Researchers surveyed a single cohort of students three days before the event and again within one week after it. Of 91 students who completed the baseline survey, 50 completed both rounds and were matched for analysis using a four-digit academic identification code. The questionnaire comprised 15 Likert-scale items grouped into perceived-benefit and concern-related domains, and a composite AI perception score was calculated as the mean of all 15 items after reverse coding the concern-oriented items, with higher scores indicating more positive perceptions.

The changes in knowledge and confidence were striking. Agreement that AI will play an important role in healthcare rose from 41 of 50 students (82 percent) to 48 of 50 (96 percent). Agreement with the statement that they understood basic AI principles jumped from 18 of 50 (36 percent) to 46 of 50 (92 percent).

Comfort with AI terminology climbed from 23 of 50 (46 percent) to 43 of 50 (86 percent), and confidence in using basic healthcare AI tools rose from 29 of 50 (58 percent) to 45 of 50 (90 percent). The composite perception score increased by 0.28 points on the study's 1-to-5 scale, a change the authors characterise as a moderate short-term perceptual shift. The paired-sample t-test yielded t(49) = −4.52, p < .001, with a 95 percent confidence interval of 0.16 to 0.40 points and a Cohen's d of 0.64, a medium effect size.

But the concern-related items moved in the opposite direction. Agreement that some medical specialties may be replaced by AI rose from 17 of 50 students (34 percent) to 25 of 50 (50 percent). Agreement that AI may replace radiologists increased from 14 of 50 (28 percent) to 22 of 50 (44 percent).

Most pointedly, reluctance to consider radiology as a career rose from 14 of 50 (28 percent) to 25 of 50 (50 percent). The authors used two established frameworks in technology research—the Technology Acceptance Model and the Unified Theory of Acceptance and Use of Technology—as interpretive lenses for the findings. The post-campaign picture was therefore one of increased perceived benefit and self-reported understanding alongside increased concern, rather than a uniformly favourable perceptual change.

Students can simultaneously rate AI as more relevant to their future, feel more capable of engaging with it, and believe it endangers their chosen career path. Several limitations temper the conclusions. The study was a single-cohort pre–post survey at one institution with a modest matched sample of 50 students, and it relied on self-reported understanding rather than objective measures of AI knowledge.

Even so, the study offers a concrete lesson for medical educators navigating the AI era. The authors conclude that brief AI-awareness activities may benefit from explicitly addressing AI limitations, automation anxiety, specialty-replacement narratives, and the continuing role of human clinical judgment—for example through structured discussions that distinguish task automation from physician replacement. The Robomedic results suggest that teaching students what AI can do, without also addressing its limitations and the continuing role of human clinical judgment, may leave future doctors better informed about the technology but more anxious about their place beside it.

Subject of Research: Medical students’ perceptions of artificial intelligence following the “Robomedic” AI-awareness campaign: a pre–post survey study in Saudi Arabia

Article Title: Medical students’ perceptions of artificial intelligence following the “Robomedic” AI-awareness campaign: a pre–post survey study in Saudi Arabia

Article References: Moria, A., Alabdullatif, N., Alrasheed, A., AlOmair, A., Al-mutairi, A., Alhashim, Z., Almajed, S., & Alomair, A. M. (2026). Medical students’ perceptions of artificial intelligence following the “Robomedic” AI-awareness campaign: a pre–post survey study in Saudi Arabia. BMC Medical Education. https://doi.org/10.1186/s12909-026-10250-6

Image Credits: AI Generated

DOI: 10.1186/s12909-026-10250-6

Keywords: Medical, students, perceptions, artificial, intelligence, following, Robomedic, AI-awareness, campaign, post, survey, Saudi