AI Agents Are Thirsty for Power | WIREDSkip to main contentMenuWIREDSECURITYPOLITICSTHE BIG STORYBUSINESSSCIENCECULTUREREVIEWSMenuWIREDAccountAccountNewslettersSecurityPoliticsThe Big StoryBusinessScienceCultureReviewsChevronMoreExpandThe Big InterviewMagazineEventsWIRED InsiderWIRED ConsultingNewslettersPodcastsVideoLivestreamsWIRED StoreSearchSearchMolly TaftScienceSep 13, 2026 6:00 AMAI Agents Are Thirsty for PowerSilicon Valley is shifting away from chatbot queries toward a future filled with resource-intensive agentic AI—and it's driving the data center buildout.Photo-Illustration: Wired Staff; Getty ImagesCommentLoaderSave StorySave this storyCommentLoaderSave StorySave this storyWelcome back to Power Play! Each week, senior writer Molly Taft tackles a topic around this midterm season’s biggest issue: data centers. If you’ve got a question or thought for the column, feel free to shoot Molly an email at [email protected] or reach them securely on Signal at mollytaft.76.“What on earth are they building all of these data centers for?” an exasperated friend asked me recently.They’re not the only one asking: We got several similar questions on our recent data center livestream. It’s a really reasonable thing to wonder about. After all, if AI is already making all these breakthroughs, why are tech companies taking on billions of dollars of debt and constructing some of the biggest power plants in the world to build even more data centers?The answer isn’t to help the average user search for recipes or look up places to visit on a vacation; simple chatbot queries are an increasingly outdated way of thinking about how AI works. Now, AI is all about agents—there’s no official definition, but roughly speaking, agents are large language model-based systems designed to make autonomous decisions to execute a task—and the shift towards them is part of what’s driving Silicon Valley’s power buildout.“Rather than asking an AI chatbot a simple question and answer, these agents can give themselves hundreds of small prompts based on a user’s original question,” says my colleague Maxwell Zeff, who writes the weekly Model Behavior newsletter. “For example, if someone asked an AI agent to build them a website, it might run for hours to build out features, re-prompting itself dozens of times in the process to build different web pages, menus, and datasets that power the thing.”Agents are now at the heart of the frontier labs’ work on AI. They’re doing some astounding—and terrifying—things. Recently, OpenAI announced that a swarm of more than 10,000 agents sending 2.7 million messages had solved a longstanding math problem. (Mathematicians pushed back on the company’s claims.) While this is an outlier—AI labs are highly committed to solving supposedly unsolvable problems, and willing to throw unusual amounts of resources into doing so—all those messages burned through a lot of processing power. That equates to a lot of energy: probably tens of millions of dollars’ worth, Max tells me, though how much exactly is tough to say.Private AI companies have historically been choosy about what to disclose when it comes to environmental metrics around their products. Many CEOs often point to single queries made by individuals as a measure of resource use. In a recent podcast interview, OpenAI CEO Sam Altman claimed that the water use needed to harvest a single almond amounted to 38,000 ChatGPT queries. (The calculation has been disputed.)“The people that are scarfing down 12 almonds at a time don't feel like they're doing something horrible from a water perspective for the most part,” he said.Introducing AI agents, which are much more energy-intensive than simple queries, into the picture makes these calculations a lot more complex. There’s a major dearth of information around the energy use of agents, whose tasks can range from simple jobs to a full day of autonomous coding involving a team of parallel “helper” agents. There’s a massive gulf in power use between these applications—and a potentially limitless expansion as tasks get more complex.“In other technological growth areas, we're constrained by how many people are driving a car or streaming Netflix,” says Boris Gamazaychikov, the co-founder and CEO of Sustainable AI, a research and advisory group. “Now, this stuff is kind of decoupled from users—and if you listen to AI leaders, I think that’s what they want. They’re talking about unicorns that have one employee.”Well, one human employee. In that imagined world, there could be hundreds or even thousands of AI agents working in the background. I don’t want to debate the odds of that happening, but suffice to say that’s the future AI companies are working toward—and it helps to explain the rush to build data centers.With little reliable data coming from the companies about their energy use, some AI enthusiasts are trying to do the math themselves. Last month, climate scientist Zeke Hausfather authored a blog post calculating how much energy his own AI use—which leans heavily on