As institutions expand AI use across teaching, research, and operations, higher education leaders are increasingly moving toward formal governance structures—particularly through AI centers of excellence. The approach aims to coordinate adoption, set risk controls, and scale AI implementation rather than letting experimentation remain fragmented. The reported model centers on cross-functional oversight, with guidance that covers responsible implementation, governance, and alignment between academic and administrative stakeholders. The underlying concern is that AI use without a framework can create inconsistent outcomes and elevated compliance risk. These centers reflect how universities are transitioning from isolated pilots to enterprise-style governance, including repeatable assessment practices and consistent policies on acceptable use. For campuses, the shift signals that AI adoption is becoming a controlled institutional capability rather than an optional innovation track, pushing requirements for documentation, governance, and accountability.