Building AI That Speaks Nuclear

BusinessEnergyBuilding AI That Speaks NuclearByAnna Broughel,Contributor.Forbes contributors publish independent expert analyses and insights. I write about green energy tech that will change your life.Follow AuthorApr 27, 2026, 06:37am EDTAI is driving demand for nuclear energy while also helping to unlock the tools to build it faster.gettyThe authoritative IPCC report makes it abundantly clear that we need nuclear power if we want to keep temperatures within the 2-degree limit, while also building data centers, electrifying everything, and lifting over 8 billion people into energy abundance.Despite this urgency, nuclear reactors cost billions of dollars to build in the U.S., yet the global experience has shown that it is indeed possible to complete six to eight reactors per year at a much lower cost. “Other countries are already doing this,” said Kevin Kong, founder and CEO of Everstar. “We don’t need to break any laws of physics to do the same.” Instead, we need to focus on the four steps: standardize reactor designs, build in series, develop an integrated domestic supply chain and train the workforce, and align the regulatory environment to support volume while maintaining safety.This approach worked in France, South Korea, Japan, and China. It even worked in the United States decades ago. Reintroducing it would not require reinventing nuclear technology, but rather restoring the system that allows it to scale. Pre-licensed domestic designs already exist, ranging from larger power plants like Westinghouse to smaller modular reactors from NuScale. What is missing is a consistent demand signal and large order books that enable serial construction. After all, building the first nuclear reactor in decades is likely to be expensive. Once experience accumulates, successive power plants can be built faster and at lower cost. Yet each nuclear project still confronts a maze of regulations and deeply manual workflows, with key information trapped in decades-old documents...