Half of Planned US Data Center Builds Have Been Delayed or Canceled
- Reference: 0181215642
- News link: https://hardware.slashdot.org/story/26/04/03/1558235/half-of-planned-us-data-center-builds-have-been-delayed-or-canceled
- Source link:
> Approximately 12 gigawatts (12 GW) of data center capacity is expected to come online in the U.S. in 2026, according to data by market intelligence firm Sightline Climate cited by [5]Bloomberg . Yet only about one-third of that capacity is currently under active construction because of various constraints.
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> Electrical infrastructure represents less than 10% of total data center cost, but it is as vital as compute hardware. A delay in any single element of the power chain can halt the entire project, which makes transformers, switchgear, and similar devices critical items despite their relatively small share of CapEx. Due to high demand, lead times for high-power transformers have expanded dramatically in the U.S.: delivery typically took 24 to 30 months before 2020, but waiting periods can stretch to as long as five years today, according to Sightline Climate cited by Bloomberg. For AI data centers, this is a catastrophe as their deployment cycles are under 18 months.
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> To address shortages, companies are turning to global markets. As a result, Canada, Mexico, and South Korea became the biggest suppliers of high-power transformers for AI data centers to AI data centers. At the same time, imports of high-power transformers from China surged from fewer than 1,500 units in 2022 to more than 8,000 units in 2025 through October, according to Wood Mackenzie data cited by Bloomberg. The volatility of exports from China does not end with transformers, as the PRC accounts for over 40% of U.S. battery imports, while its share in certain transformer and switchgear categories remains near 30%, according to Bloomberg.
[1] https://developers.slashdot.org/story/25/09/24/0351254/openai-oracle-softbank-plan-five-new-ai-data-centers-for-500-billion-stargate-project
[2] https://news.slashdot.org/story/26/03/16/1548242/data-centers-overtake-offices-in-us-construction-spending-shift
[3] https://meta.slashdot.org/story/26/03/16/1743259/meta-signs-27-billion-ai-infrastructure-deal-with-nebius
[4] https://www.tomshardware.com/tech-industry/artificial-intelligence/half-of-planned-us-data-center-builds-have-been-delayed-or-canceled-growth-limited-by-shortages-of-power-infrastructure-and-parts-from-china-the-ai-build-out-flips-the-breakers
[5] https://www.bloomberg.com/news/features/2026-04-01/us-ai-data-center-expansion-relies-on-chinese-electrical-equipment-imports
I love... (Score:5, Funny)
...the smell of bubbles popping in the morning.
Re: (Score:1)
Smells like ... recession.
(But finally I can buy PC parts.)
Re: (Score:2)
Might very well be the opposite if all the non-AI companies betting on AI suddenly have to go on a hiring spree to rehire the people they thought they could replace with snake-oil.
It'd be nice to get back to Biden's full employment again.
Re: (Score:1)
Almost nobody actually laid of employees because of AI, that was just an excuse to downsize in slow markets. If sales were growing, the same number of employees could do more work via bots such that they wouldn't actually reduce head-count. The proper business move under gained efficiency in a normal economy is to chase market share, not lay off.
Re: (Score:3)
There's at least some evidence on some level that the C-suite class actually believes all this bullshit. Hence the mandates forcing people to use AI and giving people bad performance reviews if they don't use it.
This isn't to say there hasn't also been a lot of redundancies blamed on AI that wouldn't have happened anyway, I've said as much myself, but certainly we've had plenty of cases where the C-suite have assumed that AI can fill in the gaps.
I think once the AI bubble pops, rehiring skilled workers will
Re: (Score:2)
Speaking of which, I like a news item I saw this morning that [1]RAM prices are collapsing as a massive deal that OpenAI had made w/ Samsung and Hynix to corner 40% of DRAM production [youtube.com] is not going to materialize
Can't happen soon enough. Five years ago, I bought this laptop at Costco for $250. Yesterday, looking at the latest Costco catalog, there are no laptops less than $750 (no, the Neo hasn't arrived there, and I didn't notice any Chromebooks either, which also I had bought from Costco around that time
[1] https://www.youtube.com/watch?v=gr6T4ZS7M4c
Good. (Score:3, Insightful)
Maybe we can stop with the infinite build for endless capacity bullshit.
Re: Good. (Score:3)
I agree, they are not making anything better, and only driving up the price of computer hardware
Sounds familiar (Score:5, Informative)
Shoutout to my fellow IT workers who have tried to get electrical utilities to do literally anything. Our small site UPS was reporting voltage out of range and they fixed it after 5 calls, 4 staff technician visits, 2 recorders, and 4 weeks. It was a bad component in the sub-station that was "very old" according to them. Their solution to stopping 129V from coming in overnight was to switch that one off and hope the rest can handle the load.
