GreatNorthCollective/greatnorth-us-federal-ai-inventory huggingface dataset:
US federal AI use case: Grants Program Administration - BEAD Monitoring Plan Agent Pilot
Agency: Department of Commerce - NTIA
Problem addressed: The AI system—referred to as the BEAD Monitoring Agent—is designed to enhance the ability of Federal Program Officers (FPOs) to support Eligible Entities (EEs) in monitoring their subrecipients after a Final Proposal (FP) is approved. The motivation for deploying this AI is grounded in NTIA’s need to rapidly and effectively understand the contents of each EE’s FP to support post-award monitoring.
Benefits:
1. Faster, More Thorough Review: The AI agent quickly reviews EE subgrantee monitoring plans by comparing them against a “gold standard,” helping FPOs identify best practices, inconsistencies, and gaps
2. Enhanced Risk Mitigation: By providing recommendations on oversight and potential mitigation actions, the AI helps identify areas where closer monitoring or NTIA support may be needed
3. Standardization and Transparency: The AI outputs enable more standardized and data-driven oversight across diverse plans, informing risk assessments and follow-up activities
US federal AI use case: Grants Program Administration - Tiered Environmental Assessment AI Pilot
Agency: Department of Commerce - NTIA
Problem addressed: The NTIA Tiered EA AI Pilot leverages AI to streamline the initial drafting of the “Affected Environment” section in NTIA Tiered Environmental Assessment templates by integrating project-specific data and geospatial resources. The pilot aims to evaluate AI’s effectiveness in drafting content within the tiered EA; if successful, NTIA may expand the use case to provide eligible entities with pre-populated tiered EAs based on submitted information, rather than blank templates, to accelerate permitting.
Benefits:
1. Efficiency: Automates a typically time-consuming, manual process, reducing turnaround time for drafting EAs.
2. Consistency and Standardization: By pre-populating sections with structured data and draft text, the AI helps ensure consistency across assessments and adherence to templates.
3. Reduced Burden on Entities: Utilizes information already submitted to NTIA, combined with federally available data, to minimize the effort required by entities in preparing the initial draft of a tiered EA.
US federal AI use case: NTIA Grants Portal (NGP) - AI Summarization, Analytics, and Automations
Agency: Department of Commerce - NTIA
Problem addressed: Our team is exploring using AI to support our grant program administration, specifically supporting some AI-enable knowledge management for our internal team and supporting reviews of post award technical/progress/performance/financial reports to identify trends, identify inconsistencies, increase efficiencies in processing and monitoring tasks, etc.  The latter may be more a mix of predictive and generative AI.
US federal AI use case: Using AI to assess the AI-readiness of Commerce data
Agency: Department of Commerce - OS
Problem addressed: The system measures the ability of large language models to accurately respond to questions that require an understanding of federal statistical open data resources. It will help the Department identify data quality gaps and improve the quality of departmental data by making it AI-ready.
US federal AI use case: BAS Assist
Agency: Department of Commerce - OS
Problem addressed: BAS Assist, a generative AI chatbot that supports users of the enterprise BAS applications. BAS Assist provides real-time guidance in natural, conversational language, enabling users to more effectively complete application tasks, resolve common issues, and access technical assistance without requiring direct staff intervention. This tool enhances accessibility, reduces administrative burden, and improves service delivery to state, local, and tribal government partners. BAS Assist is being developed and deployed in alignment with the Department’s enterprise AI risk management protocols, including those articulated under Section 3(a) of M-25-21 for inventory reporting, post-deployment monitoring, and incident response.
