GreatNorthCollective/greatnorth-us-federal-ai-inventory huggingface dataset:
US federal AI use case: MAPPRITE
Agency: Department of Energy - EHSS HQ - Office of Environment Health Safety and Security (EHSS)
Problem addressed: (1) The implemented AI will help automate data mining, ingesting, and indexing of existing disparate organizational data sources information for relevant safeguards and security (S&S) support information; and the (2) expected benefits will be to help
Purpose and benefits: (1) The implemented AI will help automate data mining, ingesting, and indexing of existing disparate organizational data sources information for relevant safeguards and security (S&S) support information; and the (2) expected benefits will be to help improve EHSS-51 business workflows for researching potentially relevant S&S support data available such that the information will be accessible and searchable by policy subject matter specialists for awareness and additional context for strategic decision-making and policy management
Topic area: Other
Development stage: Pilot
Impact assessment: MAPPRITE's AI does not provide outputs that serve as a principal basis for decisions or actions with legal, material, binding, or significant effects.
First used: 2025-11-23
US federal AI use case: ServiceNow AI Search
Agency: Department of Energy - ORNL - Oak Ridge National Laboratory (SC43 OIM)
Problem addressed: Intelligent query features help you quickly find the answers ServiceNow users need.
Purpose and benefits: 1) Enhancing employee productivity and efficiency.
Topic area: IT
Development stage: Pre-deployment
Impact assessment: Doesn't meet the criteria
US federal AI use case: Copilot for Microsoft 365
Agency: Department of Energy - ORNL - Oak Ridge National Laboratory (SC43 OIM)
Problem addressed: Enhancing day to day processes.
Purpose and benefits: 1) Enhancing employee productivity and efficiency.
Topic area: IT
Development stage: Deployed
Risk category: High-impact
First used: 2024-03-11
US federal AI use case: MI8 Collimators Surogate Model
Agency: Department of Energy - FNAL - Fermi National Accelerator (SC43 OIM)
Problem addressed: This project is working to create a ML surogate model of the exisitng MI8 collimation system. The purpose of the ML model is to aid in the tuning of the collimation system for acclerator operations and to help find more optimal settings in a timely m
Purpose and benefits: This project is working to create a ML surogate model of the exisitng MI8 collimation system. The purpose of the ML model is to aid in the tuning of the collimation system for acclerator operations and to help find more optimal settings in a timely manner. We hope to extend these techniques to other sub-systems and also a new MI8 collimation system being installed.
Topic area: Science
Development stage: Pilot
Impact assessment: The use case does not have an effect on civil rights/liberties/privacy, access to education/housing/insurance/credit/employment, access to critical government resources/services, human health/safety, critical infrastructure/public  safety
First used: 2025-09-25
US federal AI use case: AI for High Risk Property
Agency: Department of Energy - ORNL - Oak Ridge National Laboratory (SC43 OIM)
Problem addressed: 1) Regulatory compliance.  2) Improved identification of high-risk property items and increased productivity.
Purpose and benefits: 1) Regulatory compliance.  2) Improved identification of high-risk property items and increased productivity.
Topic area: IT
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Records Digitization
Agency: Department of Energy - SEPA - Southeastern Power Administration (PMA)
Problem addressed: Enhance lookup of agency records and electronic documents
Purpose and benefits: SEPA is leveraging AI and ML to enhance metadata tagging and quality control during the records digitization process.
Topic area: Admin Functions
Development stage: Pre-deployment
Impact assessment: As part of the records digitization process, SEPA is leveraging AI and ML to enhance metadata tagging and quality.
US federal AI use case: Machine Learning components within Splunk Enterprise Security
Agency: Department of Energy - SLAC - SLAC National Accelerator Laboratory (SC43 OIM)
Problem addressed: Clustering and Classification events
Purpose and benefits: Improved automation of security threat hunting
Topic area: Cybersecurity
Development stage: Deployed
Impact assessment: This AI system not meet the criteria of any of the six pillars that make up High Impact AI in Memorandum M-25-21
First used: 2020-09-01
US federal AI use case: Machine Learning components within CrowdStrike
Agency: Department of Energy - SLAC - SLAC National Accelerator Laboratory (SC43 OIM)
Problem addressed: CrowdStrike uses machine learning to review security events in order to create notifications of detections and incidents for the SLAC Cybersecurity team.
Purpose and benefits: From the use of CrowdStrike's machine learning components, SLAC receives the benefit of visibility to analyze possible security events
Topic area: Cybersecurity
Development stage: Deployed
Impact assessment: This AI system not meet the criteria of any of the six pillars that make up High Impact AI in Memorandum M-25-21
First used: 2021-01-27
US federal AI use case: AskOEDI
Agency: Department of Energy - NREL - National Renewable Energy Laboratory (EE)
Problem addressed: AskOEDI serves as a virtual research assistant to OEDI users.  It provides answers to a variety of user-provided questions using natural language processing and generative machine learning.  Users can get answers to questions about specific datasets,
Purpose and benefits: Making data more accessible and user-friendly for the public.
Topic area: Energy and Environment
Development stage: Deployed
Impact assessment: Tool is designed as an AI research assistant to help users find answers to questions about specific datasets beyond simple keyword searches.  Disclaimers provided with the tool state that it should not be used for strategic decision making, nor actio
First used: 2025-10-01
US federal AI use case: Hanford Search
Agency: Department of Energy - RL - Hanford - Richland Operations Office - Hanford (EM)
Purpose and benefits: The purpose of the Hanford  Search is to provide similar functionality to our Hanford Search application without needing multiple applications. The benefits of the AI are that there is a single interface with multiple uses and the AI can provide better, more relevant search results.  Additionally, users can ask questions in natural language instead of needing to input specific search criteria.
