Speed, though, is only one of the issues. Once facilities do plug in, neighbors often criticize them for drawing too much electricity and contributing to rising prices. They say the data centers generate more noise than they do long-term jobs, contribute to pollution, and threaten to put people out of work. Organizers stalled over $150 billion worth of projects in 2025, according to Data Center Watch<\/a>, and policymakers alert to the public mood are starting to impose limitations on development. <\/p>\n More than a dozen states are considering bans, and local moratoriums are in effect in places like Minneapolis and DeKalb County in Georgia. At the federal level, the GRID Act, a bipartisan bill in the US Senate, proposes to sever new data centers from public grids entirely. Some operators are already moving that way by trying to develop their own power generation.<\/p>\n Rather than rushing to build new power plants, companies could find part of the solution to the crunch right under our noses\u2014or, more precisely, in the transmission lines under our feet and above our heads. The existing system operates near its full capacity during only a small number of high-demand hours throughout the year. This means, some grid experts argue, that if data centers can limit the power they draw during those stretches, they won\u2019t need to wait for big infrastructure upgrades or build their own off-grid generation.\u00a0<\/p>\n Indeed, a growing number of studies have shown there could be plenty of power available for data centers that can flex. A widely discussed 2025 report from researchers at Duke University<\/a> found that the US grid could offer an additional 76 gigawatts\u2014about 5% of its entire capacity, and about enough to accommodate projected data-center growth in the US through 2030\u2014to facilities that are willing to reduce their usage just 0.25% of the time. That\u2019s about 22 hours a year. And when researchers from Princeton University and two grid-modernization companies looked at locations for new data centers in the PJM region, their report<\/a>, which was funded by Google, found that a 500-megawatt facility capable of flexing for less than 1% of the year could reach full operation three to five years faster than one that\u2019s inflexible.\u00a0<\/p>\n Flexible power connections could also help data centers address some of their PR problems. By decreasing their draw at times of grid stress, for instance, they could avoid diverting power from where it\u2019s most needed, thus boosting stability. By using existing capacity, they might be able to reduce the need for new fossil-fuel power plants and spread fixed costs over more electricity users, pushing prices down.\u00a0<\/p>\n The AI power pinch is attracting resources and research into strategies for grid flexibility overall, which could help negotiate a tricky period: Taken together with electric vehicles, air-conditioning, and other sectors, data centers are helping drive what analysts predict will be a 25% increase<\/a> in US electricity demand by 2030 compared with 2023 levels. <\/p>\n Ideally, flexibility gives grid operators more control over the flow of electrons, making them leaders of a harmonious ensemble rather than hostages to inflexible electricity requirements. That will help them manage demand spikes across the entire system and deal more effectively with the intermittent nature of renewables like wind and solar. \u201cDemand flexibility is incredibly useful for power grids,\u201d says Johanna Mathieu, a grid expert at the University of Michigan. \u201cIt helps reduce electricity costs and improve grid reliability.\u201d<\/p>\n But while advocates see plenty of benefits, the concept brings complexity. For data centers, compromising on energy needs can be a hard sell. Flexibility requires utilities and grid operators, which tend to be operationally conservative, to change long-held practices. And some skeptics also say that flexibility distracts from the very real need to build more grid infrastructure faster, and could even pose risks to our electricity supply.\u00a0<\/p>\n Still, some technologists, grid operators, and utilities are hoping to show that flexibility works\u2014not only in white papers or simulations but in real life.\u00a0<\/p>\n The poster children for data-center growth default toward in<\/em>flexibility. Hyperscalers like Microsoft and Oracle have proposed enormous new centers, many of which would rely on off-grid, natural-\u00adgas-burning power plants. When xAI wanted to speed up the buildout of the Colossus site outside Memphis, Tennessee, it rolled up with gas turbines on flatbed trucks. The facility, now in operation, is facing blowback from regulators and residents about the spike it\u2019s causing in emissions and other pollution. In any case, there aren\u2019t enough gas turbines worldwide to meet the demand from data-center operators.