Colleges and universities are reassessing cloud strategy as AI workloads move from specialized research to core functions such as recruitment, advising, student support and campus safety. IT leaders are weighing whether to run large language models and inference workloads in third‑party clouds, on prem, or in hybrid arrangements—decisions that relay directly to data privacy, compliance and security obligations. Institutions cited in the reporting are shifting governance: CIOs must now coordinate procurement, legal, academic affairs and research computing to set boundaries for protected data and model provenance. This realignment raises procurement, budgeting and vendor‑risk questions for finance and compliance teams. For universities, the practical stakes include where sensitive student and research data reside, how to fulfill grant terms for data locality, and how to budget for rapid spikes in GPU/TPU demand. IT governance frameworks—clarifying who signs contracts, who vets vendors, and how models are audited—are becoming a near‑term operational priority.