• AI models consume tons of energy and increase greenhouse gas emissions.
• Tech firms and governments say an energy revolution must happen to match the pace of AI development.
• Many AI leaders are rallying around nuclear energy as a potential solution.

Advances in AI technology are sending shockwaves through the power grid.

The latest generation of large language models requires significantly more computing power and energy than previous AI models. As a result, tech leaders are rallying to accelerate the energy transition, including investing in alternatives like nuclear energy.

Big Tech companies have committed to advancing net zero goals in recent years.

Meta and Google aim to achieve net-zero emissions across all its operations by 2030. Likewise, Microsoft aims to be "carbon negative, water positive, and zero waste" by 2030. Amazon aims to achieve net‑zero carbon across its operations by 2040.

Major tech companies, including Amazon, Google, and Microsoft, have also struck deals with nuclear energy suppliers recently as they advance AI technology.

"Energy, not compute, will be the No. 1 bottleneck to AI progress," Meta CEO Mark Zuckerberg said on a podcast in April. Meta, which built the open-source large language model Llama, consumes plenty of energy and water to power its AI models.

Chip designer Nvidia, which skyrocketed into one of the most valuable companies in the world this year, has also ramped up efforts to become more energy efficient. Its next-generation AI chip, Blackwell, unveiled in March, has been marketed as being twice as fast as its predecessor, Hopper, and significantly more energy efficient.

Despite these advancements, Nvidia CEO Jensen Huang has said allocating substantial energy to AI development is a long-term game that will pay dividends as AI becomes more intelligent.

"The goal of AI is not for training. The goal of AI is inference," Huang said at a talk at the Hong Kong University of Science and Technology last week, referring to how an AI model applies its knowledge to draw conclusions from new data.

"Inference is incredibly efficient, and it can discover new ways to store carbon dioxide in reservoirs. Maybe it could discover new wind turbine designs, maybe it could discover new materials for storing electricity, maybe more effective materials for solar panels. We should use AI in so many different areas to save energy," he said.

Moving to nuclear energy

Many tech leaders argue the need for energy solutions is urgent and investing in nuclear energy.

"There's no way to get there without a breakthrough," OpenAI CEO Sam Altman said at the World Economic Forum in Davos in January.

Altman has been particularly keen on nuclear energy. He invested $375 million in nuclear fusion company Helion Energy and has a 2.6% stake in Oklo, which is developing modular nuclear fission reactors.

The momentum behind nuclear energy also depends on government support. President Joe Biden has been a proponent of nuclear energy, and his administration announced in October it would invest $900 million in funding next-generation nuclear technologies.

Clean energy investors say government support is key to advancing a national nuclear agenda.

"The growing demand for AI, especially at the inference layer, will dramatically reshape how power is consumed in the US," Cameron Porter, general partner at venture capital firm Steel Atlas and investor in nuclear energy company Transmutex, told Business Insider by email. "However, it will only further net-zero goals if we can solve two key regulatory bottlenecks—faster nuclear licensing and access to grid connections—and address the two key challenges for nuclear power: high-level radioactive waste and fuel sourcing."

Porter is betting the incoming Trump administration will take steps to move the needle forward.

"Despite these challenges, we expect the regulatory issues to be resolved because, ultimately, AI is a matter of national security," he wrote.

AI's energy use is growing

Tech companies seek new energy solutions because their AI models consume much energy. ChatGPT, powered by OpenAI's GPT-4, uses more than 17,000 times the electricity of an average US household to answer hundreds of millions of queries per day.

By 2030, data centers—which support the training and deployment of these AI models—will constitute 11-12% of US power demand, up from a current rate of 3-4%, a McKinsey report said.

Tech companies have turned to fossil fuels to satisfy short-term demands, which has increased greenhouse gas emissions. For example, Google's greenhouse gas emissions jumped by 48% between 2019 and 2023 "primarily due to increases in data center energy consumption and supply chain emissions," the company said in its 2024 sustainability report.

• AI requires enormous amounts of energy, threatening global net zero goals.
• Tech giants may use fossil fuels short-term, raising concerns about clean energy commitments.
• AI is also ushering in an era of nuclear power, however, which is cleaner.

The rapid development of AI is likely to affect global net zero goals in both positive and negative ways.

Tech companies are investing in nuclear power plants to fuel AI data centers. Many of these power plants generate power through nuclear fission, which is considered cleaner than fossil fuels and more reliable than wind or solar power.

Silicon Valley investors, meanwhile, are investing in nuclear fusion, a still-nascent technique for generating power that fuses the nuclei of atoms. It could generate even more energy than fission, with fewer greenhouse gas emissions and less radioactive waste.

Some industry leaders believe that nuclear energy might be the only reliable way to meet the demands of the AI revolution.

"AI requires massive, industrial-scale amounts of energy," Franklin Servan-Schreiber, the CEO of nuclear energy startup Transmutex, previously told Business Insider. "Only nuclear power will be able to supply this massive energy demand in a reliable manner."

However, developing a reliable network of power plants is still a long-term goal that will necessitate huge investment and government support.

As of August 2023, there were only 54 nuclear power plants operating in the United States, according to the US Energy Information Administration. Companies like Amazon and Google have struck deals with companies building smaller, modular reactors that are faster to roll out than traditional reactors. However, the money is still "a drop in the bucket" compared to the billions these companies will ultimately need, physicist Edwin Lyman, director of nuclear power safety at the Union of Concerned Scientists in Washington, DC, told Nature.

In the meantime, tech giants may turn to fossil fuels to meet their short-term energy needs.

"Tech is not going to wait 7 to 10 years to get this infrastructure built," Toby Rice, the CEO of natural gas producer EQT, said in an interview with The Wall Street Journal. "That leaves you with natural gas."

Rice told the Journal that at a recent energy conference, he was repeatedly asked two questions: "How fast can you guys move? How much gas can we get?"

According to the Financial Times, last week, at the UN COP29 climate summit in Baku, Azerbaijan, Big Tech companies flew under the radar more than usual. Many opted out of displaying in the conference's business area, known as the green zone. Some attendees speculated that the surge in energy use for AI data centers has put the tech industry's clean energy commitments under scrutiny.

"If our industry starts getting treated similar to oil and gas, the public relations to counter that are going to be very expensive," said Kevin Thompson, chief operating officer at Gesi, a business group focused on digital sustainability, told the FT.

Data centers — now powered by a mix of natural gas, coal, and renewable energy sources — are expected to rise from a current rate of 3 %to 4% of US power demands to 11% to 20% by 2030, according to a report from McKinsey.

AI leaders, however, hope the intelligence revolution will inevitably lead to an energy revolution.

"My hopes and dreams is that, in the end, what we all see is that using energy for intelligence is the best use of energy we can imagine," Nvidia CEO Jensen Huang said in an interview at Hong Kong University of Science and Technology, after receiving an honorary degree last week.