Across campuses, the loudest conversation about AI centers on “AI-proofing” assignments and policing cheating. Great teaching does not ban tools—it designs for what the tool makes possible. This session shares a practical blueprint for AI-powered flipped learning in which first exposure happens through a standards-aligned AI tutor, while class time is reclaimed for coached problem solving and authentic application. Participants will explore design patterns that cut across disciplines—digital twins that simulate lab conditions before physical experiments, historical decision rooms that enable students to interrogate sources through agentic roleplay, writing copilots that scaffold revision and feedback, and career-connected projects that pair learners with task-specific copilots to build and critique portfolio artifacts.Rather than report research, this session delivers actionable takeaways: a modular framework for integrating AI tutors safely and effectively, a responsible-use playbook with bias-check and human-in-the-loop guidelines, and a model for small pilot programs that track cost per successful learning outcome. Attendees will leave with concrete tools to move from compliance to creativity—designing AI interactions that are safe, measurable, and discipline-authentic, transforming AI from a threat into a catalyst for learning.
