This is one outlet's own report from Fortune — the article as it was filed.
AIPROPX ReportFortune · 1h ago
AI’s volatile power demand is damaging its own data centers
Rapid swings in AI data centers’ power demands are straining vital equipment, causing batteries, generators and cooling systems to malfunction or wear out far sooner than expected.
As the AI boom accelerates, these technical problems suggest added costs and unforeseen reliability problems, with even a few minutes of lost uptime hitting data-center developers’ revenue. They come at a time when investors and lenders are already jittery about hyperscalers’ hundreds of billions of dollars of spending, amid growing concerns that these facilities could be depreciating much faster than estimated.
The problems are also a potential source of wider instability in power grids that are already straining to keep the lights on.
“AI does create very unusual power demand,” said Amber Villegas-Williamson, principal consultant at the Uptime Institute in the UK, which advises electricity suppliers and data centers on standards and reliability. “It’s like over-revving your car wears out the engine faster than keeping a constant speed.”
Data centers have been around for decades, gulping down electricity while they ensure that everything from your favorite streaming show to your online grocery order functions smoothly. But facilities designed for AI computing are different because their demand is so large and swings much more dramatically.
Power increments equivalent to the consumption of factories, towns or even cities can appear and disappear within seconds, creating repeated shocks that connected equipment struggles to absorb.
A gigawatt data center is equivalent to a city the size of Boston, half of which can flicker on and off every few seconds, said Shannon Miller, founder and president of Mainspring Energy Inc., which works on micro-grid projects for industrial and data-center customers. Some AI campuses planned in Texas, the Midwest and other states are more than five times bigger, consuming nearly as much power on average as New York City.
AI data centers put particular strain on their power supply when they are training new models — a process that mobilizes all of the graphics processing units in unison. Like the digital equivalent of bees swarming or a school of fish changing direction, hundreds of thousands of GPUs can power up and down on a millisecond basis.
AI at times sees power usage spike as much as 50% above its design capacity, “so a 1 gigawatt facility may use 1.5 gigawatts for a split second,” said Drew Baglino, a former Tesla Inc. executive who started Heron Power Electronics Co. The company is developing equipment to manage power fluctuations for Nvidia Corp.’s even more energy intensive next-generation of servers, due in 2027.
Most equipment isn’t designed for such big swings in power consumption. Jon Parrella, chief executive officer of energy-storage developer Terraflow Energy, likens it to driving a Ferrari and shifting straight from sixth gear to first. “You can’t swing that fast,” he said.
This story is based on interviews with more than three dozen power experts in the US and Europe, including generators and other power suppliers, data-center developers, grid operators, utilities, investors, standards developers, insurers and regulators, almost all of whom said the physical stresses on the facilities were evident.
Cranks on small natural gas combustion engines used to generate power at data centers have broken off, several of those people said. At xAI’s Colossus computing facility in Memphis, Tennessee, gas-fired turbines had developed cracks, one of the people said. Batteries were installed within the system to help smooth out power swings and reduce the strain on spinning turbines, the person said.
SpaceX, the parent company of xAI, didn’t respond to requests for comment.
Turbines have also cracked at much smaller data centers in the UK, said Andrew Cunningham, CEO of GeoPura Ltd., which is providing hydrogen for use in fuel cells that smooth out power flows at some sites.
Cracks or wear on devices can cause electrical arc flashes — when a current jumps between conductors — potentially damaging AI chips, said Jennifer Scanlon, CEO of UL Solutions Inc., which tests and certifies new technology.
There is a suite of equipment such as batteries, capacitors, transformers and flywheels that can help stabilize power flows. However, in the bid to build AI computing capacity quickly not enough of these technologies are being used at new data centers, several of the people said. Batteries that have been installed for this purpose have sometimes needed to replaced within months or even weeks due to the high strain, according to the Uptime Institute and other people working with operators.
This problem is seen at data centers around the world, from the Middle East and Africa, to Europe and the US, said Villegas-Williamson of the Uptime Institute.
Reliability Problems
These issues are already causing delays or curtailing operations – and therefore revenue – at some AI computing facilities.
To ensure that a planned 2.67-gigawatt AI campus in West Texas can achieve the 99.999% reliability required by Microsoft Corp., extra time was baked into the schedule for engineering, said Chris James, CEO of Joulent Inc., which is developing the facility with energy giant Chevron Corp. This means power delivery will begin in 2028 instead of 2027, he said.
If essential equipment breaks down prematurely, “the financial consequence is not primarily replacing a pump or a breaker or some power component — it’s the the value of that expensive compute capacity not generating revenue because it’s offline,” said Jason Hoffman, chief strategy officer at data-center builder and operator Switch.
The cost of downtime in terms of lost revenue varies widely, with...
AI’sEquipmentRapidAmber VillegasWilliamsonUptime InstituteIt’sDataPowerA BostonShannon Miller
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