For decades, educators have sought better ways to prepare students for a rapidly evolving clinical environment. Now, artificial intelligence (AI) is emerging as an important part of the roadmap. AI is playing into adaptive learning systems, virtual simulations and predictive analytics to personalize education in ways previously unimaginable.
However, this transformation won’t happen in isolation. Of course, AI presents exciting opportunities to evolve the education landscape, but it also presents equally weighted risks and challenges. In many ways, the success of AI in education depends less on whether the technology exists and more on how it is deployed. With strategic leadership and thoughtful integration, AI has the potential to transform nursing education for the better.
It’s Here: AI Use in Nursing Education
Nursing programs have been facing mounting pressure for years: faculty shortages, rising enrollment demands and the need to train graduates who can handle increasingly complex patient scenarios. Traditional models centered on lectures, flash cards and static resources are struggling to keep up. As a result, students and faculty alike are turning to AI to amp up their curricula. As reported in the Digital Education Council Global AI Faculty Survey 2025, the majority (61%) of teaching faculty are already involving AI in their curriculum, and even more (86%) expect to use AI in the future. It is clear that AI is charging ahead in education, with or without leadership buy-in.
In nursing education specifically, AI can offer a revitalized path forward when leveraged by faculty to augment their clinical training. By harnessing machine learning and natural language processing, AI can streamline workflows, personalize instruction, and provide richer clinical training experiences. Integrating AI in education and training for nurses presents a unique opportunity to boost workforce readiness and patient safety. But as we implement new technologies and tools into our studies and training, we must take a thoughtful, pragmatic approach.
Key Opportunities for AI Application in Nursing Education
- Adaptive Learning for Smarter Education
AI-driven platforms can track how students interact with course content and tailor recommendations to their unique needs. For example, a pharmacology module might not just display a grade but identify specific pharmacological categories where a student demonstrates gaps — and then generate targeted practice questions on demand. In recent years, studies have correlated adaptive learning with reduced remediation rates and improved NCLEX outcomes, indicating that technology-supported approaches can have meaningful impact on student success.
- Immersive Clinical Simulations
Simulation technology has been shown to be a successful companion technology to the clinical rotations nursing students traditionally receive. With conversational AI and augmented reality, students can engage in realistic, dynamic scenarios where virtual patients respond to assessment questions, exhibit complex, changing symptoms and react to care decisions.
These simulations allow students to practice critical thinking in high-stakes scenarios, while caring for multiple “patients” without any risk to real people. AI can even adapt the case based on student actions, offering infinite variations on the same clinical theme or offering uniquely diverse cases that a student may otherwise not experience in clinical rotations. Additionally, for educators and administrators, these tools are built to adhere to competency-based educational models, ensuring curriculum alignment.
- Continuous Student Support
AI is also changing how students receive support. AI-powered smart assistants can provide 24/7 answers to course-related questions or remind students of deadlines. This proactive approach can make the difference between retention and dropout, especially in high-stress accelerated nursing programs. By automating routine inquiries and offering scalable support, AI can also alleviate faculty workload, allowing educators to focus on higher-impact teaching and mentorship.
The Realities We Can’t Ignore
While the upside of AI in nursing education is compelling, its adoption introduces new risks and complexities. Ignoring them could undermine trust, equity and even compliance.
- Academic Integrity in the Age of Generative AI
The reality is, even if your program isn’t an early adopter of AI, your students likely are. Generative AI tools make it easy for students to create essays, care plans and discussion posts with minimal effort. Without clear guidelines, the line between assistance and academic dishonesty can blur. Faculty must collaborate to define ethical AI use in academic work and provide educational resources that teach students how to engage responsibly with these tools.
- Know Where Your Data is Coming From
When it comes to some of the most common complaints around AI, hallucinations and misinformation are some things that cannot be ignored. Because of that, leveraging AI systems that are based on trusted, evidence-based healthcare data that nurses need to be trained on is key. Leveraging publicly available AI bots may be helpful for guidelines, but proceed cautiously as that information is coming from anywhere on the internet.
- The Equity Imperative
AI-enhanced education risks widening the gap between students who have access to robust technology and those who don’t. High-speed internet, mobile and modern devices aren’t guaranteed for every learner. When applied thoughtfully, AI should narrow, not widen, the opportunity gap. As we implement AI, we still need to provide careful consideration to students who may be working with fewer resources and look to bridge the gap with solutions or support wherever possible.
Building a Roadmap for Responsible Innovation
AI in nursing education is a major inflection point. The institutions that succeed through the advent of AI will be those that combine visionary technology adoption with disciplined execution and ethical foresight.
As leaders in nursing education, we have a pivotal role to play. Here are several principles to guide the journey:
- Start with outcomes, not tools. Vet and select solutions that directly align with educational goals, from clinical judgment development to NCLEX performance.
- Launch AI initiatives in controlled environments before scaling and use measurable outcomes to justify broader investment.
- Proactively consider, develop and communicate acceptable use policies. 57% of universities now consider AI a strategic priority but in direct contrast, less than 40% have a formal acceptable-use policy.
- Keep humanity at the center. AI should support cultivating critical human skills that we will always need in nursing: empathy, critical thinking, and judgment.
Technology Doesn’t Guarantee Transformation – We Do
AI gives us the ability to create learning environments that are more responsive, personalized, and effective than ever before. But technology alone can’t guarantee transformation. True, successful change requires strategic leadership with a focus on ethics, equity, and collaboration to ensure AI strengthens nursing education and benefits our patients.
About Kelly J. Dries, PhD, RN
Kelly J. Dries, PhD, RN, is a transformational nurse educator and leader with over 29 years of experience. A former floor nurse, nursing faculty, and Dean of Nursing, she now serves as Director of Nursing Program Success at Wolters Kluwer, where she brings strategic vision and innovation to academic program development. Dr. Dries has a proven track record of leading diverse nursing programs, optimizing operations, and fostering inclusive, high-impact learning environments.
