Most published evidence on AI in nursing education records what students and nurses think and know about AI. Reviews from 2025 found generally positive attitudes and weaker practical use, with only one trial among 37 studies in one of them. A 2026 meta-analysis of 16 studies, seven of them randomized, reports gains in knowledge and practical skills in nursing courses but calls its own results preliminary. The National League for Nursing (NLN) has said that bringing AI into nursing education is not optional.
Key takeaways
- A Frontiers in Medicine review pooled 18 studies and reported 73 percent awareness, 71 percent positive attitudes, and 67 percent implementation, with very high heterogeneity.
- A Frontiers in Digital Health review of 37 studies found 28 cross-sectional surveys and one quasi-experimental trial.
- A 2026 meta-analysis of 16 studies (1,647 participants, seven randomized trials) found moderate to large gains in knowledge and practical ability, with heterogeneity above 90 percent for both.
- A second 2026 review found only three quasi-experimental studies of AI literacy training for nursing students and no randomized trial.
- The NLN's September 2025 vision statement recommends national competency standards for nurses. No such standard had been adopted in the sources checked.
What the largest 2025 review pooled
Majeda El-Banna and colleagues published a systematic review and meta-analysis in Frontiers in Medicine on November 26, 2025. The systematic review covered 111 peer-reviewed articles, and the meta-analysis pooled 18 quantitative studies. With a random-effects model, the pooled share was 73 percent for AI-related awareness (95 percent confidence interval 64 to 80 percent), 71 percent for attitudes (63 to 78), and 67 percent for implementation (55 to 78).
Students scored higher than practicing nurses on all three measures, but the gaps were not equally firm. Awareness was 79 percent among students and about 66 percent among nurses, attitudes 75 and 63 percent (not statistically significant, p=0.123), and implementation 78 percent against 56 percent (p=0.049). The authors describe curricula as fragmented and often not standardized, and they name faculty readiness, infrastructure, and institutional support as recurring barriers, with the largest gaps in low-resource settings.
The statistics carry a warning. Between-study inconsistency (I-squared) was 97 percent for awareness, 96.1 percent for attitudes, and 98 percent for implementation, so the studies disagreed far more than chance would explain. The authors state that the pooled proportions provide directional rather than definitive evidence.
What a second 2025 review found about study designs
Rabie Adel El Arab and colleagues reviewed 37 studies, published from 2022 to May 2025 with a combined sample of about 10,290, in Frontiers in Digital Health. Of these, 28 were analytical cross-sectional surveys, eight were qualitative studies, and one was a quasi-experimental trial. Students' attitudes toward AI were moderately positive, with item means from 3.03 to 3.86 on five-point scales.
One workshop for nurses raised the share holding positive attitudes from 26.1 percent to 81.8 percent, but three months later it had fallen to 63.5 percent, which the authors read as a case for booster sessions. Among neonatal nurses (107 participants), higher anxiety went with lower readiness. The authors call their overall conclusion guarded optimism. The studies come mainly from Turkey, Egypt, and Saudi Arabia, and the review itself says the findings should not be generalized beyond those perspectives.
2026 reviews: the first randomized evidence on learning
Two reviews published in 2026 move the question from attitudes toward learning outcomes. Wang and colleagues searched eight databases through February 2026 for trials of AI in nursing practice courses. Their meta-analysis in the Journal of Nursing Management included 16 studies with 1,647 participants, seven randomized controlled trials and nine quasi-experimental studies. It reports a standardized mean difference of 0.72 for knowledge (95 percent confidence interval 0.20 to 1.24), 1.25 for practical ability (0.50 to 2.00), 0.43 for critical thinking and clinical reasoning, 0.38 for learning satisfaction, and 0.50 for ethical awareness and decision-making. Heterogeneity was 91 percent for knowledge and 95 percent for practical ability. The authors call the results preliminary and ask for higher-quality research.
The narrower review, by Xia and colleagues, searched seven databases through March 24, 2026 for studies of AI literacy training for nursing students. It found three quasi-experimental studies with 443 students and no randomized trials. All three reported improved AI literacy, but different instruments prevented a meta-analysis. Neither review measures what happens at the bedside, and neither follows students into practice.
What professional bodies say
On September 17, 2025, the NLN published a vision statement on AI in nursing education. It recommends professional development for educators through workshops, micro-credentials, and work with data scientists. It also calls for national AI literacy and competency standards for licensed nurses, separating foundational knowledge such as ethics, societal impact, and basic function from advanced clinical application. It asks institutions to invest in AI-enabled learning platforms, simulation tools, and data analytics, and to keep curricula flexible enough to update quickly. In May 2026 the NLN and Walden University announced a joint national institute for AI aimed at AI leadership in nursing education.