Development stage: Retired
Impact assessment: To be retired
US federal AI use case: AI Chat Bot for IT User Services
Agency: Department of Energy - PPPL - Princeton Plasma Physics Laboratory (SC43 OIM)
Problem addressed: Interactive RAG chat bot model trained on existing, updated and new IT resource documentation in the user space. Platform will be used as an informative method for users to handle tier 1 IT issues and help guide to the correct place.
Purpose and benefits: Interactive RAG chat bot model trained on existing, updated and new IT resource documentation in the user space. Platform will be used as an informative method for users to handle tier 1 IT issues and help guide to the correct place.
Topic area: Science
Development stage: Pilot
Impact assessment: Interactive RAG chat bot model trained on existing, updated and new IT resource documentation in the user space. Platform will be used as an informative method for users to handle tier 1 IT issues and help guide to the correct place.
First used: 2025-09-25
US federal AI use case: Hanford Popfon Search
Agency: Department of Energy - RL - Hanford - Richland Operations Office - Hanford (EM)
Purpose and benefits: The purpose of the Hanford Popfon Search is to provide similar functionality to our employee look-up application without needing multiple applications. The benefits of the AI are that there is a single interface with multiple uses and the previous application, which is older in architecture, can be retired, providing a safer, more secure, and cost effective alternative. Additionally, users can ask questions in natural language instead of needing to input specific search criteria.
Development stage: Retired
Impact assessment: See question 7 - use case retired.
US federal AI use case: AI for Intelligent Automation
Agency: Department of Energy - NE INL - NE Idaho National Laboratory (NE)
Problem addressed: workplace automation
Purpose and benefits: Improve the timeliness and quality of manual work processes through automation where generative AI can make comparisons and decisions using INL procedures and controlled documents, with humans performing final validation and approval.
Topic area: Other
Development stage: Deployed
Impact assessment: Used for general purpose generative AI.
US federal AI use case: Cyber Threat Enrichment
Agency: Department of Energy - NE INL - NE Idaho National Laboratory (NE)
Problem addressed: Cyber threat analysis
Purpose and benefits: Enrich emerging cyber threat data with recent and past analysis data curated from the DOE-CESER Geo Threat Observable project and grid modernization project Deep Learning Malware using TBs of well structured cyber threat. Input vulnreability, weakness, malware inforamtion to find connections to well analyzed cyber threat including attack patterns, known exploited, spast mitigations and detections. When firmware binaries are analyzed and translated to structured threat used to create codified attack surfaces and Firmware or Software Bill of Materials (SBOM) for supply chain tracking
Topic area: Other
Development stage: Deployed
Impact assessment: Not available.
US federal AI use case: Hanford Ai Liaison (HAL) 1.1
Agency: Department of Energy - RL - Hanford - Richland Operations Office - Hanford (EM)
Problem addressed: productivity efficiency
Purpose and benefits: cost savings, increased efficiency, increased productivity, greater analytics of data
Topic area: Admin Functions
Development stage: Deployed
Impact assessment: This AI system does not provide a principle basis for decisions or actions with legal, material binding, or have any significat effects of those items listed in OMB-25-21 in the definition of High Impact.
First used: 2024-10-28
US federal AI use case: Argonne Resilience AI Assistant ARAIA (nee CALLM)
Agency: Department of Energy - GDO HQ - Grid Deployment Office (GDO)
Problem addressed: meeting current administration priorities for a secure and resilient power grid
Purpose and benefits: The AI, the Argonne Resilience AI Assistant (ARAIA) (nee CALLM - Climate Action through Large Language Models), ARAIA is on track to meet the needs and outcomes outlined in the initial project scope and work plan, but is now better positioned to meet future needs and administration goals. addresses the problem of communicating complex climate projections and scientific literature to a broad audience, particularly electric sector stakeholders. It simplifies this information to help these stakeholders identify climate resilience solutions.

Expected benefits include improved communication of climate science, empowering stakeholders to directly address climate change impacts, and accelerating the scalability  to serve a wider range of users. This ultimately leads to more effective resilience planning and potentially cost savings through better informed decision-making. 
Users can interact with the system to retrieve specific data, such as fire weather indices, and receive actionable recommendations on areas like hazard mitigation planning, infrastructure wildfire risk, and comprehensive wildfire impact. This project represents a significant step forward in integrating cutting-edge AI with our resilience planning efforts, ultimately helping communities and decision-makers mitigate the impacts of natural hazards.
Topic area: Energy and Environment
Development stage: Pre-deployment
Impact assessment: The ARAIA (nee CALLM) project will have substantial impact in meeting current administration priorities for a secure and resilient power grid by ensuring that risks to the grid can be mitigated through planning, capital resource allocation
US federal AI use case: WCD-AI
Agency: Department of Energy - ANL - Argonne National Laboratory (SC43 OIM)
Problem addressed: Recommend keyword-based search for relevant Lessons Learned published on DOE OPEXShare.
Purpose and benefits: Recommend keyword-based search for relevant Lessons Learned published on DOE OPEXShare.
