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Nurse educators' experiences and perceptions using generative artificial intelligence: a systematic review

Aug 2026 · BMC Medical Education · Vol 26 · 0 citations · 34 references
Medicine

TL;DR

A tension between optimism about Generative AI’s pedagogical potential and apprehension about its ethical, educational, and professional implications is revealed, highlighting the need for systematic capacity-building in nurse education.

Abstract

The rapid uptake of generative artificial intelligence (GenAI) in higher education has increased both enthusiasm and concern. While students’ use of GenAI has been widely discussed, empirical research focusing on nurse educators’ own experiences and perceptions remains limited. This systematic review synthesizes evidence on nurse educators’ experiences of using generative artificial intelligence in teaching. A systematic literature review was conducted in accordance with PRISMA 2020 guidelines. Searches were performed in PubMed, CINAHL, Web of Science, and ERIC. Peer-reviewed empirical studies published in English were included. Two reviewers independently screened records, extracted data, and conducted quality appraisal using established tools. Due to methodological heterogeneity, results were synthesized thematically. Thirteen studies were included, representing a total of 3082 participants. Two overarching themes were identified: (1) Nurse educators’ opportunities and challenges using Generative AI in teaching, and (2) Nurse educators’ competence and ways of using Generative AI. Educators described Generative AI as a potentially valuable resource for teaching efficiency and organizational and pedagogical inspiration. They expressed concerns relating to their loss of professional roles, academic integrity, and erosion of critical thinking related to students. Experience with Generative AI, institutional position, organizational policy and support influenced educators’ attitudes, confidence, and use. The findings reveal a tension between optimism about Generative AI’s pedagogical potential and apprehension about its ethical, educational, and professional implications. Educators’ calls for clearer policies, competency development, and institutional support highlight the need for systematic capacity-building. Generative AI's value depends on educators' skills, supportive policies, and intentional use, making structured training and governance essential for integration in nurse education.

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