Definition: An AI center of excellence (CoE) is a central team that sets standards, builds shared platforms and expertise, and coordinates governance so that teams across an organization can adopt AI consistently and safely.
Typical responsibilities include choosing approved models and vendors, running shared infrastructure such as an LLM gateway and eval tooling, publishing reference architectures, reviewing high-risk use cases, training teams and keeping an inventory of AI systems in use.
A centralized CoE builds most AI systems itself. A federated or hub-and-spoke model keeps a lean central team for standards and platforms while business-unit teams build their own use cases. Many organizations start centralized and federate as skills spread.
A CoE that only writes policy becomes a bottleneck. Effective ones ship real systems early, measure business outcomes, and make the approved path the easiest path. They also connect to existing AI governance and security processes rather than duplicating them.
Usually an AI or platform lead, ML and LLM engineers, data engineers, a product owner, and partners from security, legal and risk.
Ryz senior LLM engineers and MLOps engineers join CoE teams to build the shared platform, reporting to your leads.
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