Topic area: Other
Development stage: Deployed
Impact assessment: Impact of system failure or erroneous results is negligible.
First used: 2023-01-01
US federal AI use case: AI for Isotopes (Pellet) Inspection
Agency: Department of Energy - ORNL - Oak Ridge National Laboratory (SC43 OIM)
Problem addressed: Safety for employees
Purpose and benefits: 1) Reduce technician radiation exposure. 2) Increased productivity.
Topic area: Energy and Environment
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: OPQ-AI
Agency: Department of Energy - ANL - Argonne National Laboratory (SC43 OIM)
Problem addressed: Semi-automated person ID matching with existing database before new accounts are created.
Purpose and benefits: Significantly reduces person-hours for manual review of incoming people registrations to match with existing database records by recommending most likely matches, if an existing record is identified that matches with the registration details.
Topic area: Admin Functions
Development stage: Deployed
Impact assessment: Impact of system failure or erroneous results is negligible.
First used: 2021-03-01
US federal AI use case: Funding Finder
Agency: Department of Energy - IM-50 - Architecture Engineering Technology and Innovation (IM)
Purpose and benefits: The Funding Finder will aggregate FOAs from different DOE sources and enables users to ask questions when identifying opportunities and developing proposals.
Development stage: Retired
Impact assessment: It is retired.
US federal AI use case: PDF Analyzer
Agency: Department of Energy - IM-50 - Architecture Engineering Technology and Innovation (IM)
Problem addressed: Summarization and knowledge retrieval.
Purpose and benefits: PDF Analyzer will enable teams across the DOE to upload large PDFs and ask questions and generate content related to those PDFs.
Topic area: Admin Functions
Development stage: Deployed
Impact assessment: Does not meet the requirements defined by OMB.
First used: 2024-09-02
US federal AI use case: Hanford  Service Ticket Lookup
Agency: Department of Energy - RL - Hanford - Richland Operations Office - Hanford (EM)
Purpose and benefits: The purpose of the Hanford Service Ticket Lookup is to provide a single interface with for customers to ask questions and get to service tickets without having to navigate extensive menu's, tool bars, and search functions. Eventually, this will include service tickets from multiple platforms, providing the customer with a single interface to do all things service request related. Additionally, users can ask questions in natural language instead of needing to input specific search criteria.
Development stage: Retired
Impact assessment: See question 7 - use case retired.
US federal AI use case: INL AI Virtual Assitant (AiVA)
Agency: Department of Energy - NE INL - NE Idaho National Laboratory (NE)
Problem addressed: work productivity
Purpose and benefits: This chatbot uses commercial chatgpt-like capability to answer questions, provide coaching on processes, summarize and improve communications, and produce code in a variety of formats.  INL has been authorized and has planned activiites in 2025 to begin adding internal INL non-CUI data using RAG.  Examples include the employee handbook and approved controlled documents.
Topic area: Other
Development stage: Deployed
Impact assessment: Used as a general/business chat agent for genAI.
US federal AI use case: Unleashing AI Transformer Models on FPGAs for Accelerating LHC and Particle Physics
Agency: Department of Energy - FNAL - Fermi National Accelerator (SC43 OIM)
Problem addressed: This project centers on the deployment of Transformer models for Field Programmable Gate Arrays (FPGA), in order to seamlessly integrate AI capabilities into particle physics experiments, specifically focusing on the L1 triggering schemes and real-ti
Purpose and benefits: This effort focuses on Transformer models for representation learning on Field Programmable Gate Arrays
(FPGA), in order to seamlessly integrate AI capabilities into particle physics experiments, specifically
focusing on the CMS level-1 (L1) trigger at the High-Luminosity LHC (HL-LHC) and real-time magnet
quench detection. While conventional methods for event identification have limitations, modern AI and
machine learning techniques offer superior alternatives.
Topic area: Science
Development stage: Pre-deployment
Impact assessment: The use case does not have an effect on civil rights/liberties/privacy, access to education/housing/insurance/credit/employment, access to critical government resources/services, human health/safety, critical infrastructure/public  safety
First used: 2025-09-25
US federal AI use case: Hanford Procedure Search
Agency: Department of Energy - RL - Hanford - Richland Operations Office - Hanford (EM)
Purpose and benefits: The purpose of the Hanford  Search is to provide greater service in our customers search for relevant proceedures, which is a main look-up for many of our employees. The benefits of the AI are that there is a single interface with multiple uses and the AI can provide better, more relevant search results.  Additionally, users can ask questions in natural language instead of needing to input specific search criteria.
Development stage: Retired
Impact assessment: To be retired
US federal AI use case: LLM EV
Agency: Department of Energy - NREL - National Renewable Energy Laboratory (EE)
Problem addressed: Large-scale policy analysis to understand permitting barriers to the deployment of electric vehicle charging infrastructure
Purpose and benefits: Making NREL EV-specific data more accessible for researchers and accelerating research in this field.
Topic area: Energy and Environment
Development stage: Deployed
Impact assessment: Not intended to produce outputs that are used as principal basis for decisions or actions that have a legal, material, binding, or significant effect on rights or safety
First used: 2024-10-01
US federal AI use case: AskPRIMR
Agency: Department of Energy - NREL - National Renewable Energy Laboratory (EE)
Problem addressed: The U.S. Department of Energy's Portal and Repository for Information on Marine Renewable Energy (PRIMRE) is an interconnected system of knowledge hubs that provide access to data, information, and other resources for the marine energy community.
