The world needs clean energy that is reliable and easy to build, without producing too much carbon. Nuclear energy is gaining fresh attention in this effort, but not the kind we’re used to. A new type of reactor, called a Small Modular Reactor (SMR), could make nuclear power safer, cheaper, and faster to install.
SMR offers a promising option for the clean energy transition. But what’s helping SMRs move from the lab to reality even faster is artificial intelligence (AI).
AI is already playing a key role in many parts of the energy system. According to the International Energy Agency’s (IEA) 2024 Energy and AI report, AI is being used to improve how energy is produced, stored, distributed, and consumed.
For SMRs, which are still in the early development stages, AI is becoming a critical tool for reducing cost, time, and risk. Let’s unravel how AI helps speed up the rise of SMRs.
What Are SMRs and Why Do They Matter?
SMRs are small nuclear reactors that can make electricity or heat. They are much smaller than traditional nuclear plants. Most SMRs will make between 10 and 300 megawatts (MW) of power. That’s enough to power a town or a factory.
Big reactors take over 10 years to build and cost billions of dollars. SMRs are different; they are:
- Build in factories
- Easier to transport
- Faster and cheaper to install
The IEA says SMRs are designed to be safer and more flexible, offering a low-carbon power option. They can be used in remote areas, near factories, or with solar and wind power. These features make SMRs useful for the energy transition.
Most SMRs under development could cost less than $2 billion compared to more than $10 billion for traditional nuclear plants. They also use advanced safety features and can be installed in areas where large plants wouldn’t fit.
Where Are SMRs Being Built?
Interest in SMRs is growing quickly. In the United States alone, over 20 gigawatts (GW) of SMR capacity has been proposed, especially by tech companies looking to power their growing fleets of AI data centers.
Some utilities, like Dominion Energy, plan to add 1.3 GW of SMR capacity by 2039 to meet rising electricity demand.
China is also exploring SMRs, expecting them to play a role between 2030 and 2035. In fact, the IEA estimates that low-emissions electricity (including SMRs) will supply 60% of power for Chinese data centers by 2035. In the U.S., this share could reach 55% by the same year.
Although many SMRs are still in the planning phase, they could begin commercial deployment after 2030, especially as clean energy policies become stronger and electricity needs increase.
So, here are the many ways how AI aids in boosting SMR applications.
How AI Supports SMR Design and Operation
Designing a nuclear reactor is very complex. Engineers must decide how big each part should be, how to keep the core cool, how to manage radiation, and how to make it safe. This usually takes years of modeling and testing. But AI is changing that.
The IEA explains how generative AI and machine learning can run fast simulations of reactor designs. This allows scientists to test thousands of options in less time. AI is especially useful in adjusting the geometry of the reactor to improve how heat is managed and to avoid unsafe temperature levels.
AI is also used in materials testing. Inside a reactor, the materials need to handle very high temperatures and radiation for long periods. AI tools can now predict how metals and other materials will behave, reducing the need for long lab tests. This helps engineers choose stronger, more reliable materials faster.
Smart Fuel Management and Monitoring
Fuel is one of the most important parts of a nuclear reactor. Engineers must load it carefully and plan when to replace it. AI can help make these decisions better. According to the IEA, predictive AI can improve fuel loading and switching, making the process more efficient and reducing waste.
The IEA also notes that AI-powered predictive maintenance can find system issues before they become serious, which lowers costs and keeps reactors running longer.
AI Helps Explain Safety Risks
AI is not just used inside the reactor. It can also help outside the plant—especially with safety reports and rules. Getting approval to build a nuclear reactor takes years. Governments and safety agencies have to read thousands of pages of technical documents.
The IEA explains that large language models (LLMs) can help speed this up. These models turn complex data into clear summaries that both engineers and regulators can understand. They also help explain system faults in plain language during training or emergency situations.
SMRs and the Energy Transition
As AI increases electricity demand and more countries try to cut carbon, SMRs could become an important part of the clean energy mix. The IEA predicts that SMRs will grow in use after 2030, especially in places that need reliable, round-the-clock electricity.
In fact, spending on Small Modular Reactors could grow a lot in the coming years. The market is worth about $5 billion today, but that could rise to $25 billion by 2030, and reach $670 billion by 2050.
- If building SMRs becomes cheaper, as experts expect, the world could have 190 gigawatts of SMR power by 2050. That could bring in up to $900 billion in global investment.
The agency further notes that:
“As the world enters a new Age of Electricity, interest in nuclear power has grown to a 50-year high.”
In areas with lots of solar or wind power, SMRs can help keep the grid stable. When the sun isn’t shining or the wind isn’t blowing, SMRs can provide backup power. This is especially useful for data centers, which need electricity 24/7.
SMRs may also help companies and governments meet net-zero goals by replacing old coal and gas plants. Because they are small, they can be added to existing sites or installed closer to where energy is needed.
Big Tech’s Growing Interest in SMRs
Some of the world’s largest technology companies are now looking at SMRs to power their growing fleets of data centers and AI tools. These companies need a constant and reliable source of clean electricity, and SMRs offer one solution that can scale with their needs.
Companies like Microsoft and Google have shown interest in advanced nuclear technologies. In 2023, Microsoft even signed a power purchase agreement linked to nuclear energy and has posted job listings for roles related to nuclear-powered data center operations.
While most of these investments are still in early phases, they show that SMRs are not just a government-led effort—they are now part of the clean energy plans of major private sector players as well.
By investing early, tech companies hope to reduce emissions from AI workloads while supporting the commercialization of SMRs in the next decade.
Powering Ahead
AI is changing how the energy world works—and nuclear energy is no exception. With its help, Small Modular Reactors are becoming faster to design, safer to operate, and more efficient overall. SMRs could provide clean power in places where other options don’t work well, and AI is helping make that future possible.
- FURTHER READING: What is SMR? The Ultimate Guide to Small Modular Reactors