The Enterprise AI Operating Model

Design four connected layers

Strategy sets the outcomes and investment boundaries. Portfolio management decides which opportunities deserve attention. Delivery squads turn selected opportunities into adopted products. Enabling functions make safe delivery repeatable through platforms, data access, architecture, and governance.

The layers need explicit interfaces. A squad needs to know how to obtain access, who can accept a risk, and how to request continued funding. Leadership needs evidence of impact and an honest account of uncertainty.

Make decision rights visible

Separate business decisions from implementation decisions. Business owners decide workflow policy and outcome trade-offs. Engineers decide technical approaches within agreed constraints. Security and governance owners define controls and review exceptions.

Create a short decision matrix for high-impact actions: approving a new data source, granting an agent write access, changing a model, or expanding to a new population. Each decision needs an owner and a path for escalation.

Fund learning and continued operation

A project-only funding model encourages teams to declare success at launch. Instead, distinguish funding for discovery, delivery, and product operation. Release larger commitments as evidence improves, and make stopping an unsupported idea a legitimate portfolio outcome.

Plan for evaluation, model changes, incident response, and user support. These costs belong in the business case from the start.

Build a center of enablement

A central team is most useful when it reduces repeated work. Provide reference architectures, evaluation tooling, reusable connectors, and clear approval routes. Let domain teams retain ownership of their workflows and outcomes.

Measure the enabling team by the safety and effectiveness of delivery across the organization—not by how many proposals pass through it.

Put the idea to work.

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