Purpose and benefits: Making data more accessible and user-friendly for the public.
Topic area: Energy and Environment
Development stage: Deployed
Impact assessment: Tool is designed as an AI research assistant to help users find answers to questions about specific datasets beyond simple keyword searches.  Disclaimers provided with the tool state that it should not be used for strategic decision making.
First used: 2024-10-01
US federal AI use case: GitHub Copilot with the OpenAI Codex
Agency: Department of Energy - PNNL - Pacific Northwest National Laboratory (SC43 OIM)
Problem addressed: Accelerate coding tasks with AI-assisted code suggestions and automation.
Purpose and benefits: This increases their productivity, allows them to focus more on innovation and research, and accelerates the development of high-quality software solutions for scientific research.
Topic area: IT
Development stage: Deployed
Impact assessment: Does not meet any requiremnts for high Impact use case
First used: 2024-10-01
US federal AI use case: First Alert DataMinr AI
Agency: Department of Energy - NA-IM (Enterprise) - Office of the Associate Administrator for Information Management and Chief Information Officer (HQ-Enterprise) (NNSA HQ)
Problem addressed: combine the text of publicly available news sources about events that share the same time and geographic location
Purpose and benefits: We use this AI service to provide spectial or situational awareness, incidents occuring around NNSA or DOE Site.  Emergency reporting, monitoring, speeds up emergency operations reporting. The AI is being used in place of a large team that would be required for coding and development of emergency services facilitation.  This would be a cost saving software for the Federal government.
Topic area: Emergency Mgmt
Development stage: Deployed
Impact assessment: This use case is determined to be not high-impact base on definitoin in Section 5 of the OMB Memorandum M-25-21.
First used: 2025-01-03
US federal AI use case: Yurts AI search function
Agency: Department of Energy - SLAC - SLAC National Accelerator Laboratory (SC43 OIM)
Problem addressed: Access to data in various silos
Purpose and benefits: Easier access to appropriate data
Topic area: IT
Development stage: Deployed
Impact assessment: This AI system does not meet the criteria of any of the six pillars that make up High Impact AI in Memorandum M-25-21
First used: 2024-03-13
US federal AI use case: Interactive platform to help review and create "Promoting Inclusive and Equitable Research" Plans
Agency: Department of Energy - PPPL - Princeton Plasma Physics Laboratory (SC43 OIM)
Purpose and benefits: A trained and informed model that can help to review PIER plans for accuracy, consistency and also to help integrate specific PPPL DEIA goals and initiatives, aligned with input from the user, helping to clearly define the goals of the research plan.
Development stage: Retired
Impact assessment: Retired
US federal AI use case: Energy Wizard
Agency: Department of Energy - NREL - National Renewable Energy Laboratory (EE)
Problem addressed: The tool aims to explore and extract meaningful insights from NREL's vast database of publications including but not limited to technical reports, presentations, and conference papers. There are over 56,000 publications in the NREL research hub and t
Purpose and benefits: Making NREL data more accessible for researchers and accelerating research.
Topic area: Energy and Environment
Development stage: Deployed
Impact assessment: The tool is currently only available internally and serves as a research tool that enables the discovery and evaluation of NREL published research.
First used: 2024-08-01
US federal AI use case: LANL AI Portal
Agency: Department of Energy - LANL - Los Alamos National Lab (LAFO)
Problem addressed: "Democratized access to open-source/open-weights Large Language Models (LLMs) for general purpose office productivity, research of AI models, software development, operational streamlining, code development "
Purpose and benefits: Democratized access to open-source/open-weights Large Language Models (LLMs) for general purpose office productivity, research of AI models, software development, operational streamlining, code development
Topic area: Admin Functions
Development stage: Deployed
Impact assessment: General purpose business system
First used: 2025-01-06
US federal AI use case: SmartPD Creator
Agency: Department of Energy - IM-50 - Architecture Engineering Technology and Innovation (IM)
Problem addressed: It improves the speed and accuracy for DOE employees to create position descriptions.
Purpose and benefits: The time to hire much needed resources will be reduced and the process will be greatly improved.
Topic area: Admin Functions
Development stage: Deployed
Impact assessment: It does not meet the definition defined by OMB.
First used: 2024-09-02
US federal AI use case: ChatGPT Enterprise
Agency: Department of Energy - LANL - Los Alamos National Lab (LAFO)
Problem addressed: "General business productivity, research of AI models "
Purpose and benefits: General business productivity, research of AI models
Topic area: Admin Functions
Development stage: Deployed
Impact assessment: General purpose business system
First used: 2024-05-27
US federal AI use case: Argo
Agency: Department of Energy - ANL - Argonne National Laboratory (SC43 OIM)
Problem addressed: Broad usage across science and lab-ops for use cases that could benefit with genAI techniques.
Purpose and benefits: Enables anyone within the Argonne community to leverage text-based generative AI with their Argonne-specific information and data, including sensitive research or operational data up to and including CUI.
Topic area: Other
Development stage: Deployed
Impact assessment: Impact of system failure or erroneous results is negligible.
First used: 2023-11-01
US federal AI use case: AI Chat Bot for Facility Sustainability Practices
Agency: Department of Energy - PPPL - Princeton Plasma Physics Laboratory (SC43 OIM)
Purpose and benefits: Interactive RAG chat bot model trained on facility recycling, composting and trashing guidelines to inform users how to handle niche cases for sustainably getting rid of unwanted items. This should reduce confusion when throwing items out and also increase the amount of properly recycled items at PPPL.
