As enterprises mature self-service programs and embed AI into daily operations, Centers of Excellence (CoEs) face a sharper question: not just what they deliver, but what value they create. It’s no longer enough for a CoE to solely provide governance, onboarding, or community support. Executives want proof in measurable outcomes, tied directly to strategic priorities.
This isn’t a superficial ask. Self-service and AI programs demand sustained investment in platforms, people, and processes. Leadership now expects assurance that those investments are generating a return, not in abstract terms, but in hard business outcomes. That means every CoE must build a credible, repeatable business case.
The starting point is alignment. Too many CoEs try to measure everything and end up proving nothing. The point is not activity; it’s impact. That requires mapping CoE objectives directly to enterprise imperatives: mission statements, divisional goals, and C-suite strategies.
Once priorities are clear, the case becomes about evidence. Different stakeholders care about different dimensions of value: A CIO may look for efficiency gains in the tech stack, a CFO expects avoided spend and ROI, and a business unit VP needs proof of faster delivery or revenue impact. A strong CoE adapts its narrative to each.
If you can’t measure something, you can’t improve it. And if you can’t show it in terms the business cares about, you’ll struggle to win long-term support.
- Jon Tudor, Director of Business Architecture at Dataiku
In practice, three KPIs consistently prove a CoE’s value:
These measures reinforce each other. ROI without adoption looks like financial gymnastics. Adoption without process integration signals shallow engagement. Together, they show that the CoE is not just active, but effective.
Quantifying ROI is where many teams stumble. To move beyond hand-waving, CoEs need a structured framework. The Dataiku Value Framework defines four value pillars:
Use Case Value: Concrete applications that increase revenue, reduce costs, or mitigate risks, from predictive maintenance to churn prevention to ESG monitoring.
Time savings alone can be massive … 70% to 90% faster versus traditional tools. That translates directly into measurable productivity gains.
- Claire Gubian, VP of Business Transformation at Dataiku
In practice, these pillars translate into real numbers. For example, one CoE calculated $3.5 million in value gains by year three, delivering a 760% ROI. Gains came from productivity savings, stack efficiency, avoided governance costs, and faster delivery of high-value use cases.
The business case is only as strong as the use cases it’s built on. Chasing “AI for the sake of AI” is a trap. The right place to start is the business problem: why it matters, whose problem it is, and how solving it will create measurable outcomes.
A disciplined “use case canvas” guides this process by asking:
This structured approach ensures the CoE prioritizes opportunities where value will be visible, defensible, and aligned with enterprise strategy and avoids spreading resources across ideas with limited payoff.
Collecting metrics is necessary but not sufficient. Influence comes from how the story is told. Once ROI and adoption evidence is in hand, the CoE must communicate it widely and strategically.
That means framing wins in the language of each business unit, letting users share their own stories, and balancing numbers with qualitative impact. Employee satisfaction, data literacy, and cultural change may be harder to quantify, but they are critical to sustaining momentum.
Successful CoEs also manage adoption through an innovation funnel:
By showing how projects move through this funnel, CoEs demonstrate both innovation and scalability and position themselves as the pipeline for enterprise-grade solutions.
Not all benefits can be captured in a spreadsheet. Qualitative outcomes often make the difference between shallow adoption and durable transformation.
Take Mercado Libre as an example. To ensure self-service was more than a one-time spike, they tracked data literacy through structured training paths, certifications, and regular platform use. This sustained approach turned what could have been shadow IT into an innovation pipeline, strengthening both skills and adoption across the enterprise.
Examples like this highlight that ROI is both financial and cultural. A strong business case accounts for both and increasingly, that includes tracking how AI agents reshape the way teams work.
The strongest business cases balance immediate credibility with long-term vision. Quick wins show executives early success, while three-year ROI models capture compounding benefits from reuse, literacy, and process adoption.
Ultimately, building the case for a modern CoE is about reframing its role: not as a cost center to be defended, but as a growth engine for enterprise AI. It is the team that ensures self-service programs mature, governance scales, and AI adoption delivers measurable, repeatable business outcomes.