From Experiment to Engine: Building an Enterprise AI Lab
Challenge
The AI Lab had a mandate but not a method. Ideas arrived from every direction — research projects, partner pitches, technology briefings — but nothing had a consistent path from concept to prototype. Promising work stalled before anyone could test whether it was worth building. Without a shared intake process or validation criteria, the lab risked becoming a collection of one-off experiments with no mechanism for scale.
Solution
Built the AI Lab framework from scratch — defining intake criteria, designing validation processes, and creating cross-functional sprint workflows powered by AI tools. Every idea that entered the system had a defined path: scoped, tested against business outcomes, and either advanced or killed quickly. Standardized Vellum agent sprints replaced months-long discovery cycles with structured 1-hour sessions. The lab became infrastructure for repeatable innovation instead of a venue for one-off experiments.
Results
Cut innovation discovery from 9 months to under an hour — a 480× acceleration. Launched 19 AI-driven prototypes in year one; 3 advanced to MVP development. Mapped $933M in validated innovation opportunity from 950 minutes of SME engagement. The lab moved from a concept to an operating system for organizational innovation.