Haley Zaremba
Haley Zaremba is a writer and journalist based in Mexico City. She has extensive experience writing and editing environmental features, travel pieces, local news in the…
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By Haley Zaremba – Mar 21, 2026, 12:00 PM CDT
- Explosive AI-driven energy demand is forcing unprecedented investment in new power generation, including fusion.
- Venture capital is increasingly shifting from energy innovation to AI, creating funding tensions.
- AI tools and supercomputing are accelerating fusion research by enabling advanced simulations and plasma control.
Meeting the runaway energy demand of the artificial intelligence boom will require energy buildout and innovation at an unprecedented scale. After decades of plateaued energy growth in the United States, the breakneck expansion of energy-hungry data centers across the nation is pushing the public and private sectors to invest in new energy production and extending the life of existing power plants – and it still won’t be enough.
“There’s no way to get there without a breakthrough,” Sam Altman, co-founder and CEO of ChatGPT firm OpenAI, said at the 2024 World Economic Forum in Davos, Switzerland. “It motivates us to go invest more in fusion,” he continued.
The AI boom has indeed been a major catalyst for nuclear fusion investing, research, and development. Altman’s own fusion startup, Helion Energy, just hit a major milestone earlier this year when it achieved an ultrahot plasma temperature of 150 million degrees. And Helion is far from alone – a whole rash of startups across the globe is increasing the rate and scale of technological breakthroughs in the burgeoning fusion sector. Wall Street has finally gotten behind the next-gen energy technology that was, until recently, thought to be ripped from the pages of science fiction rather than a commercial eventuality.
But the relationship between AI and fusion is complicated. A recent report from the International Energy Agency (IEA) revealed that investors are increasingly funneling money into AI – at the expense of sorely needed energy tech innovation. “After years of growth, energy innovation funding appears to be entering a phase marked by slower growth and shifting priorities,” states the IEA’s The State of Energy Innovation 2026 report. While AI is not the only reason for this decline, the report found that “the share of VC funding for AI rose to almost 30% in 2025, while the share of energy shrank, and large non-specialist VC funds shifted focus from energy to AI.”
On the other hand, AI could also be the secret sauce to finally cracking the code for commercial nuclear fusion. Just this week, the government of the United Kingdom announced that it will invest £45 million (approximately USD $60 million), to build an AI supercomputer with the express purpose of accelerating nuclear fusion research at the UK Atomic Energy Authority’s Culham campus in Oxfordshire. The machine – named Sunrise – is expected to begin operations in June of this year.
“Officials say the machine will help scientists better understand the complex physics at work in fusion reactors,” states an Interesting Engineering report on the cutting-edge system. “By combining advanced computing with artificial intelligence models, the supercomputer could allow researchers to test ideas virtually before building costly experimental systems.” The computer represents just one component of what the UK is touting as an “AI Growth Zone” already expanding at the Culham Science Campus.
The major contribution of Sunrise will be to enable more powerful and efficient modelling, which will reduce costly experiments through the use of ‘digital twins.’ These virtual reactors can test all kinds of real-world scenarios, streamlining the process for enormously expensive fusion lab experiments. “Sunrise will bring [digital testing] capability to fusion by combining high-fidelity simulation with physics-informed AI to develop predictive digital twins that reduce the cost, risk, and time of learning that would otherwise require expensive and time-consuming physical testing,” said Dr. Rob Akers, director of computing programs at the UK Atomic Energy Authority.
While Sunrise is the largest and most powerful computer of its kind, it’s far from the only project applying AI tools to unknot the tricky problem of achieving nuclear fusion here on Earth in a way that is cost-effective and efficient. A new machine learning tool called Diag2Diag has already made forays in this regard. The AI tool can be used to help monitor and control plasma in fusion experiments, and is especially useful in terms of avoiding Edge Localized Mode (ELM), one of the key hurdles between current fusion experiments and real-world applications. ELM is a condition of instability that breaks down the materials surrounding the plasma at the heart of these experiments, causing major and majorly expensive damage for fusion plasma experiments like Europe’s ITER and China’s EAST.
By Haley Zaremba for Oilprice.com
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Haley Zaremba
Haley Zaremba is a writer and journalist based in Mexico City. She has extensive experience writing and editing environmental features, travel pieces, local news in the…
