The White House Tells Tech Giants to Pay Their Own Power Bills

When President Donald Trump took the podium for his State of the Union address this week, he delivered an unexpected message to the tech industry: the party’s over on free electricity. The proliferation of AI data centers has driven up the average national electricity price by more than 6% in the last year, and the White House has had enough.

“We’re telling the major tech companies that they have the obligation to provide for their own power needs. They can build their own power plants as part of their factory, so that no one’s prices will go up.” — President Donald Trump

The Data Center Dilemma

The AI boom has created an unprecedented demand for computing power. Hyperscale data centers—massive facilities housing tens of thousands of servers—are springing up across the country to train and run large language models. Each facility consumes as much electricity as a small city, and the strain is showing on the national grid.

For consumers, the impact has been immediate and measurable. Average electricity prices have climbed more than 6% nationally, with some regions experiencing even sharper increases. In an election year, that’s a politically toxic combination: voters paying more for power while tech giants report record profits.

The Corporate Response

Microsoft was first out of the gate. On January 11, the company announced a policy “to ensure that the electricity cost of serving our datacenters is not passed on to residential customers.” The move was widely seen as preemptive, an attempt to get ahead of regulatory pressure.

OpenAI followed on January 26, committing to “paying its own way on energy, so that our operations don’t increase your energy prices.” The pledge came as the company continues its aggressive expansion, with plans for multiple new data center complexes.

Anthropic made a similar commitment on February 11, promising to “cover electricity price increases that consumers face from our data centers.” The company’s Claude AI has become one of the most popular alternatives to ChatGPT, driving significant infrastructure demands.

Google announced the largest battery project in the world this week to support a data center in Minnesota—a clear signal that the company is preparing for a future where it must generate and store its own power.

“A handshake agreement with Big Tech over data center costs isn’t good enough. Americans need a guarantee that energy prices won’t soar and communities have a say.” — Senator Mark Kelly (D-AZ)

Questions Remain

What these commitments mean in practice remains unclear. The White House has not released the text of the proposed pledge, and critical questions about enforcement and measurement are unanswered. Who will determine which data centers are responsible for which price increases? How will costs be calculated and allocated?

Next week, representatives from Amazon, Google, Meta, Microsoft, xAI, Oracle, and OpenAI are expected to formally sign the pledge at the White House. However, none of the companies have confirmed their attendance, leaving room for last-minute changes.

Even if tech companies commit to taking on electricity costs, on-site power plants may not be a complete solution. They can still have adverse environmental impacts and will stress supply chains for natural gas, turbines, photovoltaics, and batteries, depending on how companies aim to power their compute.

The Road Ahead

The episode highlights a broader tension in the AI era: the technology’s benefits are distributed globally, but its costs—environmental, financial, and social—are often borne locally. Communities hosting data centers get the traffic and infrastructure strain without necessarily sharing in the economic upside.

For the tech industry, the White House’s intervention represents a new phase of accountability. The days of unlimited, cheap power for AI training may be coming to an end. Companies will need to factor energy costs—and their political implications—into their expansion plans.

As one industry observer noted, this could be the beginning of a fundamental shift in how AI infrastructure is built and powered. The companies that adapt fastest may find themselves with a significant competitive advantage—not just in cost structure, but in public perception and regulatory relationships.

This article was reported by the ArtificialDaily editorial team. For more information, visit TechCrunch.