As tech giants seek nuclear power for AI data centers, the flip side of that coin is emerging — using AI to improve reactor licensing and construction. Energy demand for data centers is rising fast, and nuclear energy is carbon-free and round-the-clock. But getting reactors approved and built is really complex and time-sucking. So hyperscalers, startups and federal agencies want AI to speed things up — but carefully. This week, the latest efforts emerged around both next-wave reactor designs and incumbent models. DOE’s Idaho National Lab will use a Microsoft tool to create safety and analysis reports that are part of construction and license applications, the parties said Wednesday. It ingests and analyzes engineering and safety info, and generates documents that the Nuclear Regulatory Commission and DOE require, they said. “This is a big deal for the nuclear licensing process,” Jess Gehin, a top INL scientist, said in a statement. “Introducing AI technologies will enhance efficiency and accelerate the deployment of advanced nuclear technologies.”
INL and the company are emphasizing that humans aren’t taken out of the loop. Microsoft’s Nelli Babayan tells Reuters: “It’s created for human refinement, so a human can go through each of the sections and, specifically as needed, edit any of the sections, whether manually, or maybe with the help of AI — it’s really up to the human.” Separately, Westinghouse and Google said Tuesday they’re working together to harness AI to make building Westinghouse reactors an “efficient, repeatable process.” They’re combining Westinghouse AI tools built on proprietary data with Google’s cloud capabilities.

Full report : How AI is helping United States energy sector transition to nuclear energy.