Navigating AI in Health Professions Education: A Framework to Prosper, Prepare, and Protect

Artificial intelligence (AI) has moved quickly from novelty to an everyday tool in education. Across MD, DO, NP, and PA programs, educators are exploring how to harness AI’s potential. In medicine, where clinical decision-making, patient safety, and professional judgment are paramount, the stakes are especially high. Educators have moved on from asking whether AI will influence learning to how we will approach its implementation and the impacts for the next generation of clinicians. 

Aquifer’s team agrees and believes the question is not whether to adopt AI, but how to do so responsibly.

To guide this work, we look to a widely cited framework from the Brookings Institution¹—Prosper, Prepare, and Protect—and apply it specifically to the needs of health professions education.

How AI Is Transforming Health Professions Education

AI is already reshaping how learners engage with content, practice clinical skills, and receive feedback.

Research shows that AI-driven tools can:

• Personalize learning pathways

• Improve diagnostic accuracy

• Increase student engagement

Recent studies and papers demonstrate that AI can support more adaptive, individualized learning and improve performance in clinical education settings.² At the same time, organizations like the American Medical Association highlight AI’s role in enabling “precision education,” tailoring instruction to individual learners.³

For MD and DO programs, this may mean enhanced diagnostic reasoning support during clerkships. For NP and PA programs, AI can help reinforce clinical decision-making, patient communication, and readiness for practice.

But with this opportunity comes responsibility.

Prosper: Expanding Access and Enhancing Learning

The Brookings Institution framework conceptualizes “Prosper” as leveraging AI to drive innovation, transform teaching and learning, and improve outcomes.¹ One of the most common concerns among educators is whether AI could shortcut learning or undermine critical thinking. Responsible use of AI in education should do the opposite. In health professions education, this translates to expanding access to high-quality clinical learning while enhancing how students engage with content.

AI-enabled tools can help learners:

• Identify knowledge gaps earlier

• Practice clinical reasoning in a safe environment

• Receive more timely and personalized feedback

These capabilities are especially important as programs scale and faculty resources are stretched. Used thoughtfully—and co-created with educators, students, and communities—AI can help students practice more, reflect more, and learn more consistently.

At Aquifer, we see the greatest opportunity when AI is grounded in an authentic clinical context to support learners as they work through real-world scenarios, not abstract concepts.

Learn more about how Aquifer extends the reach of faculty expertise through our AI offerings. 

Prepare: Building AI-Ready Educators and Clinicians

Within the Brookings Institution model, “Prepare” emphasizes equipping individuals with the skills needed to thrive alongside AI.¹ Sitting in on a generative AI workshop at AMA’s ChangeMedEd in fall 2025, it was clear that there are myriad ways teachers can leverage AI to help them plan. For example:

• Prompts such as “summarize my presentation and tell me what you think are the learning objectives” can help educators reflect on their plans and adjust to more deeply or clearly target objectives for a class.

• See what questions might come up after a presentation, in a situation, etc. by giving AI a scenario or a slide deck and having it ask the toughest questions it can think of that someone might ask.

But simply giving educators a list of prompts and scenarios isn’t enough. 

Faculty are navigating the changing landscape while balancing clinical care, teaching, and administrative responsibilities. Utilizing carefully crafted tools that provide students detailed feedback on clinical reasoning is one way to support educators, allowing them to focus on higher-level mentorship, discussion, and professional formation. Furthermore, AI assistants can help faculty find relevant resources, from virtual cases to teaching strategies and more. It’s up to companies and programs to create and select relevant tools accordingly.

On the flip side, the clinicians graduating today will practice in a healthcare system increasingly shaped by AI—from clinical decision support to imaging analysis to workflow automation and AI notetaking. 

Research highlights the need for structured AI literacy and training across the learning continuum. Educators can help students prepare by integrating opportunities to:

• Critically evaluate AI-generated information

• Understand limitations, bias, and uncertainty

• Use AI tools as decision-support, not decision-makers

• Reflect on ethical and professional implications

Preparing learners for this future requires intentional curriculum design to ensure AI is integrated in ways that reinforce, rather than replace, clinical reasoning.

