This guide examines how higher education institutions can scale AI across research, instruction and campus operations despite growing data demands and constrained resources. It highlights high-impact use cases, including enabling secure remote access, accelerating compute-intensive workloads and protecting sensitive research data. Readers will also gain insight into the infrastructure needed to support AI-driven learning and innovation.
