ML25273A290

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02 Kelli Voelsing Jim Slider NEI NRC Ai Workshop 2025.09.24
ML25273A290
Person / Time
Site: Nuclear Energy Institute
Issue date: 09/24/2025
From: Slider J, Voelsing K
Nuclear Energy Institute
To:
Office of Nuclear Regulatory Research
References
Download: ML25273A290 (1)


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©2025 Nuclear Energy Institute NEI Perspective NRC AI Workshop September 24, 2025 Jim Slider jes@nei.org Kelli Voelsing khv@nei.org Nuclear Industry Use of AI

©2025 Nuclear Energy Institute 2 Topics CURRENT NEI ACTIVITIES

1. Facilitating Engagement with NRC on AI issues
2. NILLM - Nuclear Industry Large Language Model
3. NEI Regulatory Requirements Checking Tool Piloting an AI-enabled tool for NEI members Enabling efficient access to and application of industry knowledge and data

©2025 Nuclear Energy Institute 3 Adoption Rapid and accelerating adoption Strong interest and hundreds of use cases across all plant departments Many uses cases focus on

- Efficient access to the right information to improve products and support informed decision making

- Automation of administrative or routine processes Human-in-the-loop (HITL) is used for validation and decision making when utilizing AI Regulation Large value to be gained from uses that do not require NRC approval Nearer-term regulatory submittals likely to involve

- Image recognition and processing

- Machine learning and pattern recognition Regulatory applications involving Generative AI (Gen AI) are likely a bit further out A graded and flexible regulatory framework is critical

-Many kinds of AI

-Large spectrum of how AI is used in any application

-Encourage innovation that benefits safety and efficiency

1. Facilitating Engagement with NRC on AI issues

©2025 Nuclear Energy Institute 4 AI-READY NRC DATASETS

Partnering with NRC staff to deliver high-value, AI-ready NRC datasets

Promotes efficiency and transparency

Supports all stakeholders

Feedback to ensure

Sustainable process

Right metadata and formats

Priorities for future datasets

Initial datasets include

Regulatory Guides

NUREGs

1. Facilitating Engagement with NRC on AI issues

PURs

LR/SLRs NRCs collaboration and support on this effort is extremely valuable

IMCs/IPs

SECYs, etc. etc.

©2025 Nuclear Energy Institute 5

2. NILLM - Nuclear Industry Large Language Model A Collaborative Industry Project Initial use case testing begins Q4 2025 Project Sponsor - Ramon Martinez, INPO (martinezr@inpo.org)

©2025 Nuclear Energy Institute 6 Initial Use Cases & Scope Knowledge Transfer (led by NEI)

Supports knowledge management and transfer by enabling overview and detailed understanding of key topics in the nuclear industry Operational Experience Search (led by INPO)

Smart search across IRIS, INPO, EPRI, and NEI documents Supports plant reliability and safety initiatives Troubleshooting (led by EPRI)

AI-assisted plans for degraded components or system conditions

©2025 Nuclear Energy Institute 7

AI-enabled Document Compliance Check

Automated identification and curation of regulatory requirements for a given application

Assess how well a document addresses each requirement

Supports high-quality and consistency in regulatory submittals

Useful for self-assessment of regulatory compliance

Near-term, 6-month pilot, proof-of-concept project

What will we learn from the pilot?

Increase comfort with AI-enabled regulatory and licensing applications

Understand appetite and adoption of targeted AI-workflows versus open-ended chatbots and prompt engineering

Assess value to end-users

Hosting and usage costs

3. NEI Member Pilot AI-ENABLED REGULATORY REQUIREMENTS TOOL Alignment Focus Insight NEI is partnering with Jensen Hughes to make this tool available to NEI members Demonstration of the tool later on todays agenda

©2025 Nuclear Energy Institute 8 Closing Thoughts Many current uses of AI in the nuclear industry are outside NRC requirements:

- Efficient access to information

- Automating administrative tasks NEI supports development of AI regulatory framework that is:

- Flexible

- Graded NEI and the nuclear industry are committed to:

- Practical use of AI for the benefit of safety and efficiency

- AI that is ethical, responsible, explainable, verifiable