Nuclear Regulatory Commission Cuts Licensing Review Times by Almost 75% with AI
The Nuclear Regulatory Commission’s (NRC) use of artificial intelligence has drastically reduced the time it takes to review nuclear licenses, with some reviews that once took four years to complete now being done in just nine months.
According to Basia Sall, NRC Chief Data Officer and Deputy Chief AI Officer, the agency has made significant strides in utilizing AI to streamline its processes. “It’s a huge shift,” she said. “We’re talking about a process that used to take years being reduced by almost three-quarters.”
The licensing review process is a critical step in ensuring the safe operation of nuclear power plants. The NRC must thoroughly evaluate every aspect of a plant’s design and operations before granting a license. However, this review process was often plagued by inefficiencies and delays, which can push back construction timelines and increase costs for plant operators.
The NRC’s adoption of AI has helped to address these issues by automating many of the more mundane and time-consuming tasks associated with licensing reviews, such as data analysis and paperwork. AI has also enabled the agency to identify potential issues and safety risks more quickly, allowing for more effective and efficient review processes.
What this means
For nuclear power plant operators, the benefits of the NRC’s AI-facilitated licensing review process are clear: faster construction timelines and lower costs. The use of AI also has broader implications for the nuclear industry as a whole, helping to improve safety and efficiency while reducing the risk of costly delays.
A New Era for Nuclear Licensing
The NRC’s success in using AI to speed up licensing reviews is just one example of the many ways in which the technology is being applied in the nuclear industry. As the agency continues to explore the potential of AI, we can expect to see even more significant improvements in nuclear safety and efficiency in the years to come.
A Look Ahead
The NRC’s current focus is on identifying ways to further integrate AI into its licensing review process. This will involve exploring new applications for the technology, as well as developing more sophisticated AI models that can handle increasingly complex licensing review tasks.
