Pharma / Life Sciences
AI in Regulated QA: What Actually Works, What Breaks
Most AI demos in regulated industries fall apart the moment a real QA reviewer touches them — hallucinated citations, no audit trail, no way to trace a decision back to source. A practitioner’s field report from building a production RAG-based QA copilot for pharma cold chain: the failure modes that killed the first three prototypes, the human-in-the-loop pattern that finally worked, and where AI belongs in compliance-critical workflows — and where it absolutely doesn’t.
45-min session or 60-min workshop
AI / ML Engineering
Human-in-the-Loop Isn’t a Safety Net: Designing It as Primary Architecture
Most teams bolt human-in-the-loop onto an AI system as a backstop for low model confidence. That’s the wrong frame. In high-stakes domains, HITL is the primary architecture and the AI is the assistant. A walk through a production system where the human is the decision-maker by design: the UX patterns that scale, the ones that turn reviewers into rubber-stampers, and audit trails that capture reasoning instead of just outputs.
30–40 min technical session
Executive / Leadership
First-Order AI: Why Most Enterprise AI Initiatives Plateau Before They Pay Off
Most organizations are doing first-order AI: bolt a model onto an existing workflow, declare victory, watch adoption stall. Second-order is product-aligned. Third-order is the whole picture — engineering org, risk posture, cost model, team structure. The Three Orders framework with examples from regulated industries, where staying at first-order isn’t just stalled ROI — it’s compliance debt. Leaders leave with a 90-day diagnostic for their own AI portfolio.
30-min strategic talk, panel-friendly