JLL famous that the appearance of AI in information facilities has introduced important modifications to the trade, notably by way of energy density and facility measurement
In sum – what it is advisable know:
AI reshaping information heart design – The rise of AI is driving demand for smaller, extra power-dense amenities because 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 masses, plus hybrid HVAC programs for combined tools.
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 trendy economic system, Sean Farney, vp of information heart technique at JLL, instructed RCR Wi-fi Information.
“The appearance of AI in information facilities has introduced important modifications to the trade, notably by way of energy density and facility measurement,” the JLL government stated.
Hyperscale suppliers proceed to increase large campuses to assist conventional compute wants, however for AI-only operations, the economics and infrastructure look very totally different. “The extraordinarily excessive price of GPU server tools, which may 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 pattern 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 relatively 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,” stated Farney. Whereas the know-how may be built-in with present chiller programs — creating some retrofit potential — “air cooling remains to be essential for personnel, community gear and different non-liquid-cooled tools.” 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 extra challenges because of energy and land shortages, in addition to restricted colocation availability,” the JLL government warned. With colocation emptiness charges dropping to simply 2.6% by the top of 2024 and rents up greater than 11% throughout the U.S., operators are in search of artistic options.
One of the crucial viable choices is adaptive reuse — repurposing industrial or industrial belongings into AI-capable information facilities. “This method 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 may be quicker and more cost effective than greenfield developments, particularly in city areas the place energy and land are scarce.
Retrofits are additionally proving superb for smaller AI workloads. “Many amenities which have shifted their crucial masses to the cloud over the previous decade now have stranded energy capability. These areas may very well be appropriate for smaller-scale AI deployments of 1-3 megawatts, which are sometimes required for product improvement and testing labs,” stated 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 stated. “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.”
