Campuses are continuing to operationalize generative AI while addressing data-security concerns and usage controls. Case Western Reserve University deployed Google Gemini for faculty, staff, and students after internal demand grew for a secure solution that would not expose campus data to training. The same broader implementation theme appears across the sector as institutions move from experimentation to enterprise tools—often requiring procurement, legal review, and technical safeguards before wider rollout. In this environment, early vendor selection criteria typically emphasize confidentiality, data retention, and administrative control. Separately, new research and policy discussions emphasize that “AI-ready” does not only mean adopting tools; it also requires governance, security, and operational planning across the connected campus ecosystem. For higher education leaders, these decisions affect classroom instruction, administrative workflows, research operations, and the compliance posture of institutional systems that increasingly integrate AI features into everyday processes.