The artificial intelligence (AI) revolution is reshaping industries, but its insatiable appetite for energy is creating a formidable challenge for global power grids. As AI applications become more sophisticated, the demand for computing power—and consequently electricity—is skyrocketing, sending tech giants and energy providers scrambling to find reliable, large-scale, and low-carbon power sources. In this search, nuclear energy is emerging as a prime contender.
The Scale of AI's Energy Problem
The energy consumption of data centers, the backbone of the digital economy, is growing at an alarming rate. International Data Corporation (IDC) projects that global datacenter electricity consumption will more than double between 2023 and 2028, reaching 857 terawatt-hours (TWh). A significant portion of this growth is driven by AI. AI datacenter energy consumption is forecast to grow at a compound annual growth rate (CAGR) of 44.7% through 2027. The International Energy Agency (IEA) reinforces this, estimating that global electricity demand from data centers could more than double by 2030 to around 945 TWh, more than the entire current electricity consumption of Japan. This massive demand is putting unprecedented pressure on existing power grids, many of which are already aging and not equipped to handle such rapid growth.
Why Nuclear?
While renewables like solar and wind are vital for decarbonization, their intermittent nature poses a challenge for data centers that require constant, uninterrupted power. Nuclear energy offers a solution. It operates 24/7, providing firm baseload power with a capacity factor exceeding 92.5%, significantly outperforming natural gas (56%), wind (35%), and solar (25%). Furthermore, nuclear is a virtually zero-greenhouse-gas-emitting source during operation and has a high energy density, requiring significantly less land compared to wind and solar farms to produce the same amount of energy.
Tech Giants Go Nuclear
Recognizing these advantages, the world's largest tech companies are actively turning to nuclear power. Amazon Web Services (AWS) made headlines by acquiring a data center campus in Pennsylvania for $650 million, powered directly by the adjacent Susquehanna nuclear plant. AWS plans to develop up to a 960 MW data center campus. Microsoft has signed a 20-year power purchase agreement with Constellation Energy to restart the Three Mile Island Unit 1 nuclear reactor, which was shut down in 2019, to power its data centers. Google has also entered into partnerships, including an agreement with Duke Energy to explore advanced nuclear projects.
The Promise of Small Modular Reactors (SMRs)
A major catalyst for this renewed interest is the development of Small Modular Reactors (SMRs). These reactors are smaller than traditional ones, factory-built, and assembled on-site, which can reduce construction times from 6-12 years to just 3-5 years. Their modular design allows for scalability and flexibility, making them ideal for powering individual data center campuses. Multiple companies, including Amazon, are partnering with SMR developers like X-energy to deploy next-generation reactors. OpenAI CEO Sam Altman is a prominent proponent, having invested in both fission startup Oklo and fusion company Helion Energy, stating that an energy breakthrough is necessary to meet the vast requirements of future AI.
Challenges and Headwinds
Despite its potential, nuclear power faces significant hurdles. High upfront capital costs, lengthy permitting and construction timelines, strict regulations, and the management of nuclear waste remain major challenges. Public perception, often colored by past accidents like Three Mile Island, is also a barrier. Furthermore, a scarcity of specialized labor and constraints in the uranium supply chain can slow the deployment of new plants. Even with the promise of SMRs, Goldman Sachs Research estimates that well less than 10% of the new nuclear capacity needed to meet data center demand growth by 2030 will be available globally.
A Hybrid Future
The future of energy for AI will likely not rely on a single solution. Experts advocate for an "and" approach, where nuclear, natural gas, renewables, and battery technology all play a role. AI itself can help optimize this complexity, improving energy demand and supply forecasting and enhancing grid stability. As AI's growth continues unabated, the pressure to find viable energy solutions will only intensify. Nuclear power, with its unparalleled reliability and carbon-free generation, is positioned as a critical, albeit challenging, pillar of the energy infrastructure that will power the next phase of technological innovation.