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Medical students want AI training but few feel ready, review of 26 studies finds

Study title: Is it time to introduce an artificial intelligence curriculum in undergraduate medical education? medical students’ perspectives: a systematic review and meta-analysis

Evidence type
Systematic review or meta-analysis
Sample
n = 20,963
Sources
1 sourcePeer-reviewed
Published
2 min read
Truvace record
TRV-2026-2784cite or check it

Study title: Is it time to introduce an artificial intelligence curriculum in undergraduate medical education? medical students’ perspectives: a systematic review and meta-analysis

A systematic review and meta-analysis pooled 26 studies covering 20,963 medical students. It found 78.0% (16,278) held positive attitudes toward adding AI to the undergraduate curriculum, and 83.1% (17,420) agreed AI training is necessary.

Read the study abstract

BACKGROUND: Although artificial intelligence (AI) is increasingly transforming healthcare systems, its systematic integration into undergraduate medical education (UME) remains limited. Despite widespread recognition of AI's potential to enhance clinical practice, AI-related competencies are still inadequately embedded in most medical curricula, even though medical students generally express positive attitudes toward AI. OBJECTIVES: This systematic review and meta-analysis synthesizes the current literature on m…

The problem

A systematic review of 26 studies of 20,963 medical students found 83.1% agreed AI training is necessary, yet only 36.4% felt confident applying AI in clinical practice.

In brief

Only 36.4% (7,630) of students felt confident applying AI in clinical practice. The authors call this the 'optimism-competence gap' and say a standardized, competency-based AI curriculum is needed to close it.

Schools face barriers to teaching AI. Curricular overcrowding was reported in 13 of 19 studies (68%), lack of faculty expertise in 12 of 23 (52%) and ethical concerns in 9 of 22 (41%). Support for AI teaching was consistent across geographic regions.

Main points

  1. The review searched PubMed, Web of Science, Scopus and Cochrane Library for studies published between January 2000 and February 2025, following PRISMA guidelines.
  2. It included 26 studies with 20,963 medical students in total.
  3. In the pooled analysis, 78.0% of students (16,278) held positive attitudes toward AI curriculum integration.
  4. 83.1% of students (17,420) agreed AI training is necessary, but only 36.4% (7,630) felt confident using AI clinically.
  5. Curricular overcrowding was the most common barrier, reported in 68% of the studies that assessed it, ahead of faculty expertise gaps (52%) and ethical concerns (41%).
  6. The authors recommend prioritizing faculty training, interdisciplinary collaboration and ethical frameworks.

What the review found when it combined the studies

These are the review’s own pooled results, copied from its abstract. Truvace did not recalculate them.

  • Medical students with positive attitudes toward AI curriculum, adjusted for possible publication bias (trim-and-fill)

    Proportion 0.818 (95% CI 0.771 to 0.861)

    26 studies · 20,963 people · search to February 2025

    The review’s own words
    However, the use of the Trim-and-Fill method gave the imputation of six studies, shifting the random-effects pooled proportion to 0.818 (95% CI: 0.771–0.861) with a prediction interval of [0.500; 0.991] (see Supplementary Material: Appendix 3, Figure S1).

  • Positive attitudes toward AI curriculum among medical students in the Middle East

    Proportion 0.730 (95% CI 0.660 to 0.800)

    search to February 2025

    The review’s own words
    The pooled proportion with favorable attitudes toward AI was: North America (0.780, 95% CI: 0.660–0.880), Asia (0.780, 95% CI: 0.700–0.860), the Middle East (0.730, 95% CI: 0.660–0.800), and other regions (0.910, 95% CI: 0.830–0.960).

  • Positive attitudes toward AI curriculum among medical students in North America

    Proportion 0.780 (95% CI 0.660 to 0.880)

    search to February 2025

    The review’s own words
    The pooled proportion with favorable attitudes toward AI was: North America (0.780, 95% CI: 0.660–0.880), Asia (0.780, 95% CI: 0.700–0.860), the Middle East (0.730, 95% CI: 0.660–0.800), and other regions (0.910, 95% CI: 0.830–0.960).

  • Medical students with positive attitudes toward AI curriculum integration (common-effect model)

    Proportion 0.779 (95% CI 0.774 to 0.783)

    26 studies · 20,963 people · search to February 2025

    The review’s own words
    Overall, the proportion with favorable attitudes was 0.779 (95% CI: 0.774–0.783) under the common-effect model and 0.780 (95% CI: 0.730–0.820) under the random-effects model using the DerSimonian-Laird estimator (Fig. 2 ).

