Nursing students are adopting AI well ahead of the programs training them, leaving faculty to set rules for behavior that is already embedded in how students study, according to a recent Wolters Kluwer survey.
Adoption is established but uneven across degree paths. Among the 394 U.S. nursing students surveyed, 79% of Bachelor of Science in Nursing students reported using AI, compared with 77% of Licensed Practical Nurse students and 66% of Associate Degree in Nursing students. Use ran higher among first-year students, which the report attributed to more recent exposure to fast-expanding tools.
Most who use AI do so often: 25% reported using it two or more times a week, 20% daily and 21% about once a month.
Students framed AI as a study aid, not a substitute for instruction. About half use it for studying (53%), testing their knowledge (49%) and preparing for exams (45%) — and they expect that to grow, with future use rising to 66% for studying, 60% for knowledge testing and 57% for exam preparation.
When asked what prevents AI use, 57% of students cited a lack of confidence that answers would be accurate, by far the leading barrier. Smaller shares pointed to tools not being approved by their school (33%), concern that AI could interfere with building clinical knowledge and skills (28%), limited understanding of AI’s strengths and weaknesses (28%) and data and security concerns (25%). Students and faculty alike named one shared reservation: that overreliance could erode critical thinking and clinical reasoning.
Student demand is ahead of program readiness. A separate national study of prelicensure programs, published in October 2025 the Journal of Nursing Regulation and cited in the survey, found only 24% of RN programs use generative AI and only 17% teach AI or digital health topics, while more than 75% either do not use AI or are unsure of its role. Limited faculty training and confidence is a central reason, the researchers found.
To close the gap, the survey recommended programs invest in faculty training, embed AI within existing course materials rather than leaving students to unapproved outside tools, focus its use on clinical application and set explicit policies on ethical use and academic integrity.
The stakes extend beyond the classroom: health systems are already embedding AI into nursing practice itself, from ambient documentation tools at Palo Alto, Calif.-based Stanford Medicine and Tampa (Fla.) General Hospital to a nurse-focused documentation tool under development at Chesterfield, Mo.-based Mercy, meaning today’s students will graduate into workplaces where AI will be part of the standard clinical workflow.
