AI Where It's Hardest: Lessons from Building in Regulated Healthcare (Pharma, Medtech, Healthtech)
About this session
Most AI conversations happen in industries where speed matters more than scrutiny. Healthcare and Pharma / MedTech are the opposite: every model, every chatbot, every automated decision has to survive regulatory review, clinical accountability, and patient trust before it ever reaches a real user. In this session, Sam Kwan shares firsthand experience building and deploying AI inside pharmaceutical marketing and commercial operations, including a machine learning model that changed how a global pharma company allocated its field force, and one of the first PAAB-approved AI chatbots in Canada. Sam breaks down what actually changes when you build AI for a regulated industry: the tradeoffs, the stakeholders you don't expect, and the discipline it takes to move from prototype to something that survives legal, compliance, and medical review. For builders working in any high-stakes or regulated space, this session offers a grounded, practitioner's view of what it takes to ship.
Speaker
Key takeaways
- How AI projects change shape once compliance, legal, and clinical stakeholders enter the room, and how to plan for that from day one
- What made a PAAB-approved HCP chatbot different from a typical AI chatbot build, and what that process revealed about trust and adoption in healthcare
- A practical framework for evaluating whether an AI idea is ready for a regulated environment, or needs more groundwork first