Transforming Nursing Education with Artificial Intelligence: A Systematic Review (2010–2025)

Synthesis: Alrazeeni et al. (2026) provide the first comprehensive systematic review of empirical AI applications in nursing education (28 studies, 2010–April 2025, from PubMed, CINAHL, IEEE Xplore, and Scopus). They find AI enhances nursing education in four areas — personalized learning, simulation-based training, automated assessment, and institutional curriculum management/predictive analytics — while surfacing recurring risks (technological inequity, faculty preparedness gaps, privacy and bias concerns). They offer concrete implementation recommendations and propose diagnostic accuracy as a measurable outcome.

Key Findings

1. Four application areas. AI in nursing education centers on: (a) personalized learning systems tailoring content to individual needs; (b) simulation-based training improving decision-making in high-acuity scenarios; (c) automated assessment providing immediate, unbiased feedback; (d) institutional-level AI for curriculum management and predictive analytics.
2. Recurring risks. Technological inequities, faculty preparedness gaps, and ethical concerns around privacy and bias are common across studies.
3. Actionable recommendations. Integrate AI-powered simulation into emergency-care training; deploy adaptive platforms to support at-risk learners; use automated tools for real-time formative feedback; and adopt diagnostic accuracy as a measurable outcome for assessing impact.
4. Next step. Initiate multi-site pilot programs over 6–12 months, evaluating improvements in learning outcomes, trust, and system integration.

Implications

This review brings the wiki's AIED themes into the clinical/health-professions context, extending Simulation-based training, Personalized Learning, and Automated Assessment to nursing. It exemplifies a thematic systematic review method and connects to medical-education and health-professions-education applications of AI, as well as to equity and Ethics concerns. The focus on faculty preparedness aligns with Faculty Development and Teacher Role; the emphasis on validated, measurable outcomes connects to AI Ed Evaluation and Educational Measurement.

Connected Concepts

• Simulation
• Personalized Learning
• Adaptive Learning
• Automated Assessment
• Curriculum Design
• Equity In AI Education
• Ethics
• Meta Analysis Systematic Review
• Faculty Development
• AI Ed Evaluation

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• Hdr Brachytherapy Agentic AI Simulation 2026 — Agentic AI simulation in clinical training
• Residencyrl Clinical RL Training 2026 — RL-based clinical training
• Simulating Students Java Programming Errors Llms — LLM simulation of learners

Citation

Alrazeeni, D. M., Alharrasi, M., Rony, M. K. K., Biswas, R. K., Tama, I. J., Halder, C. R., Deb, B., Bashar, F., & Akter, F. (2026). Transforming nursing education with artificial intelligence: A systematic review (2010–2025). SAGE Open Nursing, 12, 1–31. https://doi.org/10.1177/23779608261424597