The $17.7M Hiring Filter: What Enterprise AI Misses Without Outcome Data

About this session

Most enterprise AI can see the data behind a decision, but not the downstream outcome that reveals whether that decision actually worked. Without that feedback loop, AI risks scaling yesterday’s assumptions faster instead of helping the enterprise learn. I will show how connecting decisions, human judgment, actions, and business results across existing systems creates an outcome layer that makes AI more useful over time. Attendees will leave with a practical model for building human-approved, auditable workflows without replacing their existing stack or giving up control. If your AI roadmap is producing more copilots than measurable impact, this talk will show what is missing.