JLL famous that the appearance of AI in information facilities has introduced important modifications to the trade, notably when it comes to energy density and facility measurement
In sum – what it’s good to know:
AI reshaping information heart design – The rise of AI is driving demand for smaller, extra power-dense amenities as a result 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 techniques for combined gear.
Retrofits supply near-term aid – 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 knowledge heart technique at JLL, instructed RCR Wi-fi Information.
“The appearance of AI in information facilities has introduced important modifications to the trade, notably when it comes to energy density and facility measurement,” the JLL government mentioned.
Hyperscale suppliers proceed to develop huge campuses to help conventional compute wants, however for AI-only operations, the economics and infrastructure look very completely different. “The extraordinarily excessive price of GPU server gear, which might attain $30 million per megawatt, makes it financially impractical to construct million-square-foot AI-only amenities aside from these with the deepest pockets,” he added.
This monetary actuality is driving a pattern towards “smaller, extra power-dense buildings.” AI infrastructure is not only costlier — it’s bodily completely different. “AI differs considerably from conventional servers, with {hardware} resembling huge, heavy jet engines slightly 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 be present process a change. “Liquid cooling has emerged as a brand new problem and alternative in AI information facilities,” mentioned Farney. Whereas the expertise will be built-in with present chiller techniques — creating some retrofit potential — “air cooling continues to be mandatory 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 identical time, useful resource constraints are piling up. “The info heart trade is dealing with further challenges as a result 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 on the lookout for inventive options.
Some of the viable choices is adaptive reuse — repurposing industrial or industrial property 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 quicker and cheaper than greenfield developments, particularly in city areas the place energy and land are scarce.
Retrofits are additionally proving supreme 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 could possibly 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 info heart trade is demonstrating flexibility and agility in adapting to those new applied sciences and their distinctive necessities,” he mentioned. “The trade is repeatedly evolving its approaches to design, building and operations to accommodate the transformative potential of AI whereas navigating the challenges it presents.”
