Fragmented delivery
Different stacks and duplicated work make it harder to carry a successful use case into another business unit.
STRATEGY / OPERATING MODEL
Make AI a capability. Not a collection of pilots.
Bring people, process, and infrastructure into one operating model. Give business teams a shared foundation and clear responsibility for the AI they put into use.
From strategic direction to accountable delivery
01Set the direction
Executive mandate
Leadership defines the priorities, investment, and decisions the CoE is accountable for.
02Build the shared foundation
AI CENTER OF EXCELLENCE
- Policies & standardsDefine the boundaries.
- Shared platformReuse the foundation.
- Evaluation methodsTest before release.
- Skills & enablementEquip the teams.
03Deliver in each domain
Business teams
Own the use case and outcome.
Engineering teams
Build within shared standards.
Operational owners
Run, monitor, and improve.
FROM EXPERIMENTATION TO OPERATIONS
A working pilot is not an operating model.
When teams choose models, rebuild evaluations, and connect data independently, each new use case creates another set of decisions. A CoE makes the shared decisions explicit so delivery does not have to start again.
Unclear responsibility
An agent needs an owner for its access, operating cost, evaluation, and response when something goes wrong.
Controls added too late
Release criteria, data boundaries, and approval paths belong in the design, not in a review after deployment.
RESEARCH CONTEXT / 2025–2026
The gap is organizational, not only technical.
Separate surveys, populations, and reporting periods. These findings describe the cited respondents, not SDEN clients or results. They are context, not a combined benchmark.
Scaling was still ahead
In McKinsey's 2025 survey, nearly two-thirds of respondents said their organizations had not started scaling AI across the enterprise.
McKinsey · State of AI 2025 · p. 2 ↗Security and risk constrain scale
Cited security and risk concerns as an obstacle to fully scaled agentic AI in the McKinsey 2025 survey reproduced by Stanford.
Stanford · AI Index 2026 · fig. 3.3.10 ↗Mature agent governance is uncommon
Of respondents in Deloitte's multicountry survey said their organizations had a mature governance model for agentic AI.
Deloitte · State of AI 2026 ↗SHARED STANDARDS / DISTRIBUTED DELIVERY
Centralize the foundation. Keep expertise close to the work.
The CoE maintains common standards, reusable assets, and platform decisions. Domain teams own their use cases and operational outcomes within those boundaries.
What are we investing in, and who owns it?
Establish a portfolio and an accountable operating model.
- Use-case priorities and ownership
- Investment and capacity decisions
- Evidence of operational value
How do we move from pilots to dependable systems?
Build with shared infrastructure and repeatable delivery standards.
- Reusable models, tools, and evaluations
- Controlled releases and rollback
- Visibility into quality and usage
Where does our data go, and who can act on it?
Translate requirements into explicit boundaries and access decisions.
- Data and administrative boundaries
- Model and tool permissions
- Proportionate audit evidence
A CAPABILITY YOU CAN OPERATE
Leave with more than a strategy document.
Scope the engagement around concrete artifacts and responsibilities. The depth of implementation follows your maturity, constraints, and agreed mandate.
An agreed mandate
An accountable sponsor, decision rights, a use-case portfolio, and a way to prioritize investment.
A delivery standard
Reusable evaluation criteria, approval gates, operational handover, and change-management procedures.
A reference architecture
Defined data flows, model access, identity boundaries, observability, and deployment choices.
A team ready to take ownership
Role-specific enablement, documented systems, and a practical plan for ongoing operation.
START WITH YOUR REQUIREMENTS
Define what your organization needs to control.
Start with your workloads, data constraints, and existing architecture. Establish the scope before selecting the tools.