Nursing students are not waiting for permission to use AI. Two-thirds report using AI tools at least weekly, and a quarter use them daily, according to the Wolters Kluwer survey “Nursing students’ experiences and attitudes toward AI.” For nursing deans, faculty, and program directors, the question is no longer whether students will bring AI into their academic work. The question is how programs will shape that behavior into something rigorous, ethical, and aligned with trusted clinical content.
The same survey shows adoption that is frequent, practical, and largely self-directed. Students reach for AI to study, test their knowledge, and prepare for exams, treating it as a supplemental learning aid rather than a replacement for instruction. That pattern gives faculty a real starting point. Programs are not building from zero. They are bringing structure to behavior that already exists.
How are nursing students using AI today?
Adoption is established but uneven. In the Wolters Kluwer survey, 79% of Bachelor of Science in Nursing students, 77% of Licensed Practical Nurse students, and 66% of Associate Degree in Nursing students reported using AI. Higher usage among first-year students likely reflects more recent exposure to tools that have expanded quickly in recent years.
Students described how they actually apply these tools. About half use AI for studying, knowledge testing, and exam preparation, and they expect that use to grow. Reported future use rises to 66% for studying, 60% for knowledge testing, and 57% for exam preparation. The throughline is utility. Students engage when a tool helps them study more efficiently, check clinical understanding, or get quick feedback. For a closer look at how technology is reshaping the student experience, see our Expert Insight on the future of nursing education and the role of technology.
What is preventing nursing students from fully trusting AI?
Trust is the gating factor. When asked what prevents AI use, 57% of students named a lack of trust that the answer will be accurate, by far the leading barrier. Other concerns followed: 33% cited tools not being approved by their school, 28% worried AI could interfere with building the knowledge and skills they need, 28% pointed to a limited understanding of AI’s strengths and weaknesses, and 25% raised data and security concerns.
That hesitation is discerning rather than dismissive. Students value efficiency and quick feedback, yet they hold a clear preference for credible, human-developed resources. A recurring theme in student interviews, one that instructors echoed as their own most significant reservation, is a fear that overreliance on AI could erode critical thinking and clinical reasoning. Meeting that concern means grounding AI in content students can trust. Our Expert Insight on preparing nursing students for the future of healthcare explores how to build that foundation.
How can nursing programs guide the use of AI in education?
A gap sits between student behavior and program design. National research cited in the survey found that only 24% of RN programs report using generative AI, only 17% teach AI or digital health topics, and more than 75% either do not use AI or are unsure of its role. Faculty readiness is a central reason, as many educators lack the training, exposure, or confidence to fold AI into teaching with intention.
The survey points to a practical action plan that turns scattered experimentation into guided use:
- Commit to faculty enablement. Discipline-specific use cases, such as reinforcing complex concepts or generating practice questions, help shift adoption from avoidance to guided use.
- Embed AI within trusted learning environments. Integrating AI into existing course materials provides real-time support and reduces reliance on external or unapproved tools.
- Focus on clinical application. AI should help students connect foundational knowledge to real-world scenarios, decision-making, and patient care.
- Understand usage patterns and set clear guidelines. Insight into how students engage with AI, paired with explicit policies on ethical use and academic integrity, reduces variability and supports core competencies.
Faculty leadership makes the difference between exposure and applied learning. For more on supporting educators in this shift, read our Expert Insight on how faculty can support nursing student success.
Preparing nursing education programs for the AI era
Students have already given programs a head start. They are engaging with AI, forming expectations, and asking, through their hesitation, for guidance they can trust. The opportunity for academic leaders is to meet that readiness with structure: enable faculty, ground AI in curriculum-aligned content, and define clear expectations for ethical, clinically relevant use.
That is the foundation Lippincott® Nursing Education is built to support, integrating evidence-based content, assessment, and analytics into a connected learning experience so AI strengthens comprehension and clinical reasoning rather than replacing it. The result is stronger student outcomes, greater faculty confidence, and a program prepared for what comes next.