X-Energy's Xe-100 small modular reactor represents a direct answer to AI's insatiable appetite for reliable, continuous electrical power. The advanced high-temperature gas-cooled reactor generates 80 megawatts of electricity or 200 megawatts of thermal output per unit, and the company deploys them in groups of four to produce 320 megawatts of electricity with built-in redundancy. Unlike traditional power plants that operate intermittently, the Xe-100 is engineered specifically for the non-stop demands of AI infrastructure, with an expected capacity factor of 95 percent, meaning it runs at near-maximum output almost continuously.

Why Are Major Tech and Industrial Companies Betting on Small Modular Reactors?

The customer roster behind X-Energy's Xe-100 pipeline tells a compelling story about where the energy industry is headed. Dow, Amazon, and Centrica have committed to purchasing these reactors, and if all their contingent rights are exercised, the projects represent approximately 11.5 gigawatts of capacity across 144 reactors in the United States and the United Kingdom. That's not a pilot program; it's a commercial-scale bet that small modular reactors can solve the power reliability problem that AI data centers face. Traditional power grids, designed for variable demand, struggle to guarantee the constant, uninterrupted supply that modern AI infrastructure requires.

What sets X-Energy apart from competitors is its vertical integration. The company is developing not just the reactor but also the fuel that powers it. X-Energy's TRISO-X fuel uses HALEU, or high-assay low-enriched uranium, and is manufactured at the company's TX-1 facility in Oak Ridge, Tennessee. This facility is designed to support the first 11 Xe-100 reactors at steady-state operations, while a planned TX-2 facility could eventually support up to 44 reactors annually. By controlling both the reactor and its fuel supply, X-Energy reduces dependency on external suppliers and creates a tighter feedback loop for optimization.

How Are Advanced Manufacturing and AI Shaping Nuclear Energy's Future?

Beyond reactor design, the nuclear energy sector is embracing artificial intelligence and advanced manufacturing techniques to accelerate development and improve component quality. On August 27, 2026, 3D Systems announced a Cooperative Research and Development Agreement (CRADA) with Savannah River National Laboratory to advance additive manufacturing technologies specifically for nuclear energy and national security applications. This partnership signals a broader shift in how the nuclear industry approaches manufacturing challenges.

The collaboration focuses on several critical areas that directly impact nuclear energy's ability to scale:

• Materials Development: Creating next-generation advanced materials that can withstand the extreme conditions inside nuclear reactors while improving performance and durability.
• AI and Machine Learning Process Optimization: Deploying artificial intelligence to monitor and optimize manufacturing processes in real time, reducing defects and improving consistency across production runs.
• Equipment Enhancements: Improving the additive manufacturing equipment itself to handle the specialized materials and tolerances required for nuclear components.
• Workforce Development: Training the next generation of additive manufacturing scientists, engineers, and technicians to support rapid scaling of these technologies.

Additive manufacturing, commonly known as 3D printing, produces complex components from advanced alloys that would be difficult or impossible to create using traditional manufacturing methods. For nuclear systems, this means stronger, lighter components with fewer weak points, ultimately enhancing both performance and supply-chain resilience.

"We look forward to partnering with SRNL at the Advanced Manufacturing Collaborative and deploying 3D Systems' leading AM technologies. This agreement demonstrates the impact and importance of high-quality 3D printing materials and technologies on key industrial markets, particularly energy and national security, and on developing the skilled workforce those markets require," said Jeff Graves, President and CEO of 3D Systems.

Jeff Graves, President and CEO of 3D Systems

What Does This Mean for AI's Energy Future?

The convergence of small modular reactor technology, AI-driven manufacturing optimization, and major corporate commitments suggests that nuclear power is positioning itself as a cornerstone of AI infrastructure. Data centers consume enormous amounts of electricity, and as AI models grow larger and more capable, that demand will only increase. Unlike solar and wind, which depend on weather and time of day, nuclear power provides the steady, predictable supply that AI systems require to operate reliably at scale.

The next several years will be critical for X-Energy and other advanced reactor developers. Moving from demonstration projects to repeatable commercial deployments requires not just engineering excellence but also regulatory approval, supply chain maturity, and proven operational reliability. The company's large customer pipeline provides a foundation for substantial long-term growth, but execution will determine whether the Xe-100 becomes the workhorse reactor for AI-powered infrastructure or remains an ambitious design.

Meanwhile, the partnership between 3D Systems and Savannah River National Laboratory represents the kind of innovation infrastructure that advanced reactor programs need to succeed. By integrating cutting-edge manufacturing techniques with artificial intelligence, the nuclear industry is preparing itself for the rapid scaling that AI's energy demands will require. The result could be a new era where nuclear power and artificial intelligence grow together, each enabling the other to reach new heights of capability and scale.