Exploring Policy for Generative Artificial Intelligence in Nursing Education: Student and Faculty Perceptions

BACKGROUND: Generative artificial intelligence (GAI) is rapidly reshaping higher education, creating opportunities and challenges related to academic integrity, educator readiness, and policy clarity, particularly in nursing education. PURPOSE: To examine nurse educator and student perspectives on GAI use, institutional policies, syllabus language, and best practices in nursing education. METHODS: A descriptive quantitative survey was completed by 211 nurse educators and 89 nursing students (N = 300) across diverse nursing programs. Data were analyzed by program type, learning model, and degree level. RESULTS: Findings revealed widespread uncertainty and inconsistent communication of GAI policies and expectations. Students reported greater confusion regarding acceptable use and institutional guidance, while educators described decentralized and inconsistent approaches. Demographic factors were not significantly associated with perceptions. CONCLUSIONS: Nursing education requires clearer, more accessible, and unified approaches to GAI governance to support ethical, effective, and pedagogically sound integration.