AI is moving fast across higher education. What starts as a pilot in one department quickly becomes a campus wide expectation, and that shift exposes gaps in infrastructure, governance, data privacy, and cost control. For IT and campus leaders, the challenge is not whether AI will expand, but whether the institution is prepared to support it at scale without creating risk, overspending, or slowing innovation.

This thought leadership paper, sponsored by HP Inc. and NVIDIA, outlines a practical approach to building the foundations for responsible AI adoption. It helps you assess current readiness, align stakeholders, and make the infrastructure decisions that determine whether AI initiatives stay manageable as usage grows across teaching, research, and administration.

You will learn how to:

• Move beyond fragmented pilots with a coordinated, campus wide approach to AI adoption

• Evaluate where different AI workloads belong, including cloud, on premises, and hybrid environments

• Inventory existing workstations, endpoints, and systems to identify what is already AI ready

• Use lessons from early AI projects to forecast compute, storage, and bandwidth requirements more accurately

• Establish governance for intellectual property, ethics, security, and privacy to support consistent AI use

• Standardize provisioning and support models so users get access without overloading IT resources

• Reduce friction for faculty and researchers while maintaining oversight and institutional controls

Download the paper to build a scalable AI foundation for your campus and move from experimentation to sustainable AI operations.