When to Let Students Use AI—and When to Say No

AI can be a valuable tool for teaching and learning. It is also becoming ubiquitous in the workplace. But it brings risks if not used correctly and in the appropriate context. Students who outsource their thinking to AI tools before mastering core skills will struggle to think independently and evaluate information critically. These same skills are also needed for effective AI use after graduation. Like a conductor who tries to lead an orchestra before knowing how to play an instrument, a student needs a strong foundation to be able to leverage AI's potential ethically and effectively. In this workshop we'll focus on a scaffolded framework for managing AI in higher-education courses. We'll explain how instructors can decide if, when, and how to deploy AI tools in their teaching. We'll discuss appropriate scaffolding and how it applies across the spectrum—from no-use or restricted-use zones to sophisticated applications at the capstone level. You'll leave with a concrete decision checklist, an approach to integrating AI into your teaching, and ready-to-use AI guidance for students. The goal is teaching that supports foundational skills and prepares graduates to command AI rather than be commanded by it.