Now imaging trying to order several megawatts. Usually, the new construction department is different than maintenance, but sounds like they're having a similar experience.
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Doesn't even have to be a plant trying to get more capacity. Corporate utilities look at the cost, X , and what you're willing to reasonably pay, Y , and refuse to build if Y is less than 2-3 times, at a minimum, what X is. Which is a big part of why common infrastructure shouldn't be in corporate hands in the first place, but publicly operated. This is legitimately a serious problem for households in the US since the end of the public push for rural electrification in the 90s. The only thing that's chang
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> Usually, the new construction department is different than maintenance, but sounds like they're having a similar experience.
The lead time of bringing new capacity online is often measured in years. Even with infinite AI money being thrown at the issue, the lead time for many of the necessary generation and transmission components is quite long (last I checked the large transformers needed for large power and substations had an up to 5 year delivery wait).
Logistics matter (Score:3)
As more and more datacenters were being announced, some skeptics kept asking about how datacenters would be powered and cooled. There was concern that the infrastructure was not adequate. "Trust me bro," always seem to be the answer. It turns out building megawatt datacenters requires a great deal of meticulous planning. Who knew?
Something else that has been brought up is that with delays, the hardware in these datacenters might be obsolete by the time they are built. Previous datacenters like Google ones were built with hardware that was not the cutting edge but were stable and reliable. AI always needs the latest and greatest processors. However, by the time the datacenter is fully built, those processors are no longer the latest and greatest.
Also there is the next question: "Where did all the money go?" If datacenters are being delayed or canceled, what happened to all the money that used to start the datacenter project. Investors might start asking too many questions about what happened to their investments.
Re: (Score:2)
> As more and more datacenters were being announced, some skeptics kept asking about how datacenters would be powered and cooled. There was concern that the infrastructure was not adequate. "Trust me bro," always seem to be the answer. It turns out building megawatt datacenters requires a great deal of meticulous planning. Who knew?
I completely agree with this. My state was all about banning ICE vehicles and gas stoves and furnaces in about a decade...but had very few plans to handle the terawatt capacity requirements...and this was *before* datacenters got a seat at the table.
> Something else that has been brought up is that with delays, the hardware in these datacenters might be obsolete by the time they are built.
I'm...not quite sure I agree with this one as much...
> AI always needs the latest and greatest processors.
This...I think, has some wiggle room. Sure, training new models requires greater amounts of compute power, and as newer models and services develop, there will be a need to increase compute power. However, tha
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> This...I think, has some wiggle room. Sure, training new models requires greater amounts of compute power, and as newer models and services develop, there will be a need to increase compute power. However, that doesn't mean that older models are useless. They may not be front-and-center, but they can still be used in lesser capacities. ChatGPT 3.5 isn't quite as awesome as v5, but if it's what is used to serve up ads in ChatGPT sessions, the hardware is still perfectly fit-for-purpose. Same goes for Google or Microsoft - older boards may not be front-and-center, but they can still do boring, smaller-scope tasks that are still useful.
Older models do not generate investment which is the primary source of AI funding. While better models can be developed over time, the cheat code for all models is just to use more powerful hardware. Also logistics has been ignored by AI companies as vital. They want the most powerful hardware now. The reality that datacenters take years to build means the hardware they buy now will not bet the latest when the datacenter comes online requires forethought and planning. They would rather cancel the whole cont
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> Something else that has been brought up is that with delays, the hardware in these datacenters might be obsolete by the time they are built. Previous datacenters like Google ones were built with hardware that was not the cutting edge but were stable and reliable. AI always needs the latest and greatest processors. However, by the time the datacenter is fully built, those processors are no longer the latest and greatest.
Unless the companies are completely incompetent, they aren't having the processors manufactured until they have a plan for bringing the building online, including power delivery.
Everything else in the data center is pretty much the same no matter what hardware you put in the racks. You still need floors, walls, and a ceiling or roof. You still need places for cables to go between racks (either above or below). The floors still need to be built to handle high static weight loads where the racks are. You
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> Unless the companies are completely incompetent, they aren't having the processors manufactured until they have a plan for bringing the building online, including power delivery.
Not from what I can see. NVidia is getting tons of orders for processors. Also the RAM shortage is because AI datacenters are buying all available memory and convincing the RAM foundries to make as much high bandwidth AI server memory as possible. When the bubble bursts, will these companies be left with orders no one wants. For example, Micron has stopped selling consumer memory in order to make HBM3E which is not consumer RAM sticks. Maybe Micron could sell some of that RAM to non AI datacenters, but the
RAM (Score:2, Informative)
Please crash and burn harder AI industry bubble. I'm not buying RAM again until it's less than $6/GB. We are currently at 2009 prices for RAM:
[1]https://battlepenguin.com/tech... [battlepenguin.com]
I'm really regretting not just maxing out my homelab with RAM when it was all reasonable.
