By Christine Ji
The race for AI supremacy is quickly becoming a race for energy supremacy. As the U.S. lags China in nuclear development, both the government and Big Tech are making a massive new push to close the gap.
The AI boom has sparked renewed interest in nuclear technology to meet the skyrocketing energy needs of data centers.
Investors are paying close attention to the computer-chip war erupting as the U.S. and China race for global leadership in artificial intelligence – yet Wall Street is focused on the wrong battle.
The real winner will come down to something much less flashy: energy. Specifically, nuclear energy.
After all, the most advanced AI chips in the world are useless if you can’t turn them on. Nuclear energy is rapidly becoming one of the foremost solutions to power the AI boom – and prevent impending energy shortages.
The nuclear option
“I think that one of the best sources of data-center electricity is going to be from nuclear power, and of this there is very little doubt,” Richard Windsor, founder of the research firm Radio Free Mobile, told MarketWatch. “If you want reliable electricity without carbon, nuclear is pretty much your only option.”
According to Bank of America, data centers used to power AI globally could use more energy than the entire country of Japan by 2026. According to the research provider BloombergNEF, the amount of electricity flowing through global electricity grids is expected to surge 30% as soon as 2030. Companies like the cloud-infrastructure provider CoreWeave Inc. (CRWV) have identified energy as a critical bottleneck for AI development.
Bank of America research strategist Felix Tran highlighted nuclear energy as an emerging “necessity” for future AI growth due to its low lifetime costs, minimal carbon emissions and continuous baseload power. Windsor emphasized its ability provide continuous, round-the-clock power – something that traditional renewables, such as wind and solar, can’t guarantee.
Most nuclear plants today use fission to split large atoms like uranium to release heat and generate electricity. There are a few small modular reactors (SMRs) in operation in China and Russia, which represent the next generation of advanced, smaller-scale fission technology. But the real “holy grail” will be nuclear fusion, which works by fusing light atoms like hydrogen together at extremely high temperatures to release a massive amount of energy, according to Bank of America.
Read on: Google is making another bet on nuclear energy as it steps up its AI efforts
‘Build, baby, build!’
The U.S. government has picked up on the nuclear opportunity with a sense of increasing urgency as it aims to close a reported 10-to-15-year development gap with China, according to the Energy Department.
While U.S. energy capacity overall has been stagnant for over a decade, China is adding the equivalent of the entire U.S. power capacity to its own grid every 18 months. At the current pace, China could overtake the U.S. in nuclear capacity by 2030, according to BofA’s Tran.
In May, President Donald Trump issued four executive orders aimed at kickstarting nuclear investment. Trump’s July 2025 AI Action Plan emphasized the need to develop AI infrastructure – especially nuclear-energy capabilities – and called on the nation to “build, baby, build!” And nuclear energy was one of the top discussion topics during Trump’s visit to the U.K. this week, as Trump and British Prime Minister Keir Starmer signed a technology partnership involving investments in AI and nuclear power.
Digital infrastructure has become critically intertwined with economic and military power, increasingly aligning public and private nuclear initiatives, Sean Farney, vice president of JLL’s Americas data-center strategy, pointed out. Big Tech companies are increasingly dedicating resources to the development of nuclear energy; Nvidia Corp. (NVDA), Microsoft Corp. (MSFT), Meta Platforms Inc. (META), Amazon.com Inc. (AMZN) and Alphabet Inc. (GOOGL) (GOOG) have all made nuclear-energy investments as they scramble to secure megawatts of power in the race to build the most advanced AI models.
Can nuclear deliver?
Building nuclear infrastructure is no easy feat. While SMRs are cheaper and quicker to build than traditional energy plants, fusion technology is still nascent.
Benjamin Lee, an engineering and computer-science professor at the University of Pennsylvania, sees potential in the technology but acknowledged pragmatic constraints.
“Nuclear is not a near-term solution. It may not even be a medium-term solution,” Lee told MarketWatch. “We don’t have an established industry that knows how to build nuclear on time and on budget.”
By contrast, Tran pointed out that China can build nuclear plants in a three- to five-year time frame.
Strict regulation, high upfront costs and a loss of expertise after a long pause in nuclear-plant building all pose challenges to nuclear development in the U.S. today. However, the urgent nature of the AI race could help alleviate the “tremendously high regulatory hurdle,” according to Farney, as the Trump administration has been pursuing energy deregulation. With increased government support, Farney estimates that the time to deploy SMRs in the U.S. could be cut down from seven years to three.
And with Big Tech companies allocating parts of their massive capital-expenditure budgets to nuclear energy, the industry is seeing a fresh wave of private investment which could accelerate development, according to Lee. It all comes down to “getting a big-enough order book for new nuclear generation,” he said, as repeated construction will be the only way for the U.S. to rebuild its nuclear expertise.
The stakes are high, as both Big Tech’s financial future and U.S. national security are on the line. But Farney is optimistic that the energy industry will achieve a breakthrough.
There’s “a whole lot of money involved,” Farney said, “and an incredible spirit of innovation.”
Also read: To fuel AI’s insatiable appetite, Nvidia and Big Tech are doubling down on nuclear
-Christine Ji
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09-20-25 0800ET
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