US federal AI use case: DOC Chat
Agency: Department of Commerce - OS
US federal AI use case: USAi.gov
Agency: Department of Commerce - OS
Problem addressed: The Department is deploying USAI.gov, a government-wide generative AI capability provided by the General Services Administration (GSA), designed to provide employees with secure, role-appropriate access to advanced large-language-model tools. USAI.gov enables bureaus to rapidly pilot and scale AI use cases—ranging from document drafting and data summarization to policy analysis—within a controlled environment that incorporates enterprise risk management, security safeguards, and privacy protections. This effort embodies a DOC enterprise approach to technology modernization, ensuring that bureaus leverage shared resources to realize efficiencies, reduce duplication, and accelerate innovation. Governance for USAI.gov is planned for coordination through the Office of the Chief Information Officer (OCIO), in close consultation with bureau CIOs, bureau AI Leads, and functional area experts across cybersecurity, data governance, privacy, civil rights, and acquisitions.
US federal AI use case: PRISM BidScale
Agency: Department of Commerce - OS
Problem addressed: 4 month pilot of PRISM's BidScale automation tool.  Bidscale is built for Government contracting processes, policies, and standards to automate documentation in compliance with federal requirements.
US federal AI use case: Scientific Code Development Assistance
Agency: Department of Commerce - NOAA
US federal AI use case: Implement MS365 Copilot in OS
Agency: Department of Commerce - OS
Problem addressed: Enable this product function in OS.  From this implementation a playbook will be created that will be published to all Operating Units that explains the guidelines and standards for implementation in their areas.
US federal AI use case: Prior Art Search: AI Retrieval for Patent Search (PSAI) (Similarity Search)
Agency: Department of Commerce - USPTO
Problem addressed: AI-assisted feature for examiners to locate similar prior-art documents more effectively when performing a traditional search by finding additional documents similar to a document they are reviewing as part of their existing search.
US federal AI use case: Pre-Exam Application: CPC Classification
Agency: Department of Commerce - USPTO
Problem addressed: Auto-assign patent utility classification (CPC) symbols to patent utility documents. CPC symbols, currently over 250,000, are applied to an application for classification, assisting examination and public search by classification when an application is published. CPC is constantly expanding as new technical fields emerge.
US federal AI use case: TM Word and Image Search Tool (TWIST)
Agency: Department of Commerce - USPTO
Problem addressed: Provide the capability for external customers to perform clearance searches prior to filing  through use of Clarivate TMVision or other AI technology.
US federal AI use case: Prior Art Search: Patent Image Search
Agency: Department of Commerce - USPTO
Problem addressed: Auto-compare an input image uploaded by the examiner with images in available databases yielding image results based on, and sortable by, similarity to the input image.
US federal AI use case: Pre-Exam Application: Front End Document Code Quality Control
Agency: Department of Commerce - USPTO
Problem addressed: Review the patent applicant assigned document codes against submitted patent documents to confirm validity based on document content. Finally, confirm validity or suggest another applicable code.
US federal AI use case: GenAI platform and applications for general productivity
Agency: Department of Commerce - USPTO
Problem addressed: SCOUT LLM helps staff create content, simplify complex topics, and explore new ideas while ensuring data security. It stays current with the rapidly evolving LLM landscape by offering access to top-tier models from OpenAI, Anthropic, Meta, among others. Additionally, it provides robust customization options to fine-tune outputs
US federal AI use case: Prior Art Search: Automated Search AI Pilot (ASAP! Report)
Agency: Department of Commerce - USPTO
Problem addressed: Provide applicants with an initial communication identifying a “top ten list” of potential prior art issues in need of attention. By generating an AI-Assisted Search Results Notice (ASRN), ASAP! will afford applicants an early opportunity to assess their claims against the prior art before substantive examination.
