SPOTLIGHT
Focus on AI data centres
Data centres specially built to handle the heightened power, cooling and computing demands for AI have become a distinct sub-sector within the wider market. Our analysis suggests that in the US these ‘AI-ready’ sites carry around a 10 percent cost premium compared with traditional facilities.
Data centres specially built to handle the heightened power, cooling and computing demands for AI have become a distinct sub-sector within the wider market. Our analysis suggests that in the US these ‘AI-ready’ sites carry around a 10 percent cost premium compared with traditional facilities.
The most advanced AI-specific facilities in the US are seeing cost-per-watt construction rates of between US$14.00 and US$16.00, significantly above the US$12.08 country average.
The factors below show the main areas that can put upwards and downwards pressure on AI-ready data centre construction.
Typical AI construction premium in the US
Key driver 1
The location and scale of gigawatt campuses
Site selection teams are typically looking for 250MW of IT load+
Cost impact
Labour shortages and a limited contractor pool able to work at scale puts upwards pressure on bid price, particularly in more remote site locations where significant per diem costs need to be absorbed.
General ownership costs for the land are also higher.
Schedule impact
Contract awards and long-lead procurement have to begin before design is fixed because of the sheer volume of equipment required.
Key driver 2
Requirements for higher rack density and liquid cooling
This is the key factor in capital. Some AI-ready facilities operate at 140kW per rack, with the trajectory heading to 1MW, compared to a 2026 US average of 27kW.
Cost impact
Applies a significant premium on capital expenditure, concentrated on the mechanical package.
Schedule impact
The commissioning programme lengthens due to the requirements for flushing, filtration, and chemical baselining.
Key driver 3
Requirement for lower redundancy
As AI training can be paused and restarted, interruption is a less critical issue.
Cost impact
Fewer generators may be needed, and lower expectations of central UPS can reduce the electrical capital expenditure.
Schedule impact
Removes some generator lead time and any associated permitting from the critical path.
Key driver 4
Rack-level battery storage
Installation of energy storage units directly inside or next to server racks to provide immediate backup power directly when needed.
Cost impact
The design change shifts costs around, but ultimately may not impact the total cost directly.
Schedule impact
Additional hazard mitigation analysis is required because the batteries are now spread throughout the main server room rather than isolated in a dedicated, fire-rated UPS room.
Key driver 5
On-site power generation
To reduce reliance on gaining grid connections, a critical part of planning and design.
Cost impact
Capital expenditure on power generation infrastructure such as turbines and engines could be significant. Already demand is pushing up prices, with some suppliers reporting turbine orders in 2026 are priced 10 to 20 percent higher per kW than in late 2025.
Schedule impact
Removes the risk of a long grid queue, but replaces this with risks from planning and permitting, as well as eventual interconnection to the grid.
Key factors shaping US AI facility costs and schedules
Department of Energy regulations
New rules could restrict foreign energy equipment, delaying large data centre projects and energisation.
Electric Reliability Council of Texas Batch Zero
Queue review results will indicate how much new data centre load the Texas grid can support.
Mechanical, electrical and plumbing labour inflation
Monitor whether mechanical, electrical and plumbing wages continue rising by around 7%, outpacing broader construction inflation.
Key takeaways for markets beyond the US
While the cost premium shown in our data is built on some elements that are unique to the US, there are some broader points of relevance to other regions:
- The extent of the premium for AI-ready facilities will depend in part on the number of large contractors available locally capable of delivering these projects at scale.
- Redundancy requirements, and therefore how much they impact the premium, will depend in some cases on local regulations and customer requirements.
- The costs of on-site generation can be mitigated if a project is built in an area with more abundant or flexible grid connections.
- There are likely to be significant lessons learned, and troubleshooting data related to the testing and commissioning process for US AI facilities as we go through 2027. These will in many cases be able to help improve the design and construction processes of similar facilities in other regions.
- Evidence from current US projects suggests that data centre developers and owners are increasingly giving more attention to the transportation, living arrangements and welfare of workforces that need to deploy to remote locations to support the delivery of mega-scale campuses. This needs to be factored into both the front-end planning and the requirements set out to supply chain partners.
Contents
Follow us