The American Association of Colleges of Nursing (AACN) released a 2026 edition of its Essentials curriculum framework on April 22, 2026. Its listed changes, such as a fourth concept called Access, Connection, and Engagement, include no AI-specific competencies. AI shows up elsewhere on AACN's Essentials page: a post-conference workshop titled "Designing the Future of Nursing Education with AI" on January 14 and 15, 2027, in Coronado, California, focused on mapping competencies, finding curriculum gaps, and designing assessments. A workshop notice is not a standard, and it does not report outcomes.
Reading the reviews together
| Item | El-Banna et al., 2025 | El Arab et al., 2025 | Wang et al., 2026 |
|---|---|---|---|
| Journal | Frontiers in Medicine | Frontiers in Digital Health | Journal of Nursing Management |
| Studies | 111 reviewed, 18 pooled | 37 | 16, with 1,647 participants |
| Main designs | Quantitative studies pooled; designs varied | 28 cross-sectional, eight qualitative, one quasi-experimental | Seven randomized, nine quasi-experimental |
| Main result | Positive awareness and attitudes, weaker implementation | Moderately positive attitudes, anxiety lowers readiness | Gains in knowledge, practical ability, reasoning, and satisfaction |
| Stated limit | Very high heterogeneity; English-language, mostly high- and middle-income countries | Few trials, narrow set of countries, varied instruments | High heterogeneity; authors call results preliminary |
Together they show a shift from asking what nurses believe about AI to testing what students learn from it. None shows that students taught with AI tools make fewer errors at the bedside, and none supports a claim that AI improves licensure results or patient safety.
Questions a nursing program can ask about an AI tool
- Which outcome is being claimed: satisfaction, knowledge scores, skills in simulation, or clinical performance?
- Does the evidence come from a comparison group, or only from surveys of people who chose to take part?
- Who on the faculty reviews AI-generated material before students see it?
- Where did the studies take place, and are the settings similar to the program's own?
- Is there a plan to refresh training, since the workshop result above faded over three months?
- How are student data handled when a third-party tool is used?
This page gives general information about education research and professional statements. It is not medical advice, and nothing in it is a guide to diagnosing, treating, or caring for a patient. Clinical decisions belong with licensed professionals and the patient, and teaching content for a program belongs with its faculty and accrediting body.
FAQ
Does AI make nursing students better at patient care?
No review checked here tests that. The 2026 meta-analysis reports better knowledge and practical-ability scores in coursework, and the authors treat it as preliminary. The 2025 reviews report attitudes, awareness, and readiness only.
Are nursing students more positive about AI than working nurses?
In the pooled 2025 results, students scored higher on all three measures: awareness, attitudes, and implementation, though only the implementation gap was statistically significant. The studies disagreed widely with each other, so the gap is a direction and not a precise figure.
Is there a national standard for AI skills in nursing?
The NLN's 2025 statement recommends one but does not itself set it. The AACN's 2026 Essentials edition lists no AI-specific competencies, and its AI material found is a workshop announcement.
Does Canada have a comparable guideline?
A Canadian guideline specific to AI in nursing education could not be verified for this page, so none is described.
Related reading
- How AI is regulated and used in Canadian health care
- Where bias enters health AI
- AI in education research
- AI in classrooms, by evidence
More in AI in health.
Last verified: October 2026
Sources
- AI literacy and competency in nursing education: preparing students and faculty members for an AI-enabled future, a systematic review and meta-analysis, El-Banna MM et al., Frontiers in Medicine 12:1681784, November 2025
- Artificial intelligence in nursing: a systematic review of attitudes, literacy, readiness, and adoption intentions among nursing students and practicing nurses, El Arab RA et al., Frontiers in Digital Health 7:1666005, 2025
- Artificial Intelligence in Nursing Practice Education: A Systematic Review and Meta-Analysis, Wang J et al., Journal of Nursing Management, 2026
- Artificial intelligence (AI) literacy educational interventions among nursing students: a systematic review and narrative synthesis, Xia M et al., 2026
- NLN Publishes New Vision Statement on Artificial Intelligence (AI) in Nursing Education, National League for Nursing, September 17, 2025
- NLN and Walden University launch National Institute for Artificial Intelligence, National League for Nursing, May 11, 2026
- Essentials and Essentials Updates, American Association of Colleges of Nursing website, 2026 edition posted April 22, 2026