US federal AI use case: First Office Action Creation: Claim Comparision for Double Patenting
Agency: Department of Commerce - USPTO
Problem addressed: Compare claims in patent family documents to alert examiners of potential double patenting concerns to enhance overall patent quality and durability
US federal AI use case: First Office Action Creation: Examination Analysis Determination/Analysis of Informalities (35 USC 101 and 112)
Agency: Department of Commerce - USPTO
Problem addressed: Improve patent quality by providing examiners a report highlighting potential informality issues, as well as potential issues under 35 USC 112 and 101
US federal AI use case: Coastal Change Analysis Program (C-CAP)
Agency: Department of Commerce - NOAA
US federal AI use case: Patent Fraud Detection & Mitigation
Agency: Department of Commerce - USPTO
Problem addressed: Auto-identify  fraudulent and misrepresented patent applications to prevent/reduce such applications
US federal AI use case: Assisted software development
Agency: Department of Commerce - USPTO
Problem addressed: Support software developers in code analysis, test case generation, debugging, and documentation.
US federal AI use case: Call Center Automations (Internal)
Agency: Department of Commerce - USPTO
Problem addressed: Leverage ServiceNow’s AI-based NowAssist to support Tier 1 and Tier 2 service desk staff to support basic IT requests s
US federal AI use case: Pre-Exam Application Processing: Trademark Center (TM Center) AI Automation
Agency: Department of Commerce - USPTO
Problem addressed: Auto-analyze mark drawing images and suggest associated design search codes, auto-examine the literal element field and generate potential pseudo mark text, auto-examine goods and services to preliminarily assign one or more international classes to an application, if needed, auto-analyze the mark drawing uploads and suggest mark descriptions for marks with visual elements including a color claim for marks indicating a potential color aspect.
US federal AI use case: Evaluate AI Models for Probabilistic Hurricane Predictions
Agency: Department of Commerce - NOAA
US federal AI use case: Evaluate AI for Forecasting Fronts
Agency: Department of Commerce - NOAA
US federal AI use case: AI-Driven Global Forecast Model and Ensemble
Agency: Department of Commerce - NOAA
US federal AI use case: AI-based Biased Correction and Downscaling for Weather Models
Agency: Department of Commerce - NOAA
US federal AI use case: Improving Accuracy of Physical-based Models
Agency: Department of Commerce - NOAA
US federal AI use case: Improve Background Error Modeling for JEDI
Agency: Department of Commerce - NOAA
US federal AI use case: Enhanced Precipitation Forecasting
Agency: Department of Commerce - NOAA
US federal AI use case: ChatGPT Enterprise
Agency: Department of Commerce - ITA
US federal AI use case: Ensemble Analysis to Identify Error Sources
Agency: Department of Commerce - NOAA
US federal AI use case: Enhanced Fire Weather, Aviation, and Storm Surge Forecast Guidance
Agency: Department of Commerce - NOAA
US federal AI use case: Enhanced Flood Risk and Impact Modeling
Agency: Department of Commerce - NOAA
US federal AI use case: Fisheries ESA Section 7 Biological Opinions and EFH Consultations
Agency: Department of Commerce - NOAA
US federal AI use case: Fisheries Global Seafood Data System (GSDS) Audit Support Application
Agency: Department of Commerce - NOAA
US federal AI use case: Optics Data Processing
Agency: Department of Commerce - NOAA
US federal AI use case: Electronic Monitoring
Agency: Department of Commerce - NOAA
US federal AI use case: Passive Acoustic Monitoring
Agency: Department of Commerce - NOAA
US federal AI use case: Active Acoustics
Agency: Department of Commerce - NOAA
US federal AI use case: OLE Looker
Agency: Department of Commerce - NOAA
US federal AI use case: Google AgentSpace
Agency: Department of Commerce - ITA
US federal AI use case: Grants
Agency: Department of Commerce - NOAA
US federal AI use case: Streamlining Fisheries DevSecOps with Gemini Code Assist
Agency: Department of Commerce - NOAA
US federal AI use case: ENSO and Hurricane Outlooks using observed/analyzed fields
Agency: Department of Commerce - NOAA
US federal AI use case: Drought outlooks by using ML techniques
Agency: Department of Commerce - NOAA
US federal AI use case: NN/ML for OPC probabilistic guidance and GEFS-Waves
