A recent announcement from Aalo Atomics and Microsoft—an unlikely pairing even a few years ago—has quietly signaled a historic turning point for the nuclear sector. Their partnership, centered on using advanced software and artificial intelligence to accelerate reactor permitting and deployment, marks more than a technical collaboration. It marks a strategic inflection point: nuclear energy, long considered a uniquely analog and mechanical domain, is becoming a digitally driven industry. The technologies that will define the next generation of reactors will not be limited to advanced fuels or modular manufacturing. They will include AI-enabled engineering tools, cloud-based licensing workflows, digital twins that update in real time, and predictive systems that continually shape reactor operations.

This convergence of nuclear and digital technology is accelerating at a speed that few policymakers have fully appreciated. It is happening across all phases of the nuclear lifecycle, from early site selection to reactor decommissioning, and it is reshaping how companies design reactors, how they interact with regulators, how national security agencies plan for microreactor deployment, and how investors evaluate nuclear projects. The United States is poised at the beginning of a transformation as consequential as the shift from slide rules to supercomputing. And yet the policy frameworks governing nuclear safety, cybersecurity, export controls, defense procurement, and regulatory oversight are all rooted in assumptions from an analog era. 

I work at the intersection of nuclear regulation, international trade controls, and the emerging advanced-reactor industry. And in that space I can attest that the convergence of nuclear and AI is no longer theoretical —it is the daily reality of developers, government partners, and defense planners. The most sophisticated advanced reactor companies already treat software and data as core components of their safety and engineering philosophy. Cloud-native modeling environments, AI-assisted design optimization tools, automated supply chain verification systems, and data-rich remote operations platforms are now embedded in the DNA of the new generation of reactors and the companies that are developing them. And it has implications for all levels of regulation of the nuclear energy industry.

The United States needs to confront the implications of this transformation now, before the technology outpaces the regulatory infrastructure designed to keep nuclear energy safe, secure, and competitive.

From the Analog Era to Digital Reactors

To understand how much the industry has changed, it is instructive to recall just how non-digital the current US nuclear fleet is. The reactors supplying roughly one-fifth of US electricity were conceived in the 1960s and licensed largely in the 1970s and early 1980s. They are marvels of engineering, but their control systems were designed in a world before microprocessors, let alone machine learning. Their operational logic relies on arrays of pressure gauges, analog readouts, and mechanical switchboards. Many components have been digitally retrofitted, but the underlying architecture remains rooted in mechanical redundancy and human-centered control.

The author at the Farley Nuclear Power Plant in Dothan, Alabama. Credit is to the author.

Contrast this with the reactors now under development. Whether one examines the microreactors intended for remote military bases, small modular reactors designed for facility commitment or grid flexibility, or high-temperature reactors optimized for industrial heat production, the common denominator is digital design. These reactors are conceptualized from the ground up around software ecosystems, model-based engineering, cloud-enabled simulation environments, and extensive sensor networks. Predictive maintenance is not an add-on; it is a driving engineering assumption. Digital twins, i.e., virtual models that reflect the real-time operational state of the reactor, are not experimental — they are becoming increasingly standard in leading programs. And human operators are increasingly envisioned as supervisors of automated systems, not as direct manipulators of mechanical components as they were in previous models.

This shift brings extraordinary benefits. Digital........

© The National Interest