How Programs Can Use AI to Improve Student Outcomes

Smartphones dominated the mobile market just a few years after the release of the iPhone. At the same time, Google Glass was discontinued two separate times. HD streaming completely transformed the media landscape, while the 3D craze of the 2010s seemingly vanished overnight.

Technologies that endure are technologies with impact. You can “see” the changes they bring to popular culture and professional industries. They aren’t just about the novelty of the experience. They are about genuinely transforming (and hopefully improving) our lives.

AI and nursing are having a similar moment. AI tools are increasingly integrated into nursing practice, and nearly 30% of educators at every level are using AI in some capacity.^1,2

What’s more, the National League for Nursing recently published a toolkit for nursing programs and clinical partners to facilitate more effective AI integration. This level of adoption has a massive impact on healthcare and healthcare education — an impact you can see.

This level of adoption has a massive impact on healthcare and healthcare education — an impact you can see.

What will it look like? How should we expect nursing education to start evolving both inside and outside the classroom? This is a practical look at how generative AI will reshape the industry. In some cases, it’s already happening.

AI Inside the Classroom

Is there a student in need of intervention? Does any specific concept need re-teaching? Is the curriculum challenging for everyone? Where are the opportunities for multimodal learning?

Inside the classroom, a nurse educator juggles many priorities. That’s why the industry is so excited about the potential for AI integration. It won't just make these things easier. It will raise the bar and make new things possible.

How? By improving what already works and making new methods of teaching and learning a day-to-day reality.

• Hyperpersonalized learning paths. Instant feedback. On-the-spot differentiation. AI makes new levels of personalization possible for nursing education. This level of differentiation is particularly relevant in nursing, where learners vary widely in experience and learning styles.³
• More opportunities for student engagement. Traditional coursework and clinical experiences don’t always meet the needs of every aspiring nurse. Systems like Claire AI^® can generate a variety of learning tools, including flashcards, podcasts, visual aids, and mnemonics. Claire AI makes it easier for students to engage with NCLEX-aligned content on their own terms and create deeper, more meaningful connections.
• Real-time performance analysis. In surveys, more than 17% of nursing students report receiving delayed or confusing feedback.⁴ Other research shows that  immediate grading and analysis are simply better than delayed feedback.⁵ However, it wasn’t until recently that such immediate feedback and reporting were even possible. Expert-validated AI can provide trusted analysis in an instant.³ It naturally improves performance, and it empowers faculty to differentiate learning on a new level.
• Quicker identification of at-risk students. When it comes to any intervention, time is precious. The sooner you can identify at-risk students, the sooner you can offer remediation. AI-enhanced identification is lightning fast and extremely accurate,, meaning fewer aspiring nurses fall through the cracks.⁶

THE AI IMPACT: AI delivers real-time, personalized support and accelerates the identification of at-risk students. This improves retention and creates measurable gains in performance. Continuous feedback and adaptive learning tools increase engagement and keep students focused on NCLEX readiness. For faculty, instant insights reduce total workload and enable more focused, high-impact teaching across each cohort.

AI Outside the Classroom

Of course, the impacts of AI go well beyond the classroom. Broad-scope LLMs are accessible, but too unreliable to be useful. However, purpose-built AI systems like Claire AI are embedded across the entire education journey. They provide trustworthy support to students and faculty no matter the time or place, improving outcomes and creating space for more hands-on instruction.

How? By being an accessible and powerful tool for every student and every educator.

• 24-hour feedback drawn from evidence-based content. Did you know students who feel comfortable seeking feedback make better transitions to the clinical setting?⁷ Quality feedback and questioning are integral to nursing education, but it's also an overwhelming responsibility for faculty. Claire AI makes it immediate and always available.
• Improved competencies thanks to intelligent tutoring. Intelligent tutoring is like having your own academic coach. Need personalized study aids? Need targeted feedback? Need a mnemonic device for that one thing you can’t remember? With Claire AI, every student gets a powerful study aid suited to their needs.
• More accessible instructors and administrators. Increasing faculty workloads are limiting when instructors can be available for students, and that has a big impact on overall performance.⁸ AI systems with a focus on faculty efficiency, such as Claire AI, free up the time and space needed for educators to stay fully engaged.
• Increased emphasis on clinical decision support. Nursing education has never ended at the classroom, but that’s especially true now. “Book knowledge” is much less useful when information and diagnostics are readily available. Tomorrow’s nurses will need to understand predictive analysis and the “why” behind the data in front of them.⁹

THE AI IMPACT: Always-available AI support extends learning beyond the classroom, boosting student confidence and increasing overall retention. Personalized tutoring and instant, trustworthy feedback sustain student engagement, and that means stronger academic performance and smoother transitions to clinical practice. At the program level, these outcomes are the backbone of enrollment growth.

