Nuclear Regulatory Commission has AI integration in mind with new budget request
The Nuclear Regulatory Commission’s artificial intelligence plans came into greater focus this week with a roughly $4.43 million request for AI-related funding in its fiscal year 2025 budget, a $3.7 million increase from the previous year, according to an agency spokesperson.
In its congressional budget justification for FY 2025, the NRC said it is looking to develop an AI regulatory framework for the nuclear industry, in addition to facilitating the responsible adoption of AI, which includes generative AI.
Dave McIntyre, an NRC public affairs officer, shared in an email with FedScoop that agency staffers are “preparing a status update to send the Commission this spring outlining next steps to integrate AI across the agency, invest in the necessary IT infrastructure and recruit and train staff in AI skills.”
A different agency spokesperson confirmed in an interview with FedScoop that the NRC has conducted “some limited risk assessments” of generative AI tools that are publicly available to “help us develop our policy statement.” The spokesperson said that the agency plans to continue working with the Cybersecurity and Infrastructure Security Agency and others on risk management, in addition to working on security controls and risk mitigation as NRC implements internal AI tools.
The NRC issued an internal policy on generative AI to its employees last July, but that policy has not been made public, the spokesperson added, noting that the agency is considering whether the technology can be used “as a testbed or sandbox for tools.”
“We are talking about starting with testing use cases without enabling for the entire agency,” they said. “And we would leverage our development and test environments as we develop solutions.”
Basia Sall, deputy director of the NRC’s IT services development and operations division within the agency’s Office of the Chief Information Officer, said in an interview that the agency remains in the early stages of its gen AI experimentation.
“We see potential for these tools to be more powerful time savers to help make our regulatory reviews more efficient,” she said.
