Enterprise AI
AI operating model
The structure of roles, processes, governance, and technology used to run AI across an organization.
Example
The operating model defines who funds, builds, approves, supports, and monitors AI products.
Why it matters
It helps AI work continue reliably beyond the team that built the first version.
You'll hear it
“Who maintains this after the pilot team moves on?”
Can you control it?
Sometimes
Sometimes. An organization can define or influence an AI operating model through its policies, processes, contracts, and product choices. Individual users may have fewer controls.
Common questions
- Is an operating model the same as the AI model?
- No. It describes how people and processes organize the work, not the prediction system itself.
- Must every organization use a central team?
- No. Responsibilities can be centralized, distributed or shared.
- Can unclear handoffs create gaps?
- Yes. Maintenance or incident response may be missed when teams assume someone else owns it.