[1] https://battlepenguin.com/tech/the-high-price-of-ram/
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Back in March of 2025 I purchased 32GB of DDR4 for $62 for a system I was putting together. I just checked the other day and that same RAM is now $219. Man I got lucky. I had no idea back then RAM prices would spike this much. Like you I'm going to hold off on RAM purchases until this AI insanity bubble bursts. Same goes for all other components (SSD, NVMe, GPU, etc..)
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It's kind of pissing me off actually. I'm finally to the point where the 32GB I have in my desktop isn't sufficient for what I'm doing on it anymore, and I don't want to spend the entire price of a new mini PC to get it to 64GB.
So I have to grit my teeth through swapping and frequent reboots.
Fuck the AI billionaire bros.
Obsolete data centers canceled before construction (Score:3)
As reported elsewhere, the long lead times have made some data centers obsolete at startup, or sometimes before construction is complete. For example, Oracle and OpenAI abandoned expansion of a data center in Texas, because the expansion as planned would not be ready for new NVidia GPUs. TFA doesn't mention the tremendous water consumption by data centers, a statistic AI companies strive to hide, and which many water-constrained communities rightly use to oppose data center construction.
Re:Obsolete data centers canceled before construct (Score:4, Funny)
Most of the time, the answer I heard to any logistical concern like community water usage, missing hardware, inadequate electric grid, etc. was handwaving by AI proponents as if it could all be solved by asking AI to how build AI datacenters.
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It's almost like people that are completely bought-in on a hype cycle that can't be rationally justified are not paying attention to easily observed reality.
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Reminds me of the folks who think pod based transit works but just forgot about Morgantown or the fact cars failed to scale.
Time to innovate (Score:2)
If you have to wait years for transformers, this creates a huge market for electronic converters for high and medium voltage AC. Their production can be ramped up much faster. The problems in designing such electronic transformers is not much different from HVDCHVAC converters, it's obviously possible to do it reliably.
Will ram prices come down? (Score:2)
If a bunch of data centers are being canceled I would hope that ram prices will ease somewhat.
The natives are getting restless (Score:2)
This is interesting. Microsoft is currently preparing the site for a large data center on the border of my city and San Jose. In an area that has had power issues for years and is undergoing yet another dry winter. Will it actually get built and come online and, if so, will it be consuming an outsized share of resources such that we peasants revolt when we have brown outs when the summer temps break 100 or we have a cap placed on water usage? Stay tuned.
What a surprise (Score:2)
Thought exactly nobody.
Big infra, big timeline (Score:3)
Timelines of power infrastructure aren't planned in the same manner as private industries who are chasing AI fads and quarterly profits. Unsurprising that lead times for products are more aligned to that traditional case.
It's not the infrastructure, it's the conjob (Score:2, Interesting)
The bigger factor is that their whole "AI" thing is collapsing before their eyes, because once "AI" is explained, you can either replace "AI" with "magic" or a quantifiable, describable existing technology. And in this particular bubble, it's not a describable existing technology, it's "magic". And while investors might be fooled, the accountants aren't, and management's starting to figure it out (or aren't fooled in the first place but are intentionally misleading investors).
They're not exactly helping t
Re:It's not the infrastructure, it's the conjob (Score:5, Insightful)
It's not the accountants that are the roadblock. It's the second or third levels in the supply chain that are resistant to build out rapid additional capacity.
This is the same story for RAM providers where additional manufacturing lines are long timelines. Building extra capacity for demonstrated short term demand that may not last by the time of completion is a large risk. In the mean time, they can already rake in additional profit off that raised demand and limited supply from other competitors that are making the same cost/benefit evaluations.
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This can result in bad things in the long run, though. For example, if someone finds some new technology that is like DRAM, except doesn't need a refresh signal, something like Optane, but an order of magnitude faster. When you get extreme demand pulls, people will start doing something about it, even make long term projects because they know that the RAM issue may go away short-term, but it will hit them in the future. Or, DRAM will be minimized and Optane-like memory will be used as "swap", similar to
Re: (Score:2)
> It's not the accountants that are the roadblock. It's the second or third levels in the supply chain that are resistant to build out rapid additional capacity.
> This is the same story for RAM providers where additional manufacturing lines are long timelines. Building extra capacity for demonstrated short term demand that may not last by the time of completion is a large risk. In the mean time, they can already rake in additional profit off that raised demand and limited supply from other competitors that are making the same cost/benefit evaluations.
And why shouldn't they be "resistant"?
They go out and spend the money to increase capacity and this whole AI fad falls in a heap long before they recoup the investment, the techbros aren't going to pick up the tab. Hell, they were planning to screw them on price from the very beginning.