Consumers Are Footing the Bill for AI’s Insatiable Appetite for Energy
- The rapid growth of data centers, particularly due to AI, is significantly increasing energy demand and jeopardizing clean energy initiatives by extending the life of fossil fuel plants and promoting new ones.
- The issue is compounded by "phantom data centers," which inflate projected energy demand and give utilities leverage to expand fossil fuel infrastructure.
- This surge in energy demand and the resulting infrastructure projects are projected to lead to higher energy bills for consumers, especially in the Southeast United States.
As data centers place more and more demand on global power grids, policy and economic priorities are shifting from creating more clean energy to creating more energy, period. Projected clean energy additions are simply not enough to meet the runaway demand of the global tech sector, meaning that climate goals could be at risk.
The proliferation of artificial intelligence is causing massive increases in energy demand from data centers, and the areas that host them are struggling to keep up. A 2024 study from scientists at Cornell University found that generative AI systems like ChatGPT use up to 33 times more energy than computers running task-specific software. As a result, it is estimated that each AI-powered internet query consumes about ten times more energy than traditional internet searches. But these numbers are just our best guess – we don’t really know how much energy AI is sucking up, because the companies who are piloting AI platforms aren’t sharing those numbers.
But we know that the overall picture is pretty grim. Last year, Google stated that the company’s carbon emissions had skyrocketed by a whopping 48 percent over the last five years. “AI-powered services involve considerably more computer power - and so electricity - than standard online activity, prompting a series of warnings about the technology's environmental impact,” the BBC reported last summer. While Google hasn’t publicly revised its goal of becoming carbon neutral by 2030, the tech firm has admitted that "as we further integrate AI into our products, reducing emissions may be challenging."
Already, the uptick in energy demand from data centers is causing new plans for gas- and coal-powered plants as well as extending the life of existing fossil fuel operations across the United States. Utility Drive reports that “at least 17 fossil fuel generators originally scheduled for closure [are] now delaying retirement” due to data center demand, and that “utilities in Virginia, Georgia, North Carolina and South Carolina have proposed building 20,000 MW of new gas power plants by 2040” for the same reasons.
The issue is particularly acute in the Southeast. Major utilities in Virginia, North Carolina, South Carolina and Georgia project that they will collectively add 32,600 MW of electrical load over the next 15 years. The Institute for Energy Economics and Financial Analysis reports that in Virginia, South Carolina and Georgia, “data centers are responsible for 65% to more than 85% of projected load growth.”
However, it could be the case that this projected demand growth is overblown, and that states will add extra gas power capacity – and therefore extra greenhouse gas emissions – unnecessarily. Because the competition for energy sources is so fierce between data centers, the project managers of new centers are likely to reach out to many different power providers at once with speculative connection requests, creating redundancies and a compounding issue of “phantom data centers.” This inflates demand and makes accurate projecting extremely difficult.
A study published last year by Lawerence Berkley National Lab calculated exactly how big the phantom data center issue might be, and they found that projected energy demand could be as much as 255 terawatt-hours of energy higher than real energy demand. That’s enough energy to provide power to more than 24 million households.
However, it’s not in utilities’ interest to simplify interconnection processes and ferret out phantom data centers. In fact, the panic over rising energy needs from data centers is giving them great leverage to expand their businesses and push through huge fossil-fuel powered energy projects. Plus, while building new plants and extending the lives of old plants is costly, those costs will be borne by the ratepayers.
Consumers across the U.S. – and especially in the data-center-laden Southeast – can expect their energy bills to rise in response. "We are witnessing a massive transfer of wealth from residential utility customers to large corporations—data centers and large utilities and their corporate parents, which profit from building additional energy infrastructure," Maryland People's Counsel David Lapp recently told Business Insider. "Utility regulation is failing to protect residential customers, contributing to an energy affordability crisis.”
By Haley Zaremba for Oilprice.com
Utilities, AI, and the Quiet Raid on Consumers
- Utilities are quietly signing electricity deals with AI firms that shift major capital costs to regular customers.
- Utilities are placing AI-related infrastructure in their regulated rate base, socializing risks and costs while offering AI firms preferential, often secretive, pricing.
Policymakers would be wise to force AI firms to build their own power infrastructure, shielding consumers from excessive costs.
Ok, we are cynical. The current electric utility policy environment is not exactly what you would call a level playing field, fairly balancing corporate and public interests. Quite the contrary. Right now, we have highly profitable (and politically influential) corporations facing underpowered civil servants in diminished regulatory agencies. State regulators are in a position to grant data centers and possibly other enormous users of electricity the opportunity to milk huge subsidies from unsuspecting consumers. How? By putting these vast new power-generating resources in the utility’s rate base, thereby socializing these enormous incremental costs, facilitated by pro-business politicians.
Harvard researcher (Daniel Oberhaus, “How AI Could Be Raising Your Energy Bill, ” Harvard Magazine, July/August 2025) cites more evidence that utilities are making AI power deals whose terms are not public that burden the rest of their customers. One utility plans to build several large power plants to serve a long term contract with an AI site, put the plants in their regulated rate base, but so far, no details on apportionment of costs have been released. Another large utility has been accused of offering a cut-rate deal to an AI firm with the full expectation that the rest of its customers would make up the profit differential. Stated simply, residential utility customers would be subsidizing corporate or AI electricity usage. In addition, several AI centers announced deals in which they would take the output of existing deregulated stations. Those are perfectly above-board transactions, but not neutral to consumers who have to finance new power stations at current, relatively high prices to replace the output taken by AI. Just a guess, but we think that if AI adds 10% to system sales, it will add 30% to the fixed and capital costs of the utility, so if the AI firm gets a discount, who pays the higher costs? You guessed it.
Next, let’s consider a few wild thoughts.
For instance, might we be in an AI bubble, on par with the dot.com bubble and the power generator bubble, and way back, the bowling alley bubble? These economic or speculative bubbles burst because actual demand did not materialize to keep up with supply based on overly optimistic forecasts. As a result, entrepreneurs overbuilt or somebody came up with a better or cheaper product. “Of course”, you say, ”this time is different.” But someone always says that.
Let’s consider possibilities. First, the AI providers may have wildly overestimated electricity demand, which will leave a lot of underutilized AI data centers looking for ways to dodge those big power bills. Second, the Chinese will develop cheap, low powered AI related computer chips that make the US version look uneconomical. For example with electric vehicles, Tesla came first but Chinese auto makers have caught up fast and now offer superior products. As Andrew Carnegie supposedly and ungrammatically said, “Pioneering don’t pay.” Third, when quantum computing makes an earlier-than-expected appearance, will all those AI data centers become white elephants?
Mind you, we don’t object to building AI centers. Entrepreneurs should take chances and reap the rewards. We just object to making consumers subsidize this essentially speculative activity via their electric bills. Given the intricacies of the electric network, and cross subsidies in pricing, the divergence in cost between new and old plant, and the political pressure to give large corporations what they want via hidden extra charges in the customer's electric bill, we suggest that there is only one way to protect consumers from what AI will do to the grid. That is by requiring that AI and similar power guzzlers build their own generation and networks. Put all these new expensive generating assets behind the meter so to speak. That means build, not snatch existing stations that consumers will have to replace. That way, data centers will pay full freight and consumers will only have to deal with all the other costs increasingly burdening the utility network.
By Leonard Hyman and William Tilles for Oilprice.com
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