The State of AI: Energy is king, and the US is falling behind - https://www.technologyreview.com/2025/11/10/1126805/the-state-of-ai-energy-is-king-and-the-us-is-falling-behind/
Casey Crownhart writes:
In the age of AI, the biggest barrier to progress isn’t money but energy. That should be particularly worrying here in the US, where massive data centers are waiting to come online, and it doesn’t look as if the country will build the steady power supply or infrastructure needed to serve them all.
It wasn’t always like this. For about a decade before 2020, data centers were able to offset increased demand with efficiency improvements. Now, though, electricity demand is ticking up in the US, with billions of queries to popular AI models each day—and efficiency gains aren’t keeping pace. With too little new power capacity coming online, the strain is starting to show: Electricity bills are ballooning for people who live in places where data centers place a growing load on the grid.
If we want AI to have the chance to deliver on big promises without driving electricity prices sky-high for the rest of us, the US needs to learn some lessons from the rest of the world on energy abundance. Just look at China.
China installed 429 GW of new power generation capacity in 2024, more than six times the net capacity added in the US during that time.
China still generates much of its electricity with coal, but that makes up a declining share of the mix. Rather, the country is focused on installing solar, wind, nuclear, and gas at record rates.
The US, meanwhile, is focused on reviving its ailing coal industry. Coal-fired power plants are polluting and, crucially, expensive to run. Aging plants in the US are also less reliable than they used to be, generating electricity just 42% of the time, compared with a 61% capacity factor in 2014.
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It’s not a great situation. And unless the US changes something, we risk becoming consumers as opposed to innovators in both energy and AI tech. Already, China earns more from exporting renewables than the US does from oil and gas exports.
Building and permitting new renewable power plants would certainly help, since they’re currently the cheapest and fastest to bring online. But wind and solar are politically unpopular with the current administration. Natural gas is an obvious candidate, though there are concerns about delays with key equipment.
One quick fix would be for data centers to be more flexible. If they agreed not to suck electricity from the grid during times of stress, new AI infrastructure might be able to come online without any new energy infrastructure.
One study from Duke University found that if data centers agree to curtail their consumption just 0.25% of the time (roughly 22 hours over the course of the year), the grid could provide power for about 76 GW of new demand. That’s like adding about 5% of the entire grid’s capacity without needing to build anything new.
But flexibility wouldn’t be enough to truly meet the swell in AI electricity demand. What do you think, Pilita? What would get the US out of these energy constraints? Is there anything else we should be thinking about when it comes to AI and its energy use?
Pilita Clark responds:
I agree. Data centers that can cut their power use at times of grid stress should be the norm, not the exception. Likewise, we need more deals like those giving cheaper electricity to data centers that let power utilities access their backup generators. Both reduce the need to build more power plants, which makes sense regardless of how much electricity AI ends up using.
This is a critical point for countries across the world, because we still don’t know exactly how much power AI is going to consume.
Forecasts for what data centers will need in as little as five years’ time vary wildly, from less than twice today’s rates to four times as much.
This is partly because there’s a lack of public data about AI systems’ energy needs. It’s also because we don’t know how much more efficient these systems will become. The US chip designer Nvidia said last year that its specialized chips had become 45,000 times more energy efficient over the previous eight years.
Moreover, we have been very wrong about tech energy needs before. At the height of the dot-com boom in 1999, it was erroneously claimed that the internet would need half the US’s electricity within a decade—necessitating a lot more coal power.
MIT Technology Review subscribers can read the rest of Pilita's response, and Casey's reply here.
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