The city stands up an AI Center of Excellence to coordinate pilots across public-health, permits, and 311. What governance structure is this?

An AI Center of Excellence (CoE) that coordinates cross-department municipal pilots is a governance structure for aligning standards, intake, shared platforms, and reusable practices across public-health, permits, 311, and similar units. The CoE works because cities otherwise reinvent conflicting model rules, duplicate unsafe pilots, and cannot compare risk or reuse controls. Central coordination does not mean the CoE builds every model alone; it means common guardrails, prioritization, and knowledge sharing so civic AI scales without chaotic fragmentation.

An AI Center of Excellence that sets cross-department municipal model standards fails because setting standards alone is only one part of governance, not the full active coordination of pilots, intake, shared platforms, and reuse across departments. An AI Center of Excellence that reviews cross-department municipal pilot proposals fails because reviewing proposals is only front-end intake, not the ongoing coordination, guardrails, and shared learning across the pilot lifecycle. An AI Center of Excellence that reuses successful municipal pilots citywide fails because reuse and scaling alone come after coordination, without the upfront prioritization, standards alignment, and cross-cutting risk review the question describes.

Exam caveat: a CoE without authority or executive sponsorship becomes a discussion forum; exams often distinguish coordination structures from policies and from individual role titles. Operational check: publish CoE intake criteria for pilots, maintain a shared register of municipal AI use cases, require CoE review for cross-cutting data/model risks, and track whether public-health, permits, and 311 pilots actually reuse the same security and evaluation baselines.