Development stage: Retired
Impact assessment: Retired
US federal AI use case: AskGDR
Agency: Department of Energy - NREL - National Renewable Energy Laboratory (EE)
Problem addressed: AskGDR serves as a virtual research assistant to GDR users.  It provides answers to a variety of user-provided questions using natural language processing and generative machine learning.  Users can get answers to questions about specific datasets.
Purpose and benefits: Making data more accessible and user-friendly for the public.
Topic area: Energy and Environment
Development stage: Deployed
Impact assessment: Tool is designed as an AI research assistant to help users find answers to questions about specific datasets beyond simple keyword searches.
First used: 2024-10-01
US federal AI use case: Topic Modeling for Energy.gov
Agency: Department of Energy - PA HQ -  Office of Public Affairs (PA)
Purpose and benefits: Minimize time spent through manual effort of reading and tagging 100,000 Energy.gov webpages.
Development stage: Retired
Impact assessment: Because it doesn't impact an individual or entity's civil rights, civil liberties, or privacy; or an individual or entity's access to education, housing, insurance, credit, employment, and other programs; an individual or entity's access to critical
US federal AI use case: Boston Dynamics Spot Robotics
Agency: Department of Energy - Y-12 - Consolidated Nuclear Security Y-12 (YFO)
Problem addressed: Obstacle avoidance without human intervention
Purpose and benefits: Automation of the robots movements
Topic area: Emergency Mgmt
Development stage: Deployed
First used: 2025-07-05
US federal AI use case: DNA-P Use Cases Leaverging Artificial Intellegence  (Pilot)
Agency: Department of Energy - NA-IM (Enterprise) - Office of the Associate Administrator for Information Management and Chief Information Officer (HQ-Enterprise) (NNSA HQ)
Problem addressed: "- identify data clusters/trend analysis - identify data discrepencies/data enrichment - generate suggestions (including generating reports, data linkages, and courses of action) - generate graphical and natural language analyses"
Purpose and benefits: "-save time for DOE DNA-P users
- improve DOE/NNSA data quality
- improve DOE/NNSA safety operations"
Topic area: Other
Development stage: Pilot
Impact assessment: This use case is determined to be not high-impact base on definitoin in Section 5 of the OMB Memorandum M-25-21.
First used: 2024-04-01
US federal AI use case: Advanced Peer to Peer Transactive Energy Platform with Predictive Optimization
Agency: Department of Energy - BNL - Brookhaven National Laboratory (SC43 OIM)
Problem addressed: Applying AI/ML to optimize renewable energy generation and consumption on Smart Grid with block chain technologies
Purpose and benefits: Applying AI/ML to optimize renewable energy generation and consumption on Smart Grid with block chain technologies
Topic area: Science
Development stage: Pre-deployment
Impact assessment: Does not meet definition
US federal AI use case: ServiceNow Virtual Agent Natural Language Understanding
Agency: Department of Energy - NR HQ - Naval Reactors (NR)
Problem addressed: Aid in users receiving better IT support for incident reporting and service delivery.
Purpose and benefits: Quicker and easier access for users to access pre-built IT Service Management incident and request templates.
Topic area: IT
Development stage: Deployed
Impact assessment: System is used as part of IT Service Management and does not meet the criteria outlined in section 5 of OMB Memorandum M-25-21.
First used: 2025-06-30
US federal AI use case: ServiceNow Predictive Intelligence
Agency: Department of Energy - SLAC - SLAC National Accelerator Laboratory (SC43 OIM)
Problem addressed: Reduce error rate of categorization of incidents in ServiceNow
Purpose and benefits: Reduction of errors in the categorization of incidents
Topic area: IT
Development stage: Pre-deployment
Impact assessment: This AI system does not meet the criteria of any of the six pillars that make up High Impact AI in Memorandum M-25-21
US federal AI use case: Microsoft Bing Service
Agency: Department of Energy - EMLA - EM Los Alamos Field Site (EM)
Purpose and benefits: AI was automatically integrated into the product without an identified benefit to the organization.
Topic area: IT
Development stage: Deployed
Impact assessment: AI integrated into the software is solely used to provide a user with assistive functions.
First used: 2023-02-01
US federal AI use case: Ariculate 360 AI Assistant
Agency: Department of Energy - EMLA - EM Los Alamos Field Site (EM)
Purpose and benefits: AI was automatically integrated into the product without an identified benefit to the organization.
Topic area: IT
Development stage: Pre-deployment
Impact assessment: AI integrated into the software is solely used to provide a user with assistive functions.
US federal AI use case: Microsoft Azure Quantum Elements
Agency: Department of Energy - PNNL - Pacific Northwest National Laboratory (SC43 OIM)
Problem addressed: Accelerate chemistry and materials discovery using AI, HPC, and quantum-ready tools.
Purpose and benefits: Speeds discovery of new materials and chemicals for energy solutions.
