Colleges and universities are changing where and how they run workloads as artificial intelligence moves beyond research labs into enrollment, advising, campus safety and administrative systems. IT leaders report that AI’s data demands and privacy implications are forcing new cloud decisions — not simply more cloud but different cloud placements tied to compliance, costs and vendor risk. The story, reported across higher-education IT outlets, emphasizes that institutions must align procurement, legal and academic priorities when choosing cloud providers and deployment models. Campus IT leaders and general counsels are weighing trade-offs: on‑premises control versus hyperscaler scale, and centralized governance versus decentralized academic experimentation. The shift has immediate budgeting implications — new contracts, revised SLAs and reworked data classification — and creates a governance workload that many campuses are not staffed to handle. Practical takeaways for presidents and provosts: establish cross‑functional AI/cloud governance, map sensitive datasets used in AI projects, and build procurement processes that vet vendor compliance with student‑privacy laws and research export controls.