  • Positive attitudes toward AI curriculum among medical students in other regions

    Proportion 0.910 (95% CI 0.830 to 0.960)

    search to February 2025

    The review’s own words
    The pooled proportion with favorable attitudes toward AI was: North America (0.780, 95% CI: 0.660–0.880), Asia (0.780, 95% CI: 0.700–0.860), the Middle East (0.730, 95% CI: 0.660–0.800), and other regions (0.910, 95% CI: 0.830–0.960).

  • Positive attitudes toward AI curriculum among medical students in Asia

    Proportion 0.780 (95% CI 0.700 to 0.860)

    search to February 2025

    The review’s own words
    The pooled proportion with favorable attitudes toward AI was: North America (0.780, 95% CI: 0.660–0.880), Asia (0.780, 95% CI: 0.700–0.860), the Middle East (0.730, 95% CI: 0.660–0.800), and other regions (0.910, 95% CI: 0.830–0.960).

  • Medical students with positive attitudes toward AI curriculum integration (random-effects)

    Proportion 0.780 (95% CI 0.730 to 0.820)

    26 studies · 20,963 people · search to February 2025

    The review’s own words
    Overall, the proportion with favorable attitudes was 0.779 (95% CI: 0.774–0.783) under the common-effect model and 0.780 (95% CI: 0.730–0.820) under the random-effects model using the DerSimonian-Laird estimator (Fig. 2 ).

  • Positive attitudes toward AI curriculum in studies using standardized questionnaires

    Proportion 0.780 (95% CI 0.690 to 0.850)

    search to February 2025

    The review’s own words
    Stratified by type of questionnaire, researcher-developed surveys gave a proportion of 0.780 (95% CI: 0.710–0.840), and standardized tools gave 0.780 (95% CI: 0.690–0.850).

  • Positive attitudes toward AI curriculum in studies using researcher-developed surveys

    Proportion 0.780 (95% CI 0.710 to 0.840)

    search to February 2025

    The review’s own words
    Stratified by type of questionnaire, researcher-developed surveys gave a proportion of 0.780 (95% CI: 0.710–0.840), and standardized tools gave 0.780 (95% CI: 0.690–0.850).

Code checks every number above against the review’s text before it is shown. The short labels are an AI model’s reading of that text, so the review’s own sentence sits under each one. A pooled figure is only as strong as the studies behind it. How Truvace uses pooled results

The full story

The authors searched four databases for studies from January 2000 to February 2025 and pooled student support using a random-effects model with Freeman-Tukey transformation. The 26 included studies assessed attitudes and challenges related to learning AI among 20,963 medical students.

Students were broadly supportive: 78.0% favored integrating AI into the curriculum, and subgroup analyses showed the support held across geographic regions. Confidence lagged far behind, with 36.4% feeling able to apply AI in clinical practice.

On the supply side, the barriers were crowded curricula, limited faculty expertise and ethical concerns. The authors conclude that a standardized AI curriculum is urgently needed and that faculty training should come first.

Sources

1 on file
  1. BMC Medical Educationdoi:10.1186/s12909-026-09630-9
    Peer-reviewed2026-06-17

Talk it over

Four questions to start onWho carries this cost, and what would have to change to prevent it?

Start with a question

Medical students want AI training but few feel ready, review of 26 studies findshttps://truvace.com/item/is-it-time-to-introduce-an-artificial-intelligence-curriculum-in-undergraduate-m

  1. Who carries this cost, and what would have to change to prevent it?

    The problem A systematic review of 26 studies of 20,963 medical students found 83.1% agreed AI training is necessary, yet only 36.4% felt confident applying AI in clinical practice.

    Answer in the thread

  2. How do we know? What can this kind of evidence show, and what can’t it?

    The evidence This rests on a systematic review or meta-analysis with a sample of 20,963, from BMC Medical Education.

    Answer in the thread

  3. What does it leave open? What else would you want to know before acting on it?

    The record’s own caveat The meta-analysis found extreme heterogeneity across studies (I² = 98.5%), so the pooled proportions mask large differences between the underlying studies.

    Answer in the thread

  4. Have you seen AI used this way where you study, work or live? Did it go the same way?

    Answer in the thread

The questions are the same on every record. The details under them are taken from this record as written.

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