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Democrats Seek to Shield Voters From AI Power Costs
Posted
February 10, 2026
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February 10, 2026
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7:42Now PlayingCheryl McKissick Daniel, chair of the board of McKissick and McKissick and author of the recently published book The Black Family Who Built America, joined Bloomberg Businessweek Daily to discuss the economy, her family-run construction business, which dates back more than 120 years, and the current economic environment for large-scale construction.
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Data centers are proliferating in Virginia and a blind man in Baltimore is suddenly contending with sharply higher power bills.
The Maryland city is well over an hour’s drive from the northern Virginia region known as Data Center Alley. But Kevin Stanley, a 57-year-old who survives on disability payments, says his energy bills are about 80% higher than they were about three years ago. “They’re going up and up,” he said. “You wonder, ‘What is your breaking point?’”
It’s an increasingly dramatic ripple effect of the AI boom as energy-hungry data centers send power costs to records in much of the US, pulling everyday households into paying for the digital economy.
The power needs of the massive complexes are rapidly driving up electricity bills — piling onto the rising prices for food, housing and other essentials already straining consumers. That’s starting to have economic and political reverberations across the country as utilities and local officials wrestle over how to divvy up the costs. Yet those same facilities are a linchpin of US leadership in the global AI race.
A Bloomberg News analysis of wholesale electricity prices for tens of thousands of locations across the country reveals the effects of the AI boom on the power market with unprecedented granularity. The locations and prices were tracked and aggregated monthly by Grid Status, an energy data analytics platform. Bloomberg analyzed this data in relation to data center locations, from DC Byte, and found that electricity now costs as much as 267% more for a single month than it did five years ago in areas located near significant data center activity.
Listen: Big Take: AI Data Centers Use a Lot of Energy. You May Be Paying for It (Podcast)
About two-thirds of the power consumed in the US runs off of a state or regional grid, where the system operator manages the trading of energy. These wholesale commodity costs are passed on to households and businesses on their utility bills, which then include other charges to maintain and expand the network. That can affect even customers who aren’t in close proximity to a data center, since their energy relies on the same grid.
Every day, wholesale electricity prices are measured in real time by Locational Marginal Pricing points on the power grid, called nodes. LMPs are primarily made up of the cost to produce the energy and congestion. Analyzing data from 25,000 nodes used by seven regional transmission authorities, Bloomberg News estimated how much wholesale prices in the lower 48 states have changed since 2020. Tech companies, now among the biggest and most powerful forces in the world, have staked their future on AI. Data centers — some with a footprint large enough to cover much of Manhattan — are chock full of racks of servers delivering computer power and storage needed to train and run models.
Their power needs are only set to accelerate. In recent weeks alone, Nvidia Corp. said it will invest as much as $100 billion in OpenAI to support new data centers, while Microsoft Corp. struck a multiyear deal worth almost $20 billion to get cloud computing power from Amsterdam-based Nebius Group NV using a New Jersey data center. OpenAI and Oracle Corp. forged a partnership to build 4.5 gigawatts’ worth of data center capacity, enough energy to power millions of American homes.
“The reliability crisis is here now; it’s not off in the distance somewhere,” said Mark Christie, a former chairman of the Federal Energy Regulatory Commission who also served as a long-time Virginia regulator. He said that load forecasts — the expected demand for power on electricity grids — are a key factor pushing up costs, driven by the data center interconnection requests.
The affordability problem extends beyond US borders.
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