The aroma of hay and manure hangs over Culpeper County, Virginia, where there’s a cow for every three humans. “We’ve got big farms, most still family-owned, and a lot of forests,” says Sarah Parmelee, one of the county’s 55,000 residents. “It’s very charming small-town USA,” she adds.
But this pastoral idyll is in the middle of a twenty-first-century shift. Over the past few years, the county has approved the construction of seven large data-centre projects, which will support technology firms in their expansive plans for generative artificial intelligence (AI). Inside these giant structures, rows of computer servers will help to train the AI models behind chatbots such as ChatGPT, and deliver their answers to what might be billions of daily queries from around the world.
In Virginia, the construction will have profound effects. Each facility is likely to consume the same amount of electrical power as tens of thousands of residential homes, potentially driving up costs for residents and straining the area’s power infrastructure beyond its capacity. Parmelee and others in the community are wary of the data centres’ appetite for electricity — particularly because Virginia is already known as the data-centre capital of the world. A state-commissioned review, published in December 2024, noted that although data centres bring economic benefits, their growth could double electricity demand in Virginia within ten years1.
“Where is power going to come from?” asks Parmelee, who is mapping the rise of data centres in the state and works for the Piedmont Environmental Council, a non-profit organization headquartered in Warrenton, Virginia. “They’re all saying, ‘We’ll buy power from the next district over.’ But that district is planning to buy power from you.”
Similar conflicts about AI and energy are brewing in many places around the globe where data centres are sprouting up at a record pace. Big tech firms are betting hard on generative AI, which requires much more energy to operate compared with older AI models that extract patterns from data but don’t generate fresh text and images. That is driving companies to collectively spend hundreds of billions of dollars on new data centres and servers to expand their capacity.
From a global perspective, AI’s impact on future electricity demand is actually projected to be relatively small. But data centres are concentrated in dense clusters, where they can have profound local impacts. They are much more spatially concentrated than are other energy-intensive facilities, such as steel mills and coal mines. Companies tend to build data-centre buildings close together so that they can share power grids and cooling systems and transfer information efficiently, both among themselves and to users. Virginia, in particular, has attracted data-centre firms by providing tax breaks, leading to even more clustering.
“If you have one, you’re likely to have more,” says Parmelee. Virginia already has 340 such facilities, and Parmelee has mapped 159 proposed data centres or expansions of existing ones in Virginia, where they account for more than one-quarter of the state’s electricity use, according to a report by EPRI, a research institute in Palo Alto, California2. In Ireland, data centres account for more than 20% of the country’s electricity consumption — with most of them situated on the edge of Dublin. And the facilities’ electricity consumption has surpassed 10% in at least 5 US states.
Complicating matters further is a lack of transparency from firms about their AI systems’ electricity demands. “The real problem is that we’re operating with very little detailed data and knowledge of what’s happening,” says Jonathan Koomey, an independent researcher who has studied the energy use of computing for more than 30 years and who runs an analytics firm in Burlingame, California.
“I think every researcher on this topic is going crazy because we’re not getting the stuff we need,” says Alex de Vries, a researcher at the Free University of Amsterdam and the founder of Digiconomist, a Dutch company that explores the unintended consequences of digital trends. “We’re just doing our best, trying all kinds of tricks to come up with some kind of numbers.”
Content retrieved from: https://www.nature.com/articles/d41586-025-00616-z.