Agency: Department of Commerce - NOAA
US federal AI use case: ProbSR (probability of subfreezing roads
Agency: Department of Commerce - NOAA
US federal AI use case: WAWENETS
Agency: Department of Commerce - NTIA
US federal AI use case: AI/ML based atmospheric physics parameterizations for numerical weather prediction
Agency: Department of Commerce - NOAA
US federal AI use case: Detecting rip currents with coastal imagery
Agency: Department of Commerce - NOAA
US federal AI use case: AI QC of water level observations
Agency: Department of Commerce - NOAA
US federal AI use case: Real Time Classification for the Economic Census
Agency: Department of Commerce - Census
US federal AI use case: Flowcytobot imaging system data using ML
Agency: Department of Commerce - NOAA
US federal AI use case: HABScope
Agency: Department of Commerce - NOAA
US federal AI use case: IOOS Coastal Modeling Cloud Computing Sandbox
Agency: Department of Commerce - NOAA
US federal AI use case: GitHub Copilot for Code Modernization
Agency: Department of Commerce - BEA
US federal AI use case: Classifying communitity shifts with Self Organizing Maps
Agency: Department of Commerce - NOAA
US federal AI use case: Picky
Agency: Department of Commerce - NOAA
US federal AI use case: Automated Change Detection
Agency: Department of Commerce - Census
US federal AI use case: School staff information extraction from web page text
Agency: Department of Commerce - Census
US federal AI use case: Census Bureau Demographic Frame Person-Place Model
Agency: Department of Commerce - Census
US federal AI use case: Race and Ethnicity Autocoding
Agency: Department of Commerce - Census
US federal AI use case: Amazon Web Services NLP, Classification, Text Mining
Agency: Department of Commerce - ITA
US federal AI use case: Information extraction for web scraped data for Group Quarters frame enhancement
Agency: Department of Commerce - Census
US federal AI use case: Current Population Survey (CPS) Name Screening Tool
Agency: Department of Commerce - Census
US federal AI use case: Linkage and Matching Program (LaMP)
Agency: Department of Commerce - Census
US federal AI use case: Census Research Exploration and Analysis Tool (CREAT)
Agency: Department of Commerce - Census
US federal AI use case: Dr. NAICS LLM
Agency: Department of Commerce - Census
US federal AI use case: Automating Multilingual Census Data Processing: An AI and Transformer-Based Pipeline for Efficient Language Detection and Translation for Short-Text
Agency: Department of Commerce - Census
US federal AI use case: FAQ for SMaRT
Agency: Department of Commerce - Census
US federal AI use case: Statistical package syntax development and debugging
Agency: Department of Commerce - Census
US federal AI use case: DSD Python Code Translation
Agency: Department of Commerce - Census
US federal AI use case: Census API GPT
Agency: Department of Commerce - Census
US federal AI use case: Google Public Sector NLP, Classification, Text Mining
Agency: Department of Commerce - ITA
US federal AI use case: Natural Language Search for data.census.gov
Agency: Department of Commerce - Census
US federal AI use case: ACES CAPEX (structures, equipment, other) Machine Learning
Agency: Department of Commerce - Census
US federal AI use case: Structure from Motion photomosaic work in SE/Caribbean
Agency: Department of Commerce - NOAA
US federal AI use case: Utilizing Machine Learning for Coral Identification at Flower Garden Banks National Marine Sanctuary
Agency: Department of Commerce - NOAA
US federal AI use case: FirstNet Authority Communications Topaz Labs Photo Editing
Agency: Department of Commerce - FirstNet
US federal AI use case: Global Business Navigator Chatbot
Agency: Department of Commerce - ITA
US federal AI use case: Generative AI Tools Pilot - Global Markets
Agency: Department of Commerce - ITA
Problem addressed: ITA developed the Generative AI Tools Pilot – Global Markets use case to enhance the efficiency and quality of market research analysis. The tool enables analysts to generate initial drafts of market research reports using public data sources, produce data-driven insights to identify top markets and recommend strategic directions, and integrate seamlessly with existing workflows. This support allows analysts to refine and finalize comprehensive, actionable reports more effectively.
