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AI Foundations for Medical Education

Introduction

Welcome to AI Foundations for Medical Education. This 2026 collection of orientation modules is designed for medical educators seeking a practical introduction to generative AI in education and practice. Curated for busy faculty, it provides a concise, tier-one foundation for undergraduate medical education, with focused modules and selected key resources for further exploration.

Given the complexity and rapid evolution of AI, this resource is not intended to be comprehensive, but rather to highlight essential concepts, capabilities, and limitations. It is intended primarily for academic contexts rather than clinical competency development. Additional tiers will be added over time to support more advanced learning. This resource will be reviewed and updated annually to reflect the evolving role of AI in medicine and medical education.

Modules

  1. Introduction to AI in Medical Education and Medicine
  2. Understanding Generative AI and Large Language Models
  3. Responsible Use of AI in Medical Education
    Coming Soon!
  1. Selecting your AI Toolset
  2. Interacting with AI - Prompts and Process
  3. Evaluating AI Output - Applying Critical Thinking

Each module is broken into sections to avoid information overload and should take less than 15 minutes to review. Each module will also contain additional resources for further exploration.

Learning Objectives

Upon completion of these modules, medical educators will be able to:

  • Communicate an informed awareness of AI’s evolving role in medicine and medical education, and reflect on how it intersects with personal values, institutional policies and future practices.
  • Analyze the capabilities and limitations of generative AI and large language models to support informed, ethical and critical use in health professions education.
  • Apply principles of responsible and ethical AI use in medical education, including considerations related to academic integrity, bias, privacy and institutional policy.
  • Compare and evaluate generative AI tools based on their features, alignment with institutional policies and suitability for educational contexts.
  • Construct effective prompts to guide AI tools in supporting teaching, learning and professional tasks.
  • Critically assess generative AI outputs using structured evaluation frameworks to ensure factual accuracy and academic integrity.

Authors

  • Lise McCoy, EdD
    Director of Faculty Development
    New York Institute of Technology College of Osteopathic Medicine
  • Steve Garwood, EdD
    Director of Faculty Development
    Rowan-Virtua School of Osteopathic Medicine

Note: The text and graphics in these modules were co-developed with the assistance of generative AI tools such as OpenAI’s ChatGPT, Google’s Gemini and NotebookLM and Microsoft’s CoPilot, drawing on the indicated reference materials. The materials were then edited for relevance and accuracy.