\u00a0<\/p>\n One big obstacle for anyone demanding a lot of power is that our grids are mostly rigid. They\u2019re designed to supply enough power to meet total demand when it\u2019s highest, even if that\u2019s for only a relatively small number of hours a year. That conservative approach is a simple route to reliability, but it means that the grid has quite a bit of headroom. \u201cThe grid is already overbuilt by a lot. If you were an airline running at 30% utilization, you would not buy more planes,\u201d says Amit Narayan, the cofounder and CEO of GridCare, a company developing flexibility technologies, referring to a 2025 Stanford study<\/a> of transmission lines in western North America. \u201cIf you are running a grid at 30% utilization, there\u2019s no scientific reason you can\u2019t go to 60.\u201d\u00a0<\/p>\n \u201cIf you were an airline running at 30% utilization, you would not buy more planes. If you are running a grid at 30% utilization, there\u2019s no scientific reason you can\u2019t go to 60.\u201d<\/strong><\/p>\n<\/blockquote>\n To be fair, the idea of flexibility isn\u2019t entirely foreign to grid operators. For decades, they\u2019ve practiced a technique called demand response: When it looks as if demand will get too close to supply, as it might during a heat wave when many people turn on the AC at the same time, they call large commercial or industrial facilities and ask them to shut down parts of their operations. This method can help avoid the need to fire up so-called peaker plants, which run on fossil fuels, but it\u2019s slow, imprecise, and hard to scale.<\/p>\n In the 2000s, as the adoption of technologies like electric cars and solar panels presented new challenges, more internet-\u00adconnected grids also provided new means of flexibility. Virtual power plants, or VPPs, offered a smarter, faster, more granular alternative. Electricity customers ranging from factories to homeowners with smart thermostats, solar panels, or big batteries would allow the utility to adjust their draw to help meet demand\u2014often getting paid for their (frequently unnoticed) trouble.\u00a0<\/p>\n After the generative AI boom began with the release of ChatGPT in 2022, some companies began to see flexibility as a way to get data centers set up more easily, efficiently, and affordably. If they bring AI money into existing grids and reduce or defer the need for expensive upgrades, data centers could actually help spread out fixed costs so as to lower rates for other users. A study from Duke University published this past February, for instance, found that flexibility could reduce rates by 0.5% to 2.8%<\/a>.\u00a0<\/p>\n The trick is figuring out how data centers, notorious power hogs, can keep operating when their flexible connections are throttled. Flexibility specialists envision three possible ways. The simplest is for the new data center to install on-site backup power storage or generation to tap when the grid is maxed out\u2014at their own expense, of course.<\/p>\n A facility could also fill the gap by drawing on a VPP. The utility would turn down the electricity going to users who signed up for the VPP, and the data center would pay them for their flexibility. This method wouldn\u2019t require any major infrastructure, but it would require the utility to have a big VPP program and to coordinate the exchange at a time when the grid was under stress. While VPPs exist to some extent in nearly 40 states, the rules governing them vary widely, and they are empowered to do more in some areas than in others.\u00a0<\/p>\n Finally, a data center could simply use less power at peak times. The conventional wisdom is that they won\u2019t go for such limits, particularly when every number-\u00adcrunching server can feel like a goose potentially laying little golden eggs. But some experts are betting that the value of getting up and running quickly is enough to change their minds. \u201cThere is a clear and growing trend,\u201d says Ayse Coskun, chief scientist at Emerald AI. \u201cOperators are increasingly willing to trade some level of flexibility for faster grid interconnection.\u201d\u00a0<\/p>\n GridCare, a startup based in Silicon Valley, was one of the first companies to use flexibility to get data centers online quickly. Instead of looking at grids only in worst-case scenarios when electricity demand is highest, the company analyzes the system under all conditions, explains CEO Narayan, who studied smart grids at Stanford. It feeds every part of the grid\u2014including power plants, lines, substations, and homes\u2014into a generative AI model that creates a \u201cdigital twin\u201d for different grid configurations. It then picks out results that could unlock capacity while maintaining reliability, and it feeds those into another model trained on the physics of electrical components like resistors and capacitors to make sure they\u2019re realistic.<\/p>\n GridCare found its first customer in the Silicon Forest, an area in the Pacific Northwest named for the trees that dominate the landscape and the IT industry that has more recently sprouted up there. The local grid needed more capacity to support more data centers. \u201cData centers wanted \u2018speed to power,\u2019\u201d says Isaac Barrow, a manager of data-center relations at Portland General Electric, or PGE, the local power generator and distributor, \u201cbut transmission buildout is a long process that\u2019s very costly.