Integrating generative AI in nursing education: A comparative analysis of faculty knowledge, skills, and attitude

AbstractBackgroundArtificial intelligence is transforming healthcare education through tools that support clinical decision-making, personalized learning, and simulation-based training. However, its integration into nursing education varies globally, often limited by differences in faculty readiness and institutional support.AimTo assess and compare nursing faculty members’ self-perceived knowledge, skills, and attitudes toward integrating generative AI in nursing education across the United States, Egypt, and Israel.MethodsA cross-sectional comparative survey was conducted between May and September 2024, involving 157 nursing faculty members from the United States (n = 72), Egypt (n = 41), and Israel (n = 44). The survey measured self-reported knowledge, skills, and attitudes using Likert-scale items and open-ended responses, structured by Bloom’s taxonomy.ResultsMost faculty expressed positive attitudes, with 79.3% believing AI will transform nursing education. However, only 4.8% identified as experts. Faculty in Egypt and Israel reported higher knowledge, skills, and attitudes compared to those in the United States. Only 24.0% indicated their institution had formal AI-related policies.ConclusionsDespite enthusiasm, knowledge gaps and limited institutional support challenge effective AI integration in nursing education.