Not the Future — the Present

The academic impacts aren’t destined for some distant future. For better or for worse, many of them are happening right now.

Such a large shift for such a risk-averse industry inevitably presents a series of challenges, and those challenges are only overcome by purposeful planning and guided decision making. Those challenges are outweighed by the potential benefits of AI integration, and many of those benefits are available today — no wait needed.

These evolutions aren’t waiting for anyone. Every corner of the healthcare industry is rushing to build their version of an AI-powered future. Before long, healthcare education will be divided into two camps: the ones that evolved alongside the industry and the ones that got left behind.

It isn’t a matter of IF. It’s a matter of WHEN.

Staying Ahead of the AI Evolution With ATI

ATI isn’t just part of the AI space in nursing education. ATI is a leader and pioneer in the industry.

Our suite of AI resources is powered by a first-of-its-kind AI engine and an extensive library of evidence-backed content. Claire AI support is embedded into Custom Assessment Builder as well as the Engage^® Series and Launch: Nursing Academic Readiness^®.

This isn’t just adding an off-the-shelf LLM to your educational process. This is a fully integrated, fully supported and vetted AI system designed specifically for nursing education.

Programs need to stay ahead of the AI evolution. It brings enhancements and innovations to the educational process, but it’s also burdened by challenges. Ethics. Reliance. Trustworthy content. These aren’t easy problems to solve, especially if your program is already falling behind.

References

1. Wei Q, Pan S, Liu X, Hong M, Nong C, Zhang W. The integration of AI in nursing: addressing current applications, challenges, and future directions. Frontiers in Medicine. 2025;12:1545420. doi: 10.3389/fmed.2025.1545420
2. Microsoft Corporation. AI in Education Report 2025.  https://cdn-dynmedia-1.microsoft.com/is/content/microsoftcorp/microsoft/bade/documents/products-and-services/en-us/education/2025-Microsoft-AI-in-Education-Report.pdf
3. Cucci F, Marasciulo D, Romani M, Soldano G, Cascio D, De Nunzio G, et al. The contribution of artificial intelligence in nursing education: a scoping review of the literature. Nursing Reports. 2025;15(8):283. doi: 10.3390/nursrep15080283
   
4. Rathobei LM, Dube MB. Nursing students' perceptions regarding feedback from their educators in a selected higher education institution in KwaZulu-Natal province, South Africa. African Journal of Health Professions Education. 2021;13(4):271-275. doi: 10.7196/AJHPE.2021.v13i4.1111
5. Fyfe ER, de Leeuw JR, Carvalho PF, Goldstone RL, Sherman J, Admiraal D, et al. ManyClasses 1: assessing the generalizable effect of immediate feedback versus delayed feedback across many college classes. Advances in Methods and Practice in Psychological Science 2021;4(3):1-24. doi: 10.1177/25152459211027575
6. Zamani M, Asadi H, Gholipour M, et al. Identifying at‑risk students for early intervention—A probabilistic machine learning approach. Applied Sciences. 2023;13(6):3869. doi: 10.3390/app13063869
7. Liang S, Xue M, Tang N, Ban H, Qin Y, Chen Y. The mediating role of feedback-seeking behavior in the relationship between self-efficacy and transition shock of nursing interns: a cross-sectional study. Frontiers in Medicine. 2025;12:1635755. doi: 10.3389/fmed.2025.1635755
8. Ateeq A. Impact of faculty workload on mental health and student success: a comprehensive review. In: AlDhaen E, Braganza A, Hamdan A, Chen W, editors. Business Sustainability With Artificial Intelligence (AI): Challenges and Opportunities. Studies in Systems, Decision and Control. Vol 568. Springer; 2025. doi:10.1007/978-3-031-71526-6_67
   
9. Atalla ADG, Mousa MAE‑G, Abou Hashish EA, Elseesy NAM, Mohamed AIAK, Mohamed SMS. Embracing artificial intelligence in nursing: exploring the relationship between AI‑related attitudes, creative self‑efficacy, and clinical reasoning competency among nurses. BMC Nursing. 2025;24(1):661. doi:10.1186/s12912‑025‑03306‑3
10. Yoo H, Lin Y, Attenweiler R, Hodge KJ, Miller JE, Phillips BC. Effectiveness of AI-Assisted Item Writing in Nursing Education: A Mixed-Methods Evaluation. Journal of Professional Nursing. 2026;67:284–293. https://doi.org/10.1016/j.profnurs.2026.09.001