agents—consumes. He used a variety of different sources to work out that his average daily Claude session may consume more than the energy needed to power two refrigerators. (Gamazaychikov, whose group will release research later this month with more precise calculations around the environmental footprint of agents running on closed models, noted that Hausfather made a good effort, but that his math was based on somewhat outdated findings. That’s unsurprising, given how little academic work there has been done on this topic and how opaque tech companies are when it comes to disclosing emissions metrics.)Hausfather concludes that in the grand scheme of his personal life, his AI use being on par with keeping a few spare fridges running isn’t a world-ending number. But this AI use “also represents a net new source of emissions, at a time when global temperatures are skyrocketing and our emissions reduction goals are increasingly off track,” he writes. And it’s a lot bigger than the fraction-of-an-almond-sized numbers Altman is throwing around as a metric.Hausfather says he uses AI and agentic tools “more than most people,” but that could change soon. Last week, Meta rolled out a personal AI agent that, the company said in a press release, is “built to work for billions of people worldwide.” Dubbed Muse, Meta trumpeted that it will maintain a “dedicated computer in the cloud” for each user that would work even when the user is offline; the company plans to integrate Muse with its AI glasses later this year. It is very possible that in the near future, Meta users toying around with their glasses or fussing around on Facebook may be outsourcing tasks to agents without realizing what they’re doing.Again, when compared to things like taking regular flights or eating beef every day, the carbon footprint for personal agentic use is still relatively small. But if Meta envisions a future where everyone’s using an agent, it explains the massive scale of some of the data centers they’re building—like the Hyperion project in Louisiana, which will be powered by 10 natural gas plants.“The technology that’s going to be trained by the data centers that are being proposed and built right now is three to five years away,” Gamazaychikov says. “It’s going to be a very different flavor than just the chatbot window.”What You’re AskingA reader asks: Would small nuclear power plants work for data centers?The short answer is that yes, small nuclear power plants could be a great choice for carbon-free power for data centers. A number of startups and data center developers envision a futuristic utopia where data centers are happily coupled with what are known as small modular reactions running off the electric grid.The problem (as always with nuclear) is how long that might take: No small modular reactors are operating commercially in the US, and just one model has been licensed for sale, despite decades of development. The Trump administration is trying to help the industry mature more rapidly, including creating a pilot project in the Department of Energy for 11 startups to hit a key milestone this year. At least a handful have succeeded in reaching that milestone. Now, they begin the long journey to bring their products to market.But many data center developers don’t want to wait years for these companies to prove themselves, so they’re installing gas turbines now. In other words, they’re not waiting for utopia to come around. We’ll see what happens in the next few years!What We’re ReadingFor Scientific American, Austyn Gaffney travels to Memphis to document the backlash against SpaceX’s data centers.The Wall Street Journal reports on how some states that gave out tax breaks for data centers are now walking back on those deals.Texas’s KERA News covers how data centers are making some Republican voters consider leaving the party.CommentsBack to topJoin the discussionCommentsBack to topTriangleYou Might Also LikeIn your inbox: WIRED's most ambitious, future-defining storiesAI slop backlash is actually having an impactBig Story: The cop who took on FlockThe rise of the 1am job interviewWatch: I stole a car by hacking this hidden deviceMolly Taft is a senior writer for WIRED, covering climate change, energy, and the environment. Previously, they were a reporter and editor at Drilled, an investigative climate multimedia reporting project. Before that, they wrote about climate change and technology for Gizmodo, and served as a contributing editor for the New ... 