Beyond the Campus: Move Your AI Infrastructure Off‑Site

Learn why leading universities are shifting AI infrastructure off‑site. Legacy on‑campus data centres have become bottlenecks: they strain budgets, consume valuable space and struggle to meet modern AI performance. The alternative is purpose‑built environments designed for accelerated computing.

Mounting Pressure on On‑Campus Facilities

• Compute capacity gaps: on‑campus systems can’t deliver the speed, scale or reliability for large‑scale AI, simulations or digital twins; many will be outpaced within 3–5 years.
• Escalating costs: building or maintaining on‑campus facilities requires major capital and high ongoing energy/operational spend.
• Sustainability challenges: ageing infrastructure is among the most energy‑intensive campus assets, complicating Net Zero and ESG goals.
• Space constraints: prime real estate for teaching and labs is tied up by outdated IT rooms.
• Connectivity barriers: limited network capacity hampers collaboration, real‑time data sharing and access to global ecosystems.

From Data Centres to ‘AI Factories’: What Modern Research Needs

• Power multiplication: AI racks consume roughly 10–40× the power of conventional compute.
• Next‑gen cooling: liquid cooling (e.g., direct‑to‑chip/immersion) replaces conventional air systems for dense GPU clusters.
• Built‑in scalability: modular, rapidly deployable infrastructure free of legacy constraints.

Proof in Action

La Trobe University deployed NVIDIA DGX H200 inside NEXTDC colocation to power its Australian Centre for AI in Medical Innovation, illustrating how off‑site, AI‑optimised infrastructure accelerates research while remaining sovereign.

The AI race isn’t waiting. Download the Brief to see the off‑site path universities are taking, from cost and risk reduction to connectivity and sovereign operations.