Big Tech Commits $16B+ to Nuclear Power for AI Data Centers

Tech companies are becoming power companies

Microsoft is spending $16 billion to restart the Three Mile Island nuclear reactor in Pennsylvania, renamed the Crane Clean Energy Center, with all its electricity dedicated to powering the company's AI data centers when it comes back online in late 2027. The 20-year contract marks a dramatic reversal for a facility whose sister reactor nearly melted down in 1979, effectively halting new nuclear construction in America for four decades.

The Microsoft deal is part of a broader pattern. Every major AI company—Microsoft, Google, Amazon, and Meta—has signed at least one nuclear agreement in 2026, committing to more than a dozen deals worth nearly 10 gigawatts of combined capacity, enough to power roughly 7 million homes, according to reporting first published by Forbes contributor Ken Silverstein. In June, the U.S. and Canada each announced plans to build 10 new reactors, the largest coordinated nuclear push North America has seen in decades.

Meta has signed agreements for up to 6.6 gigawatts of nuclear power. Google has struck deals with two nuclear developers plus a separate 1,800-megawatt contract. Amazon has invested $700 million in X-energy to build up to a dozen small modular reactors—compact, factory-built units designed for faster, cheaper deployment than traditional plants.

Why it matters

AI data centers require constant, uninterrupted electricity 24 hours a day, making nuclear power's reliability uniquely valuable compared to weather-dependent solar and wind. Global electricity demand is projected to grow by more than 10,000 terawatt-hours by 2035, with data centers driving over a fifth of that growth in wealthy countries by 2030. By decade's end, AI data processing in the U.S. is expected to consume more power than the country's aluminum, steel, cement, and chemical industries combined. Tech companies are now directly financing power generation because traditional utilities and government efforts failed for 40 years to make new nuclear construction economically viable.

The economics and timeline challenges

Rafael Mariano Grossi, who leads the International Atomic Energy Agency, told UN News that "only nuclear energy can meet the five needs of low-carbon power generation, round-the-clock reliability, ultra-high power density, grid stability and true scalability."

Yet critics question whether these investments match reality. Researchers Molly Langabeer and M.V. Ramana argued in the Bulletin of the Atomic Scientists that nuclear power "will be unable to provide any significant boost to the electricity consumption of data centers anytime soon—especially within the next several years, when AI-related energy demand is expected to increase most rapidly."

A single new reactor costs billions and takes nearly a decade under ideal conditions. The last large-scale U.S. reactors completed were Georgia's Plant Vogtle Units 3 and 4, finished in 2023 and 2024—seven years late and $36.8 billion over budget, more than double the original estimate.

Most tech company investments target small modular reactors, none of which have been completed commercially in the U.S. The Department of Energy pledged up to $17.5 billion in loans for 10 new reactors in June, with construction targeted to start by 2030.

Restarts versus new builds

The distinction matters: reactor restarts like Three Mile Island can return to service in two to three years, not ten. These provide near-term capacity while new construction remains a longer-horizon bet. Natural gas will likely fill gaps in the interim.

What has fundamentally changed is that AI's energy demands have made both restarts and new builds financially viable for the first time in four decades, backed by real capital and political support. As Grossi noted, AI technology advancement and nuclear reactor construction are now moving in tandem globally.

The country or company that pairs AI computing power with reliable, carbon-free electricity fastest may determine not just the future of energy infrastructure, but leadership in artificial intelligence itself.

These details were first reported by Ken Silverstein in Forbes.