HealthJuly 07, 2026

How to use AI to build clinical judgment in Nursing Education

By: Judith W. Herrman

Key Takeaways

  • AI can enhance learning, but only when guided by evidence-based teaching strategies that promote critical thinking.
  • Without structure, AI use can lead to superficial learning and weaken clinical judgment development.
  • Nurse educators play a key role in teaching students to evaluate, critique, and apply AI responsibly.
AI is already embedded in nursing education — but its value depends on how it’s used. Learn how faculty can apply brain-based strategies to ensure AI strengthens clinical judgment, not shortcuts learning.

Artificial intelligence is already part of how students learn.

They’re using it to generate study guides, create practice questions, and even draft assignments. On the surface, this looks like efficiency. But many faculty are noticing something deeper: when AI does the work, students may stop doing the thinking.

That creates a real risk in nursing education. Because success in practice isn’t about recalling steps — it’s about making decisions in complex, unpredictable situations. Clinical judgment is built through thinking, not shortcuts.

This is where the conversation around AI needs to shift. It’s not about whether students should use it. It’s about how we ensure AI strengthens learning instead of replacing it.

What challenges does using AI in nursing education create for developing clinical judgment?

AI is designed to give fast, polished answers. But nursing students don’t need faster answers — they need stronger reasoning.

When learning activities can be completed by AI, students may engage less deeply with the material. Over time, this can lead to:

  • Superficial understanding instead of durable learning
  • Reduced ability to apply knowledge in new situations
  • Less confidence when faced with real patient decisions

The solution isn’t to remove AI — it’s to redesign learning so that AI becomes part of the thinking process, not a substitute for it.

Essentially, when lesson plans build on the capabilities of AI with evidence-based strategies, thinking and clinical judgment are fostered, rather than replaced.  
Judith W. Herrman PhD, RN, CNE, ANEF, FAAN

How can AI be used to build clinical judgment in nursing education?

When used intentionally, AI is helping nursing educators teach more effectively, and students to learn more deeply, but only when it is grounded in the science of how students learn.

The most effective approaches combine AI with brain-based learning strategies that require students to retrieve, apply, and reflect on knowledge.

In practice, this means shifting AI from an answer generator to a thinking partner, designing activities that prioritize retrieval over passive review, and introducing variation that reflects the complexity of real clinical settings. It also includes using AI to support targeted remediation, helping students identify gaps, reflect on performance, and focus their efforts where it matters most.

What does effective AI use look like in nursing education?

To be effective, AI must be paired with clear expectations and guardrails. Faculty play a central role in teaching students how to:

  • Recognize bias or inaccuracies in AI-generated content.
  • Validate information using evidence-based sources.
  • Use AI outputs as inputs for critical thinking — not final answers.

Just as importantly, students need to understand that AI is part of their future practice. Healthcare is already integrating AI into clinical decision support, documentation, and patient engagement. Preparing students to use these tools responsibly is no longer optional — it’s essential.

The most effective faculty are not choosing between AI and human connection. They are integrating both — using AI to support learning while keeping the focus on the person behind the care.

Moving forward: designing learning that builds real readiness

Though new AI-powered tools – such as Lippincott CoursePoint+’s Faculty Assistant and Nursing Tutor, powered by Expert AI – are taking learning to a new level, this shift requires more than getting familiar with the technology. It requires a new approach to how we design teaching, assessment, and student engagement.

We continue to search for ways to help educators intentionally design learning experiences where:

  • Students think deeply and are pushed to ask and answer the “why.”
  • Students interact with AI in creative ways that make learning stick.
  • Knowledge transfers into practice, creating nurses who are ready to enter clinicals confidently.

Download the full report, “Leveraging the power of AI to foster clinical judgment."

For a deeper look at how to align AI use with brain-based learning principles — and practical classroom strategies you can apply across lecture, lab, and clinical settings — download the full Trends & Insights paper: Leveraging the power of AI to foster clinical judgment.

Judith W. Herrman
PhD, RN, CNE, ANEF, FAAN
Judith W. Herrman, PhD, RN, CNE, ANEF, FAAN, is a nurse, educator, and researcher interested in teaching and learning across the lifespan, nursing education, and health promotion. Judy has published over 100 publications and speaks nationally and internationally. As a Senior Clinical Content Specialist-Nursing with Wolters Kluwer, Judy works with nursing schools and customers to explore brain science and biology of learning, creative teaching strategies, accreditation, NCLEX® success, testing, remediation, curriculum design, team building, and other topics revolving around enhancing nursing education and student learning. Judy published the 4th Edition of Creative Teaching Strategies for the Nurse Educator in November 2024. 
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