Artificial intelligence (AI) is reshaping how clinicians document, diagnose and deliver care. As these tools become more common in practice, faculty face a critical challenge: How do we integrate AI into health care education without losing what makes it human?
At the 2025 Evidence In Motion (EIM) Faculty Symposium, Dr. Dipu Patel DMSc, MPAS, PA-C, ABAIM, delivered a session designed to help faculty and institutional leaders answer that question.
A nationally recognized expert in artificial intelligence and digital health, Patel is vice chair for innovation and professor in the University of Pittsburgh's DMSc program, and president of the Physician Assistant Education Association.
Her session, "The GenAI in the Classroom," focused on practical, ethical and scalable ways faculty can use AI to enhance teaching while preserving the empathy, reasoning and adaptability that define great clinicians.
Why AI Fluency Is Essential in Care Education
Generative AI models such as ChatGPT, Gemini and Perplexity are already being used to support case-based learning, clinical reasoning, student remediation and formative assessments.
Yet many institutions are just beginning to explore how to integrate these tools into formal curriculum.
Patel urged academic leaders to view AI fluency as a core competency, not a siloed skill.
Key considerations:
- Make digital literacy a curriculum-wide priority
- Establish policy-level guidance on AI use
- Provide faculty support for revising rubrics and assessments
- Address bias and access issues in AI-generated content
"You're not preparing students for graduation," Patel said. "You're preparing them for 40-year careers that will rely on these tools."
Four Practical Ways Faculty Can Use AI in Health Care Education
Patel outlined four high-impact teaching applications for generative AI that can be implemented now, even without major system overhauls.
- AI as Clinical Tutor
- Students can use AI tools like Gemini to simulate patient interviews, practice history-taking and improve clinical decision-making.
- Pro tip: Start with the diagnosis and have students build the history through iterative prompts and SOAP note construction.
- Writing and Editing Support
- Students can be tasked with evaluating the accuracy of AI-generated responses by highlighting reliable and unreliable content.
- Pro tip: Use this method to strengthen source literacy, especially in first-year or preclinical courses.
- Active Learning and Remediation
- Faculty can prompt AI to generate customized study plans or learning activities tied to missed objectives.
- Pro tip: Integrate AI tools into one assignment per course to support differentiated instruction.
- AI in Assessment and Rubric Alignment
- AI can be used to generate feedback or score student work when paired with faculty-approved rubrics.
- Pro tip: If AI is used in grading, be transparent and ensure final review remains with faculty.
Risks of Using AI in Health Care Education: Bias, Misinformation and More
Patel emphasized that while AI can support learning, it can also reinforce harmful biases or inaccuracies if used uncritically.
- Bias: AI models trained on internet data may reproduce racial, gender, or cultural disparities in output.
- Misinformation: Tools can hallucinate citations or present inaccurate clinical details.
- Overreliance: Students may lean too heavily on AI instead of developing their own reasoning.
She recommended training students to verify AI-generated output, cite sources properly and reflect on when and why they use these tools.
Building AI Capacity in Health Care Programs Without Losing Clinical Focus
"AI is not here to replace the human elements of care," Patel said. "It's here to elevate them if we use it wisely."
She forecasts a shift away from standardized multiple-choice testing and toward more human-facing evaluations, such as oral exams, skills demonstrations and real-time clinical decision-making.
Faculty, she said, should focus on the irreplaceable parts of clinical education: empathy, ethical reasoning and communication.
"We're shifting from memorization to meaning-making," she said. "Students now need to question not just their preceptors, but the models themselves."
How Higher Ed Leaders Can Start Integrating AI in Health Care Programs
For department chairs, deans and academic directors, Patel recommended three starting points:
- Audit curriculum for AI-relevant outcomes
- Identify where AI tools can enhance or assess competencies already in place.
- Pilot AI-informed teaching in one course or assignment
- Allow early adopters to explore applications in SOAP note revisions, case-based discussions or formative assessment.
- Create a development track focused on AI fluency
- Offer workshops or peer-led sessions to build confidence in prompt writing, bias detection and instructional design.
Key Takeaways: AI in Health Care Education for the Long Term
Generative AI is no longer a future concern. It is already reshaping health care education, and academic leaders have a pivotal opportunity to guide its responsible, effective use in the classroom and beyond.
According to Patel, AI should not be viewed as a shortcut but as a support system that complements the human insight at the heart of clinical care.
"The most important skills for the future," she said, "will be adaptability and flexible thinking paired with curiosity."
Health care educators who lead with those traits today will be best positioned to train the clinicians of tomorrow.