AI Agents Are Thirsty for Power

What happened

Welcome back to Power Play! Each week, senior writer Molly Taft tackles a topic around this midterm season’s biggest issue: data centers. 76. ” 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.

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. ” Well, one human employee.

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of agents running on closed models, noted that Hausfather made a good effort, but that his math was based on somewhat outdated findings.

Why it matters

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average user search for recipes or look up places to visit on a vacation; simple chatbot queries are an increasingly outdated way of thinking about how AI works.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. ” Agents are now at the heart of the frontier labs’ work on AI. They’re doing some astounding—and terrifying—things. 7 million messages had solved a longstanding math problem.

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.

What to watch

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.