Nuclear Energy

What Is Nuclear Energy?

Nuclear energy is the energy released from the nucleus of an atom through fission (splitting heavy atoms like uranium) or fusion (combining light atoms like hydrogen). Fission-based nuclear power plants currently generate roughly 10% of the world's electricity with a capacity factor exceeding 92.5%—far outpacing natural gas (56%), wind (35%), and solar (25%). This makes nuclear the most reliable source of firm, around-the-clock baseload power available today, a property that has made it central to the strategy of companies building AI infrastructure at scale.

Nuclear Energy and the AI Power Crisis

The explosion of artificial intelligence workloads has created an unprecedented energy crisis. Data centers accounted for 2% of global electricity consumption in 2022, a figure expected to double by 2026 and to represent over 20% of electricity-demand growth in advanced economies by 2030. Training and running large language models requires sustained, high-density power that intermittent renewables alone cannot reliably deliver. In response, Big Tech has made massive nuclear commitments: Meta announced agreements with Vistra, TerraPower, Oklo, and Constellation totaling over 6 gigawatts of nuclear capacity—enough to power approximately 5 million homes—making it one of the largest corporate nuclear energy purchasers in history. Microsoft, Google, and Amazon have all signed similar nuclear power purchase agreements, driven by the same calculus: GPU-dense data centers need power that never stops.

Small Modular Reactors and Next-Generation Technology

Small modular reactors (SMRs) represent a paradigm shift in nuclear deployment. Rated at 300 MWe or less, SMRs apply principles of modularity and factory fabrication to dramatically reduce construction timelines and capital risk compared to traditional gigawatt-scale plants. In March 2026, the Rolls-Royce SMR became the first small modular reactor to receive regulatory justification approval in the United Kingdom, while the European Union adopted a formal SMR strategy to accelerate deployment across the continent. In the United States, the Nuclear Regulatory Commission is expected to make several SMR licensing decisions in 2026, with companies like NuScale, Oklo, and TerraPower competing to bring designs to commercial operation. SMRs' smaller footprint and passive safety features enable deployment near industrial sites and data center campuses, making them ideal for powering edge AI and digital twins infrastructure.

Nuclear Fusion: The Long Bet

While fission dominates today, nuclear fusion—the process that powers the sun—is advancing rapidly toward commercial viability, propelled by breakthroughs in high-temperature superconducting magnets, more powerful AI chips, and sophisticated simulation software. Helion Energy's Polaris prototype achieved 150 million degrees Celsius plasma temperatures in February 2026 and became the first privately developed fusion machine to operate with deuterium-tritium fuel; Helion has a contract with Microsoft to sell electricity from its first 50 MW commercial plant starting in 2028. Commonwealth Fusion Systems expects its Sparc reactor operational by late 2026 or early 2027, with a 400 MW commercial plant to follow. TAE Technologies plans to begin building the first utility-scale fusion power plant in 2026. The fusion industry has attracted over $7.1 billion in private investment, with multiple approaches—tokamaks, stellarators, inertial confinement, and pulsed fusion—competing to achieve net energy gain at commercial scale.

Powering the Semiconductor Supply Chain

Nuclear energy's relevance extends beyond data centers to semiconductor manufacturing itself. A single advanced fab consumes upward of 100 megawatt-hours per hour—more than many automotive plants or oil refineries. TSMC's Arizona facility will consume roughly 200 MW in its first phase, with planned expansions potentially exceeding 1 GW, roughly equivalent to a single nuclear reactor's output. As global semiconductor electricity consumption is projected to reach 237 TWh by 2030, nations like South Korea are building out nuclear capacity specifically to support chip fabrication alongside AI compute. The convergence of AI infrastructure demand and semiconductor expansion is creating an energy bottleneck that only nuclear—with its unmatched power density and reliability—can credibly address at the scale required by the inference economy.