness is crucial.
Addressing barriers such as lack of training, cost, and reliability concerns is essential for effective AI integration.