One of the most challenging parts of AI adoption is finding trusted use cases. Most people fall into three camps regarding AI: true believers, hard skeptics, and the crucial "maybe" group, stuck in the middle. The "maybes" aren't against AI—they just haven't seen a use case that clicks.

Through the open-source project PETE (Patient Engagement Training Experience), I'll show you exactly how AI transforms medical education by creating realistic patient interactions that would be impossible to replicate at scale otherwise. PETE demonstrates how to build AI applications that enhance human capabilities rather than compete with them. By creating realistic patient simulation scenarios for medical students learning motivational interviewing techniques, this project showcases AI adoption that's both practical and ethical.

This talk offers more than just information; it’s a roadmap for practical AI integration and adoption. I'll walk through the technical implementation using Ollama and Django, but more importantly, the decision-making framework that led to this use case. You'll learn how to identify AI opportunities that build trust rather than erode it, implement guardrails that matter, and create value propositions that resonate with both technical teams and stakeholders.