Topic area: Science
Development stage: Pilot
Impact assessment: Does not meet any requiremnts for high Impact use case
First used: 2024-10-01
US federal AI use case: Nanoparticle growth kinetics and mechanism
Agency: Department of Energy - BNL - Brookhaven National Laboratory (SC43 OIM)
Problem addressed: AI is used to digitalize the nanoparticle from TEM images. Morphology and crystalline feature will be made available through AI. Combining with kinetics modeling, AI detects critical material transformation event. The CFN TEM facility will be enhance
Purpose and benefits: AI is used to digitalize the nanoparticle from TEM images. Morphology and crystalline feature will be made available through AI. Combining with kinetics modeling, AI detects critical material transformation event. The CFN TEM facility will be enhanced by AI pipelines.
Topic area: Science
Development stage: Pre-deployment
Impact assessment: Does not meet definition
US federal AI use case: Bernie-AI: Infrastructure Planning Support POC
Agency: Department of Energy - LLNL - Lawrence Livermore National Laboratory (LFO)
Problem addressed: Quick access to specific building, and major asset information to be used for planning and predictive maintenance purposes
Purpose and benefits: Ability to quickly find and access building and asset information to support planning activities
Topic area: IT
Development stage: Pilot
Impact assessment: Not being used to make critical runtime decisions.
First used: 2025-06-30
US federal AI use case: Center for Mesoscale Transport Properties
Agency: Department of Energy - BNL - Brookhaven National Laboratory (SC43 OIM)
Problem addressed: Center for Mesoscale Transport Properties
Purpose and benefits: Center for Mesoscale Transport Properties
Topic area: Science
Development stage: Pre-deployment
Impact assessment: Does not meet definition
US federal AI use case: Develop a Machine Learning Framework for Optimal Computational Campaigns for Complex Uncertain Systems
Agency: Department of Energy - BNL - Brookhaven National Laboratory (SC43 OIM)
Problem addressed: 'Two projects to use machine learning to acclerate the design of optimal strategies and robust computational campaigns for complex systems in the
presence of substantial data and model uncertainty, and/or which have
processes that span multiple scale
Purpose and benefits: 'Two projects to use machine learning to acclerate the design of optimal strategies and robust computational campaigns for complex systems in the
presence of substantial data and model uncertainty, and/or which have
processes that span multiple scales'
Topic area: Science
Development stage: Pre-deployment
Impact assessment: Does not meet definition
US federal AI use case: Microsoft Co-Pilot
Agency: Department of Energy - RL - Hanford - Richland Operations Office - Hanford (EM)
Problem addressed: Better analytics of data in our microsoft applications
Purpose and benefits: Better analytics of data in our microsoft applications
Topic area: Admin Functions
Development stage: Pilot
Impact assessment: This AI system does not provide a principle basis for decisions or actions with legal, material binding, or have any significat effects of those items listed in OMB-25-21 in the definition of High Impact.
First used: 2025-09-01
US federal AI use case: Visual Studio Enterprise
Agency: Department of Energy - EMLA - EM Los Alamos Field Site (EM)
Purpose and benefits: AI was automatically integrated into the product without an identified benefit to the organization.
Topic area: IT
Development stage: Deployed
Impact assessment: AI integrated into the software is solely used to provide a user with assistive functions.
First used: 2023-02-01
US federal AI use case: NLP Data Analytics for Program and Portfolio Insights
Agency: Department of Energy - EE HQ - EE Headquarters (EE)
Problem addressed: Improve analytical capabilities and self service to organizational data.  Increase process efficiency and analytical insights.
Purpose and benefits: Faster and more consistent analysis, earlier risk detection, enhanced decision-making.
Topic area: Admin Functions
Development stage: Pre-deployment
Impact assessment: Produces analytic insights only; does not affect rights, benefits, or binding decisions.
US federal AI use case: Command Media
Agency: Department of Energy - Pantex - PanTeXas Deterrence Pantex (PFO)
Problem addressed: The AI is intended to solve the inefficiency of plant personnel who have questions about policies, procedures, and work instructions by providing a more direct way to find information.
Purpose and benefits: The expected benefit is increased effiency for plant personnel.
Topic area: IT
Development stage: Pre-deployment
Impact assessment: The AI output is not a basis for decisions or actions. It is for information retrieval.
US federal AI use case: Ask CAS
Agency: Department of Energy - SRS - ESB - Savannah River Site - Enterprise System Boundary (SRFO)
Problem addressed: GenAI-RAG to support issues management
Purpose and benefits: Productivity Tool
Topic area: Other
Development stage: Pre-deployment
Impact assessment: End User Productivity Tool
First used: 2024-10-01
US federal AI use case: AI/ML in High Energy Physics Research
Agency: Department of Energy - BNL - Brookhaven National Laboratory (SC43 OIM)
Problem addressed: Within the high energy physics research in the energy, intensity and cosmic frontiers, as well as the advance detector R&D and scientific computing, AI/ML techniques have been developed and applied to solving a variety of problems in studying particl
Purpose and benefits: Within the high energy physics research in the energy, intensity and cosmic frontiers, as well as the advance detector R&D and scientific computing, AI/ML techniques have been developed and applied to solving a variety of problems in studying particle physics and cosmology.
Topic area: Science
Development stage: Pre-deployment
Impact assessment: Does not meet definition
US federal AI use case: ESH&Q NEPA App
Agency: Department of Energy - NE INL - NE Idaho National Laboratory (NE)
Problem addressed: Not available
Purpose and benefits: Speeds up environmental review processes and improves compliance accuracy, reducing delays in project approvals.
Topic area: Other
Development stage: Deployed
Impact assessment: Used for general purpose generative AI within a COTS product.
