Artificial intelligence adoption in higher education is often discussed through policy or technology strategy, but much of the real work is happening informally through experimentation, peer learning, and day-to-day problem solving across institutions. This session explores how AI Communities of Practice can help universities move from fragmented experimentation toward more thoughtful and coordinated approaches to AI governance. Drawing from experiences supporting AI initiatives in higher education, the session examines how faculty, staff, and administrators make decisions about AI use while institutional guidance and norms are still evolving. The conversation will focus on professional judgment, trust, ethical uncertainty, institutional culture, and the hidden labor involved in helping colleagues make sense of rapidly changing technologies. Rather than viewing governance only as a top-down policy process, this session considers how governance also develops socially through conversation, collaboration, and shared institutional learning.
