Department of Energy Unleashes AI to Reduce Reactor Licensing Timelines

The U.S. Department of Energy (DOE), in collaboration with Idaho National Laboratory (INL), Argonne National Lab (ANL), Microsoft, and Everstar, has successfully demonstrated the use of artificial intelligence (AI) tools to streamline the nuclear regulatory process.  

The team used AI mapping to convert a safety analysis document required under DOE’s authorization pathway for advanced reactor demonstrations into U.S. Nuclear Regulatory Commission (NRC) licensing documents for commercial deployment. 

This accomplishment shows the role AI can play in improving the efficiency and accuracy of nuclear technology licensing, and could one day help to accelerate timelines for the commercial deployment of advanced nuclear reactors.

Accelerating the Nuclear Renaissance, One Reactor License at a Time  

Everstar’s Gordian AI solution, built on the Microsoft Azure platform, was recently used to convert the Preliminary Documented Safety Analysis for DOE’s National Reactor Innovation Center’s (NRIC) Generic High Temperature Gas Reactor (HTGR) into sections equivalent to an NRC license application.  

The final 208-page document took one day to generate. Typically, the process takes a team of people between four and six weeks to complete the same task. The AI tool also comprehensively identified missing or incomplete information needed to successfully complete an NRC application. 

Gordian was engineered for nuclear-grade technical work and is equipped with physics and engineering tools, as well as the ability to understand and integrate data through semantic ontology mapping, to ensure that the final output is computed and verified, not inferred. 

AI's ability to accelerate the development of a licensing application from weeks to days does not mean that nuclear licensing experts are out of a job. The approach maintains a critical principle where experts design, AI accelerates, and experts validate  

Gordian’s output was subsequently evaluated by an expert for accuracy, missing information, consistency, as well as grammar and structure to ensure that its results were correct and adhered to rigorous professional standards. The output was found to demonstrate quality, rigor, and depth, as well as the tool's ability to identify and qualify its own gaps in data knowledge.   

“Now is the time to move boldly on AI-accelerated nuclear energy deployment,” said Rian Bahran, Deputy Assistant Secretary for Nuclear Reactors. “This partnership, combined with the President’s orders, represents more than incremental ‘uplift’ improvements. It has the potential to transform how industry prepares its regulatory submissions and deploys nuclear energy while upholding the highest standards of safety and compliance.” 

“Nuclear is poised to solve today’s critical energy challenges,” said Kevin Kong, CEO and Founder of Everstar. “We’re excited to partner with INL to meet the moment, working together to accelerate regulatory review and commercialization.”  

“Our collaborations with DOE, INL and across the industry are demonstrating how we can effectively bring secure, scalable AI technologies to solve key energy challenges and achieve the broader national and economic security goals envisioned by the Department’s Genesis Mission,” said Carmen Krueger, Corporate Vice President, US Federal, Microsoft.

New AI Tools Pick Up Speed 

Currently, the nuclear licensing process involves multiple rounds of manual document reviews and minor clerical adjustments, which can take years to complete.  

The HTGR test case is the latest in a growing list of examples that successfully demonstrates the role AI can play in improving the process.  

Earlier this year, INL collaborated with Microsoft to deploy a Microsoft Azure AI-based solution to show how advanced AI models can generate engineering and safety analysis reports, a key part of applications for construction permits and operating licenses for nuclear power plants.  

These early wins are only the beginning. A recent study by NRIC highlighted how AI has the potential to reduce both document development time and regulatory review cycles by as much as 50 percent, while simultaneously improving accuracy, consistency, and traceability.

What’s Next? 

Looking ahead, the team plans to strengthen and validate their approach. A reviewing agent will evaluate AI-generated documents against NRC guidance to validate that they are ready for submittal. A benchmarking rubric is also being developed to provide a confidence grade for the Gordian’s performance.  

INL is also developing its own in-house AI tools including potential applications for fuel fabrication facilities. 

The work progresses President Trump’s Genesis Mission, a national initiative to unleash a new age of AI-accelerated innovation and discovery. Under the Genesis Mission, DOE recently announced $293 million in competitive funding to advance twenty-six pressing national science and technology challenges, including one focused on expediting nuclear energy deployment. 

Learn more about the Genesis Mission.