US federal AI use case: Microsoft OneNote
Agency: Department of Energy - EMLA - EM Los Alamos Field Site (EM)
Purpose and benefits: AI was automatically integrated into the product without an identified benefit to the organization.
Topic area: IT
Development stage: Deployed
Impact assessment: AI integrated into the software is solely used to provide a user with assistive functions.
First used: 2023-02-01
US federal AI use case: OpenAI ChatGPT Pilot
Agency: Department of Energy - LLNL - Lawrence Livermore National Laboratory (LFO)
Problem addressed: Quick access to general knowledge.
Purpose and benefits: Ability to quickly find and access general knowledge and business productivity
Topic area: IT
Development stage: Pilot
Impact assessment: General chatbot knowledge and capabilities
First used: 2025-06-30
US federal AI use case: ACORN (Autonomous Operation for Reactor Technologies)
Agency: Department of Energy - NE INL - NE Idaho National Laboratory (NE)
Problem addressed: AI automatically identifies process models from simulation and operational data, solves for optimal control actions that can achieve user-defined objectives, executes actions and observes system responses
Purpose and benefits: reduce labor and costs to performance operation tasks in advanced reactors and microreactors
Topic area: Other
Development stage: Pilot
Impact assessment: currently focusing on reactor simulator or auxilary moderator displacement rod with minimal impacts on reactor safety
First used: 2023-09-01
US federal AI use case: NIF Shot Analytics & Predictive Maintenance Support Pilot
Agency: Department of Energy - LLNL - Lawrence Livermore National Laboratory (LFO)
Problem addressed: Quick access to specific NIF laser data and problem resolution information
Purpose and benefits: Ability to quickly find and access targeted NIF maintenance knowledge
Topic area: Science
Development stage: Pilot
Impact assessment: Not being used to make critical runtime decisions.
First used: 2025-06-30
US federal AI use case: Merlin - KCNSC Generative AI with RAG
Agency: Department of Energy - KCNSC - Kansas City National Security Campus (KCFO)
Problem addressed: Intended to address the opportunity to enhance overall productivity. No definite 'problem' being solved, just capitalizing on an opportunity to leverage industry investment in generative AI broadly.
Purpose and benefits: It serves as a general productivity enhancer -not driven by a specific problem, but by the opportunity to improve efficiency.
Topic area: IT
Development stage: Pilot
Impact assessment: Output does not serve as a principal basis for decisions or actions that have a legal, material, binding, or significant effect on rights or safety. Assists in developing software code that may accept product, but this AI will not make those decision
First used: 2025-07-16
US federal AI use case: IDAES-PSE
Agency: Department of Energy - NETL - National Energy Technology Laboratory (FECM)
Problem addressed: Offers extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems.
Purpose and benefits: Opitmize the design and operation of complex, interacting technologies and systems.
Topic area: Energy and Environment
Development stage: Pre-deployment
Impact assessment: Limited to a specific area of research
US federal AI use case: NRAP-Open-IAM
Agency: Department of Energy - NETL - National Energy Technology Laboratory (FECM)
Problem addressed: Enables quantification of containment effectiveness and leakage risk at carbon storage sites in the context of system uncertainties and variability.
Purpose and benefits: Enables quantification of effectiveness and risk.
Topic area: Energy and Environment
Development stage: Pre-deployment
Impact assessment: Limited to a specific area of research
US federal AI use case: SMMM
Agency: Department of Energy - BNL - Brookhaven National Laboratory (SC43 OIM)
Problem addressed: AI/ML is being used to evaluate measurements in real-time during simultaneous experiments on two beamlines and then drive subsequent data collection on both of the beamlines to maximize the scientific value generated per time.
Purpose and benefits: AI/ML is being used to evaluate measurements in real-time during simultaneous experiments on two beamlines and then drive subsequent data collection on both of the beamlines to maximize the scientific value generated per time.
Topic area: Science
Development stage: Pre-deployment
Impact assessment: Does not meet definition
US federal AI use case: Custom GenAI for eVinci Microreactor Engineering (MauroGPT)
Agency: Department of Energy - NE INL - NE Idaho National Laboratory (NE)
Problem addressed: Reactor engineers spending extensive time manually iterating through documents during the reactor engineering process
Purpose and benefits: Reactor engineers save time by using the AI to quickly find answers and relevant source documents.
Topic area: Other
Development stage: Pilot
Risk category: High-impact
First used: 2025-08-04
US federal AI use case: AI Builder Document Scraping
Agency: Department of Energy - NR HQ - Naval Reactors (NR)
Problem addressed: Enhance and automate PDF scraping for large sets of PDF files.
Purpose and benefits: Improved Microsoft PDF scraping model that allows the user to provide a training set for their PDFs.
Topic area: Admin Functions
Development stage: Deployed
Impact assessment: AI Builder scrapes PDF files for text.  The end user is responsible for verifying the quality of the final text. This does not meet the criteria outlined in section 5 of OMB Memorandum M-25-21.
First used: 2025-02-03
US federal AI use case: Microsoft Azure Authoring Tools
Agency: Department of Energy - EMLA - EM Los Alamos Field Site (EM)
Purpose and benefits: AI was automatically integrated into the product without an identified benefit to the organization.
Topic area: IT
Development stage: Deployed
Impact assessment: AI integrated into the software is solely used to provide a user with assistive functions.