\u201d<\/p>\n In 2024, Aligned Data Centers came to PGE wanting to expand its operation in Hillsboro, Oregon, and PGE followed a recommendation from GridCare. Aligned will install a 31-megawatt battery, set to be in service in May 2027, and decrease its draw by up to that amount when the grid becomes congested. Bundled with other flexibility measures, that battery has allowed PGE to increase the capacity it can offer Aligned and other nearby operators by 80 megawatts without any new power plants. Though the buildout of data centers in Hillsboro has faced plenty of pushback from locals, Barrow points out that it could have the knock-on effect of lowering costs for ratepayers, because it spreads out the tab.<\/p>\n Other companies are promoting different flavors of flexibility. Google has been moving processing loads<\/a> from facilities in areas experiencing demand spikes to those in less stressed spots since 2023. It\u2019s signed agreements with five utilities<\/a>, including the Tennessee Valley Authority and Indiana Michigan Power, that add as much as a gigawatt of flexibility.\u00a0<\/p>\n Voltus, a major VPP provider across the US and Canada, markets a \u201cbring your own capacity\u201d program in which a data-\u00adcenter company can fund a VPP nearby. The grid operator can use the VPP to decrease demand at busy times, and participants get a financial thank-you. \u201cWe can spin up new VPPs on the order of months,\u201d says Emily Orvis, Voltus\u2019s vice president of energy markets. In June, the company signed their first such data-center deal<\/a>: a three-year plan in which Google will bankroll a VPP in the PJM interconnection.<\/p>\n Of all the approaches to flexibility, Emerald AI\u2019s may be the most ambitious: asking data centers to dial into the grid\u2019s needs. The company\u2019s Conductor software, which can run on premises or in the cloud, builds on the research of chief scientist Coskun. Her group at Boston University showed in a pair of 2013 papers that a data center could watch the grid and help balance big power fluctuations, such as the intermittent effects of solar and wind power. By 2022, she and her colleagues had tested their methods on a cluster of 36 research servers<\/a> and shown that the system could respect power limits without breaking the processes it was running.\u00a0<\/p>\n One of the most important questions for Conductor is deciding which AI processes can be slowed down to save energy without kneecapping performance. A lot of companies label their jobs by priority\u2014a real-time chatbot query, for instance, might outrank something like a web search that\u2019s part of a deep research project. When they don\u2019t, Emerald AI tries to infer priority from the nature of the job. Conductor then analyzes the AI workload to determine how tweaking the power to a given processor will affect the performance and help meet the usage limits set by the grid operator. <\/p>\n \u201cThe performance curve changes for different kinds of workloads,\u201d says Coskun. \u201cEach AI job is going to have a different location on that curve. Our intelligence is figuring out where you are on that curve.\u201d\u00a0<\/p>\n Last year, Emerald AI began assessing the technology\u2019s readiness for real-world use in a series of tests, raising the difficulty each time. The trials were carried out in partnership with the Data Center Flexible Load Initiative\u2014a collaboration among tech companies like Google and Nvidia, utilities like Duke Energy, and grid operators like PJM that aims to help establish a repeatable framework<\/a> for power-\u00adflexible data centers.<\/p>\n The first challenge was in Phoenix, a fast-growing computing hub. For the test, Conductor took control of a group of server racks laden with 256 Nvidia A100 GPUs\u2014hardware that can use about as much power as around 170 US homes. When presented with a simulation of a busy grid, Conductor reduced the power to the chips by 25% for three hours, while maintaining acceptable computing performance. Emerald AI and its partners reported the results in a paper in Nature Energy<\/em><\/a> in December 2025.<\/p>\n The next trial forced the system to juggle surprise grid fluctuations without advance warning and redirect AI jobs from a data center in Virginia to a less busy one in Chicago. Then, in London, Conductor took the reins of equipment beyond the main GPU processors and faced a more complicated mix of fluctuations, including very short and long bouts of congestion\u2014plus the notorious teakettle effect.<\/p>\n The progress so far shows that flexibility can work, at least in some situations, but only a small fraction of operators have pursued it as yet. \u201cWe\u2019re just in the beginning innings of the game,\u201d says Jesse Jenkins, one of the authors of the 2025 Princeton study and cofounder of Firma, a startup that works on data-center flexibility. \u201cPeople are recognizing that this is a potential solution. The motivation is there; there are some bespoke examples. But there\u2019s no uniform solution set that\u2019s the default option, which is where we need to get.\u201d<\/p>\n While data centers are going up across the US, no place on Earth comes close to the accumulated computing muscle in Northern Virginia\u2019s Data Center Alley. The region is home to around 500 compute-crunching facilities, which represent 13% of the entire world\u2019s capacity; the next two hot spots, Beijing and Oregon, contain 6% each.<\/p>\n
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