People Management for AI: Building High-Velocity AI Teams

Only a couple of years ago, most AI, ML, and data work sat squarely with data scientists. A few teams ran more advanced combinations of roles and services, but the default was still a data scientist managing models in notebooks.

That model no longer holds. Shipping AI/ML to production quickly, efficiently, and at scale requires a cross-functional, high-performing team — multiple roles, each owning their slice of ML infrastructure and MLOps.

This flipbook shows how ML infrastructure, people, and processes lock together to enable MLOps. It is built for managers and directors who are standing up — or rebuilding — a robust AI/ML practice with high-velocity AI teams, drawing on the Provectus AI team’s experience across customers at every stage of the AI journey.