Every week brings new requests to use this or that AI tool, and most of us are deciding case by case with no shared logic. In this hands-on session I'll share a decision tree I built to route and evaluate AI tool requests at the college level, then show you how to use AI itself to turn your own logic into an interactive tool. We'll work through the real questions: data sensitivity, vendor review, approved alternatives, and when to escalate. You'll leave with a working first draft you built in the room and can adapt to your institution's rules.

Learning Objectives:

• The core questions every AI tool request should pass through before approval
• How to map data sensitivity and vendor review into simple routing logic
• How to use AI tools to turn that logic into an interactive decision tree