First used: 2023-02-01
US federal AI use case: WETO SA
Agency: Department of Energy - NREL - National Renewable Energy Laboratory (EE)
Problem addressed: Assess the developable quantity and quality of the renewable resources.
Purpose and benefits: It seeks to better understand the uncertainty and impact of siting considerations and to understand when and where wind technological innovation may help to overcome potential land barriers.
Topic area: Energy and Environment
Development stage: Deployed
Impact assessment: Not intended to produce outputs that are used as principal basis for decisions or actions that have a legal, material, binding, or significant effect on rights or safety
First used: 2024-10-01
US federal AI use case: AI Assistant Phase 2 Simple Chat
Agency: Department of Energy - ORNL - Oak Ridge National Laboratory (SC43 OIM)
Problem addressed: Emplyees at ORNL more productive
Purpose and benefits: Enhanced employee productivity
Topic area: Admin Functions
Development stage: Deployed
Impact assessment: Doesn't meet the criteria.
First used: 2025-08-04
US federal AI use case: Drone Imagery Analysis
Agency: Department of Energy - LM HQ - Office of Legacy Management (LM)
Problem addressed: AI used to allow drone to improve human safety in imagery collection and analysis.
Purpose and benefits: Simple and efficient asset inspection with improved safety factor.
Topic area: Energy and Environment
Development stage: Pilot
Impact assessment: Does not meet definition
First used: 2022-10-01
US federal AI use case: OpenAI Enterprise
Agency: Department of Energy - PNNL - Pacific Northwest National Laboratory (SC43 OIM)
Problem addressed: Provide enterprise-grade AI assistance with secure access to OpenAI GPT models.
Purpose and benefits: Provides secure, reliable access to advanced AI capabilities for research.
Topic area: Science
Development stage: Deployed
Impact assessment: This AI use case does not serve as a principal basis for decisions or actions with legal, material, and binding
First used: 2024-10-01
US federal AI use case: VIPER (Visualizaiton for Predictive Maintenance Recommendation)
Agency: Department of Energy - NE INL - NE Idaho National Laboratory (NE)
Problem addressed: VIPER presents comprehensive system health diagnostics, explainability metrics, and actionable recommendations to system engineers at nuclear power plants, enabling informed decision-making through an easy-to-use visualization interface. A multi-mode
Purpose and benefits: reduce labor and costs to performance maintenance tasks in existing light water reactors
Topic area: Other
Development stage: Pilot
Impact assessment: Does not meet any requiremnts for high Impact use case
First used: 2024-09-01
US federal AI use case: Decisions AI
Agency: Department of Energy - PNNL - Pacific Northwest National Laboratory (SC43 OIM)
Problem addressed: Enhance meeting management by integrating AI insights with Decisions platform.
Purpose and benefits: Enhances meeting effectiveness and decision-making outcomes.
Topic area: Admin Functions
Development stage: Deployed
Impact assessment: Does not meet any requiremnts for high Impact use case
First used: 2024-10-01
US federal AI use case: Poseidon
Agency: Department of Energy - SRS - ESB - Savannah River Site - Enterprise System Boundary (SRFO)
Problem addressed: Content analysis across domains and structured/unstructured content for SCRM
Purpose and benefits: Productivity Tool
Topic area: Procurement and Finance Mgmt
Development stage: Pre-deployment
Impact assessment: End User Productivity Tool
US federal AI use case: Soil Moisture Modeling
Agency: Department of Energy - LM HQ - Office of Legacy Management (LM)
Problem addressed: Machine learning  solves issues with soil moisture by enhancing accuracy and efficiency in data analysis
Purpose and benefits: The ability to determine evapotranspiration rates on disposal cell cover using publicly available data from satellites.
Topic area: Energy and Environment
Development stage: Pilot
Impact assessment: This AI use case does not serve as a principal basis for decisions or actions with legal, material, and binding
First used: 2022-02-01
US federal AI use case: Azure Document Intelligence
Agency: Department of Energy - NR HQ - Naval Reactors (NR)
Problem addressed: Enhance and automate PDF scraping  for large sets of PDF files.
Purpose and benefits: Improved Microsoft PDF scraping model that allows the user to provide a training set for their PDFs.
Topic area: Admin Functions
Development stage: Pre-deployment
Impact assessment: Azure Document Intelligence scrapes PDF files for text.  The end user is responsible for verifying the quality of the final text/product. This does not meet the criteria outlined in section 5 of OMB Memorandum M-25-21.
US federal AI use case: AI-Enhanced Hub
Agency: Department of Energy - PNNL - Pacific Northwest National Laboratory (SC43 OIM)
Problem addressed: Enhance staff matching and profiles with AI-driven HUB search capabilities.
Purpose and benefits: Enhances collaboration and expertise matching across the lab.
Topic area: HR
Development stage: Pre-deployment
Impact assessment: Does not meet any requiremnts for high Impact use case
First used: 2024-10-01
US federal AI use case: OpenText for Records Management (Email Auto-Classification)
Agency: Department of Energy - EE HQ - EE Headquarters (EE)
Development stage: Retired
Impact assessment: Does not fall within the requirements for high impact.
US federal AI use case: Apple Intelligence
Agency: Department of Energy - EMLA - EM Los Alamos Field Site (EM)
Purpose and benefits: AI was automatically integrated into the product without an identified benefit to the organization.
Topic area: IT
Development stage: Deployed
Impact assessment: AI integrated into the software is solely used to provide a user with assistive functions.
First used: 2024-10-28