Protect: Safeguarding Learning and Clinical Judgement 

The third pillar of the Brookings Institution framework, “Protect,” focuses on safeguards (such as those for privacy, well being, and development) and mitigating risks.¹

In health professions education, risks such as bias, misuse, and unintended consequences are especially significant. Emerging research⁴ warns that overreliance on AI may:

• Reduce independent critical thinking

• Diminish active learning

• Introduce bias into clinical decision-making

As for safeguards, the importance of trust between educators, students, and ultimately, patients is fundamental. 

In a recent episode of Your Undivided Attention, a podcast from the Center for Humane Technology, Daniel Barcay⁵ and Rebecca Winthrop⁶ noted:

“Trust in the classroom is such a precious commodity. What causes everyone to open up, to actually learn, to actually track each other…to listen to take feedback, to engage, to pay attention to care. Trust is something you don't miss until it's gone.”

That trust is not only vital for the relationships within a learning environment, but also for educators and students in relation to the tools they are using, and for clinicians as they work with patients. 

Educators need to understand how AI systems work, what information they rely on, and where their limitations lie. Students need similar clarity so they can learn to evaluate AI outputs critically rather than accepting them uncritically. Together, they need to keep their patients at the center of their learning and practice.

Commitments, like Aquifer’s AI Transparency Statement, help ensure AI not only protects students’ data and keeps humans in the loop, but supports learning in ways aligned with the core mission of health professions education: preparing thoughtful clinicians that focus on person-centered care.

Aquifer’s Perspective: AI + Clinical Reasoning, Not AI Instead of It

Health professions education has always evolved alongside advances in medicine and science–from new diagnostic technologies to new models of patient care. AI is simply the next chapter. 

But its impact will depend on the choices educators make today. The institutions that succeed will not be those that adopt AI the fastest, but those that adopt it most intentionally. Prioritizing transparency, responsible design and integration, and AI literacy—for students and educators alike—is how schools can ensure that AI strengthens rather than weakens the educational process and the development of future clinicians. 

That’s why our approach focuses on:

• Case-based learning that mirrors real patient encounters

• Structured development of clinical reasoning skills

• Formative assessment and feedback that support students in the moment

• Analytics that give educators actionable insight

By grounding AI within authentic clinical experiences, we ensure that technology strengthens, rather than substitutes, the learning process.

The goal is not to replace educators or clinical judgment. If implemented thoughtfully, AI can help educators do what they have always aimed to do: prepare clinicians who think carefully, reason clinically, and place patients at the center of care. 

¹ Winthrop R, Dusenbury C, Hinton R, McGivney E. A new direction for students in an AI world: prosper, prepare, protect. Brookings Institution. Published January 17, 2024. Accessed March 20, 2026. Available at: https://www.brookings.edu/articles/a-new-direction-for-students-in-an-ai-world-prosper-prepare-protect/

² Pillay R. The AI revolution in medical education. Birmingham, AL: University of Alabama at Birmingham; 2024. White paper.
Sriram A, Ramachandran K, Krishnamoorthy S. Artificial intelligence in medical education: transforming learning and practice. Cureus. 2025 Mar 19;17(3):e80852. doi:10.7759/cureus.80852. PMID:40255837; PMCID:PMC12007958.

³ American Medical Association. Augmented intelligence in medicine. Updated March 13, 2026. Accessed March 20, 2026. https://www.ama-assn.org/practice-management/digital-health/augmented-intelligence-medicine. 

⁴ Naqvi WM, Ganjoo R, Rowe M, Pashine AA, Mishra GV. Critical thinking in the age of generative AI: implications for health sciences education. Front Artif Intell. 2025;8:1571527. doi:10.3389/frai.2025.1571527.
BMJ Group. Overreliance on AI risks eroding new and future doctors’ critical thinking while reinforcing existing bias. BMJ Evidence Based Medicine. News release. December 2, 2025. Accessed March 20, 2026. Available at: https://bmjgroup.com/overreliance-on-ai-risks-eroding-new-and-future-doctors-critical-thinking-while-reinforcing-existing-bias/

⁵ Daniel Barcay is a senior fellow at the Center for Humane Technology. 

⁶ Rebecca Winthrop is a senior fellow and the director of the Center for Universal Education at the Brookings Institution.