JLL famous that the arrival of AI in knowledge facilities has introduced vital adjustments to the trade, significantly by way of energy density and facility dimension
In sum – what it’s essential know:
AI reshaping knowledge 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 flooring masses, plus hybrid HVAC programs 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, knowledge 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 economic system, Sean Farney, vp of information heart technique at JLL, instructed RCR Wi-fi Information.
“The arrival of AI in knowledge facilities has introduced vital adjustments to the trade, significantly by way of energy density and facility dimension,” the JLL govt stated.
Hyperscale suppliers proceed to develop large campuses to assist conventional compute wants, however for AI-only operations, the economics and infrastructure look very completely different. “The extraordinarily excessive value of GPU server gear, which may 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 development towards “smaller, extra power-dense buildings.” AI infrastructure is not only dearer — it’s bodily completely different. “AI differs considerably from conventional servers, with {hardware} resembling large, heavy jet engines reasonably than the simply manageable servers of the previous,” Farney defined. This shift is forcing operators to rethink flooring 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 knowledge facilities,” stated Farney. Whereas the expertise may be built-in with present chiller programs — creating some retrofit potential — “air cooling continues to be essential 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 info heart trade is dealing with extra challenges on account of energy and land shortages, in addition to restricted colocation availability,” the JLL govt warned. With colocation emptiness charges dropping to only 2.6% by the top of 2024 and rents up greater than 11% throughout the U.S., operators are searching for artistic options.
Some of the viable choices is adaptive reuse — repurposing industrial or industrial belongings into AI-capable knowledge facilities. “This strategy harkens again to the early days of the web when many iconic knowledge facilities have been repurposed from present industrial amenities,” Farney famous. These conversions may be quicker and less expensive than greenfield developments, particularly in city areas the place energy and land are scarce.
Retrofits are additionally proving splendid for smaller AI workloads. “Many amenities which have shifted their essential masses 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 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 constantly evolving its approaches to design, development and operations to accommodate the transformative potential of AI whereas navigating the challenges it presents.”
