As generative AI moves from research labs into student services and campus operations, colleges and universities are reassessing cloud architecture, procurement and governance. Institutional IT leaders warn that AI workloads—used for recruiting, advising, student safety and administrative automation—raise new data‑privacy, cost and jurisdiction questions that legacy cloud plans didn’t anticipate. The shift is reshaping decisions about on‑premises versus multi‑cloud deployments, vendor contracts, and data‑sharing agreements with ed‑tech partners. Campus counsel and CIOs are drafting new governance frameworks to address model provenance, student data protections and research compute needs. The debate underscores a broader tradeoff: scale and agility from cloud providers versus control and compliance demanded by academic missions and regulations.