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Why Your AI Center Of Excellence Should Get Smaller As AI Gets Bigger
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Igor Rikalo, Forbes Councils Member

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World NewsForbes: Innovation

Why Your AI Center Of Excellence Should Get Smaller As AI Gets Bigger

Igor Rikalo is President at o9 Solutions.

AI activity has become ubiquitous within large businesses as they deploy co-pilots, agents, forecasting models and dozens of pilots across many functions.

McKinsey’s 2026 State of the AI survey found that 88% of organizations regularly use AI in at least one business function and 44% now report scaling it across the enterprise, up from 38% a year earlier. However, the financial results have not kept pace. The survey finds that only 6% qualify as high performers, crediting AI with at least 5% of operating profit, a share that has not moved since 2025.​

Large companies aren’t lacking effective ideas for using AI. Rather, they lack a reliable way to transform those ideas into business value, and this gap is why the AI center of excellence (AI CoE) remains necessary. However, its purpose needs to change. ​

Initially, AI CoEs acted as a pool for scarce technical talent because it was difficult and expensive to find workers with the necessary skills. Today, these constraints have mostly disappeared, but what remains scarce is even harder to buy: knowing which decisions move the business, earning enough trust to let a system run and measuring what changed.​

A modern AI CoE should own this record and create the standards around it, whereas business teams own the work and results. When the AI CoE is tasked with assessing every use case, tool choice and risk review passes, the enterprise slows down.

Start With Decisions, Not Use Cases

When starting new projects, organizations usually begin by inventorying possible AI use cases. However, it’s more productive to start with the decision itself. For example, consider the difference between “build a supply-planning agent” and “reduce the risk of running out of stock while holding inventory and expediting costs within agreed limits.” The first option describes a technology project, whereas the second identifies the decision, the trade-off, the owner and the measure of success.

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This story was published by Forbes: Innovation and written by Igor Rikalo, Forbes Councils Member. SyncAI.news shows a preview; the complete article is on the publisher's site.

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