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The country’s AI ambitions hang in the balance.Joel KhaliliOpenAI Is Developing a ‘Persistent’ AI AgentCode reviewed by WIRED reveals the company is developing a feature that enables Codex to continue working proactively until it is “put to sleep.”Maxwell ZeffClearview AI Is Testing an AI Tool That Would Let Cops Unearth Your Life OnlineInquiryIQ, a previously unreported prototype, tested a model from xAI, maker of Grok, to surface associates, social accounts, and other information about people identified through Clearview.Dhruv MehrotraOne of AI’s Fiercest Critics Says All the Doom Talk Is ‘Meant to Distract Us’Timnit Gebru argues that AI companies are stoking fears of extinction to avoid discussing actual harms, like autonomous weapons.Lauren GoodeTech Visionary Says the Big AI Labs Don’t Get What People WantTim O’Reilly built a publishing empire that AI is helping to destroy. Yet he loves AI—as long as it’s open source.Steven LevyPangram Has Emerged as the Gold Standard of AI Detection. Should You Trust It?Meet the AI police who can make or break careers—in publishing and beyond.Lexi PandellCandidates Are Signing a Pact Promising Action on Data Centers and AI SafetyMore than 15 politicians from across the country have signed on to the AI Pact, vowing to regulate data centers and AI. “We’ve got to get this right,” says Senate candidate Dan Osborn of Nebraska.Molly TaftWIRED is obsessed with what comes next. Through rigorous investigations and game-changing reporting, we tell stories that don’t just reflect the moment—they help create it. When you look back in 10, 20, even 50 years, WIRED will be the publication that led the story of the present, mapped the people, products, and ideas defining it, and explained how those forces forged the future. 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The development of agentic artificial intelligence is driving significant demand for computing power, fundamentally shifting the focus in Silicon Valley away from simple chatbot queries toward resource-intensive agentic systems and the corresponding expansion of data center infrastructure. These agents are defined as large language model-based systems designed to autonomously make decisions to execute complex tasks. Unlike traditional chatbots that respond to single queries, agents can generate numerous prompts and iteratively re-prompt themselves to achieve complex goals, such as developing a website by building out various features and datasets over time. This capability to self-direct and execute multi-step procedures is central to the current push for physical power buildout.

The utilization of these agents, particularly in frontier laboratory research, results in substantial energy consumption. For instance, one reported example involved a swarm of over ten thousand agents processing millions of messages to solve a mathematical problem, which consumed an estimated amount of energy equivalent to tens of millions of dollars. This highlights a major information gap regarding the energy footprint of agents, as private AI companies have historically provided ambiguous environmental metrics, often focusing on single queries rather than aggregate resource usage. This lack of transparency complicates environmental accountability when assessing the power demands of these advanced applications.

The potential for autonomous agents to operate in the background suggests a future where tasks are decoupled from direct human interaction, potentially allowing for hundreds or thousands of agents to work concurrently to achieve objectives. This vision of highly distributed, autonomous AI is reflected in infrastructure planning, such as the Hyperion project in Louisiana, which is planned to be powered by ten natural gas plants to support vast data center operations. While some calculations based on personal AI agent use, as performed by climate scientist Zeke Hausfather, suggest that personal AI usage consumes energy comparable to running several refrigerators, the systemic environmental impact of widespread agentic deployment must be considered against the backdrop of skyrocketing global temperatures and emission reduction goals.

The infrastructure debate also involves potential power solutions for these data centers. There is interest in exploring small modular nuclear reactors as a carbon-free power source for data centers, though the practical implementation faces challenges, including the slow pace of commercial deployment and the need for regulatory processes, as evidenced by the ongoing efforts by the Trump administration to facilitate pilot projects. In the interim, many developers are opting for existing solutions, such as gas turbines, rather than waiting for advanced nuclear technology to mature.

Beyond energy consumption, the broader context involves concerns over AI safety and regulation. There is a philosophical debate among AI leaders regarding the motives behind public discourse on AI risks, with some critics suggesting that fear is intentionally stoked to deflect from actual harms, such as the development of autonomous weapons. This tension is reflected in ongoing efforts, such as the AI Pact signed by numerous politicians, which aims to establish regulatory frameworks for data centers and AI safety. Furthermore, internal concerns exist regarding the automation of technical roles within data centers, as companies are testing robots to perform tasks like cable swapping and server maintenance, which raises concerns among some workers about job security.