Health education
AI in medical education: a faculty’s playbook for the next five years
The decision
The decision every medical school will make before 2027
Generative AI did not ask permission to enter your curriculum — students brought it. The decision in front of academic leadership is no longer whether to have a position, but which one, and the next accreditation cycle will ask for it in writing. The schools that do this well will treat it as a curriculum design problem with four distinct layers, not a single ban-or-allow policy.
The playbook
Four layers, not one policy
- Assessment: when a written exam can be answered by a model, move the weight to what cannot be faked — reasoning out loud, in conversation, observed.
- Teaching: stop teaching recall AI does in seconds; teach the judgment of when the AI is wrong.
- Content: let faculty use AI to build teaching material and simulations from their own sources — the upside few schools have claimed yet.
- Accreditation: document the position now, so the next review finds a deliberate policy rather than a scramble.
The technology that made the written exam easy to game is also the one that makes the harder, better assessment finally scalable.
Next step
From playbook to implementation
The content and assessment layers are where a school can act this year without waiting on policy: faculty-authored AI simulations that train and assess the reasoning a written exam no longer can. It is the most concrete first move, and the easiest to show a board.
For universities & faculties · Free guide
Free: the Education 4.0 Guide
Higher education in the post-ChatGPT era — the methodologies that work and how to use AI as the answer.
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