JLL famous that the appearance of AI in information facilities has introduced important adjustments to the trade, significantly by way of energy density and facility dimension
In sum – what you’ll want to know:
AI reshaping information heart design – The rise of AI is driving demand for smaller, extra power-dense amenities on account of GPU prices reaching $30M per MW, JLL says.
Cooling and construction reimagined – AI {hardware}’s weight and warmth require new designs, together with liquid cooling and stronger ground hundreds, plus hybrid HVAC methods for blended gear.
Retrofits provide near-term reduction – With colocation emptiness at 2.6%, adaptive reuse and stranded energy capability in cloud-shifted websites are rising as scalable options for 1–3MW AI workloads.
As AI adoption accelerates globally, information heart operators are grappling with unprecedented infrastructure and actual property calls for. From energy density to house constraints, the race to construct AI-ready amenities is reshaping the digital spine of the fashionable financial system, Sean Farney, vp of information heart technique at JLL, informed RCR Wi-fi Information.
“The arrival of AI in information facilities has introduced important adjustments to the trade, significantly by way of energy density and facility dimension,” the JLL government mentioned.
Hyperscale suppliers proceed to broaden large campuses to help conventional compute wants, however for AI-only operations, the economics and infrastructure look very totally different. “The extraordinarily excessive value of GPU server gear, which might attain $30 million per megawatt, makes it financially impractical to construct million-square-foot AI-only amenities apart from these with the deepest pockets,” he added.
This monetary actuality is driving a development towards “smaller, extra power-dense buildings.” AI infrastructure isn’t just dearer — it’s bodily totally different. “AI differs considerably from conventional servers, with {hardware} resembling large, heavy jet engines quite than the simply manageable servers of the previous,” Farney defined. This shift is forcing operators to rethink ground loading capacities and the bodily construction of buildings themselves.
Cooling infrastructure can also be present process a change. “Liquid cooling has emerged as a brand new problem and alternative in AI information facilities,” mentioned Farney. Whereas the know-how will be built-in with present chiller methods — creating some retrofit potential — “air cooling continues to be needed for personnel, community gear and different non-liquid-cooled gear.” This hybrid requirement complicates facility design and HVAC planning, even in new builds.
On the similar time, useful resource constraints are piling up. “The information heart trade is going through further challenges on account of energy and land shortages, in addition to restricted colocation availability,” the JLL government warned. With colocation emptiness charges dropping to only 2.6% by the tip of 2024 and rents up greater than 11% throughout the U.S., operators are in search of inventive options.
One of the vital viable choices is adaptive reuse — repurposing industrial or business belongings into AI-capable information facilities. “This strategy harkens again to the early days of the web when many iconic information facilities had been repurposed from present industrial amenities,” Farney famous. These conversions will be sooner and cheaper than greenfield developments, particularly in city areas the place energy and land are scarce.
Retrofits are additionally proving excellent for smaller AI workloads. “Many amenities which have shifted their vital hundreds to the cloud over the previous decade now have stranded energy capability. These areas might be appropriate for smaller-scale AI deployments of 1-3 megawatts, which are sometimes required for product growth and testing labs,” mentioned Farney.
Regardless of the constraints and complexity, he sees the trade rising to the problem. “The information heart trade is demonstrating flexibility and agility in adapting to those new applied sciences and their distinctive necessities,” he mentioned. “The trade is constantly evolving its approaches to design, building and operations to accommodate the transformative potential of AI whereas navigating the challenges it presents.”