Why AI that works in the lab often fails in production — and what actually fixes it

Why AI that works in the lab often fails in production — and what actually fixes it

Capital One shows AI's core problem: models work in labs but fail in production due to real-world constraints. Fix: R&D bridging foundational research to applied work with honest metrics. For CTOs, value is scaling prototypes via cross-functional teams and rapid learning—not latest models.