US federal AI use case: Generative AI Tools Pilot - Enterprise & Solutions Architecture
Agency: Department of Commerce - ITA
US federal AI use case: Streamline Spectrum Activities
Agency: Department of Commerce - NTIA
US federal AI use case: Spectrum Visualizations
Agency: Department of Commerce - NTIA
US federal AI use case: Google Colab and VertexAI
Agency: Department of Commerce - ITA
US federal AI use case: Use of Lexis. Other searches for legal research
Agency: Department of Commerce - NTIA
US federal AI use case: Improving the quality of NGS's GPS on Benchmarks with machine learning
Agency: Department of Commerce - NOAA
US federal AI use case: Grammarly
Agency: Department of Commerce - NIST
US federal AI use case: Supporting the Development of System Resilience Indicators for Wild Rice in Lake Superior, Lake Michigan, and Lake Huron
Agency: Department of Commerce - NOAA
US federal AI use case: Steller sea lion brand sighting
Agency: Department of Commerce - NOAA
US federal AI use case: Great Lakes Coastal Assembly Coastal Wetland Conservation Framework
Agency: Department of Commerce - NOAA
US federal AI use case: BANTER, a machine learning acoustic event classifier
Agency: Department of Commerce - NOAA
US federal AI use case: Automated Post-Disaster Vessel and Debris Mapping from Remotely Sensed Imagery
Agency: Department of Commerce - NOAA
US federal AI use case: LightningCast: A lightning nowcasting model
Agency: Department of Commerce - NOAA
US federal AI use case: Machine Learning Collaboration Yields New Methods to Measure Shoreline Marine Debris
Agency: Department of Commerce - NOAA
US federal AI use case: Anthropic - Claude For Government
Agency: Department of Commerce - ITA
Problem addressed: Deploy Claude AI to automate the generation of comprehensive analytical reports, data visualizations, and documentation for research and policy analysis workflows. The system will process complex datasets to produce polished, multi-page deliverables including executive summaries, detailed findings, statistical charts, and interactive visualizations. Claude's artifact generation capabilities enable creation of complete, production-ready outputs that support iterative refinement through targeted edits to specific sections, charts, or formatting without regenerating entire documents.
US federal AI use case: Mussel Watch data management
Agency: Department of Commerce - NOAA
US federal AI use case: Ice seal detection and species classification in multispectral aerial imagery
Agency: Department of Commerce - NOAA
US federal AI use case: Edge AI survey payload development
Agency: Department of Commerce - NOAA
US federal AI use case: Steller sea lion automated count program
Agency: Department of Commerce - NOAA
US federal AI use case: Use of an Imaging Flow Cytobot for identification of phytoplankton and HABs in Alaska's Large Marine Ecosystems
Agency: Department of Commerce - NOAA
US federal AI use case: Automated classification of zooplankton images
Agency: Department of Commerce - NOAA
US federal AI use case: Acoustic and image-based habitat classification in the Gulf of Alaska using machine learning
Agency: Department of Commerce - NOAA
US federal AI use case: Virtual Assistant (Public)
Agency: Department of Commerce - USPTO
Problem addressed: Chatbot on USPTO 's public-facing website to answer patent and trademark questions from the general public
US federal AI use case: Automated detection and abundance estimation of salmon and pollock in Alaska's walleye pollock fishery
Agency: Department of Commerce - NOAA
US federal AI use case: Pre-Exam Application: Skill Group Matching
Agency: Department of Commerce - USPTO
Problem addressed: Auto-assign patent cases to examiner-groups based on application subject matter.
US federal AI use case: AI for Operations Center
Agency: Department of Energy - ANL - Argonne National Laboratory (SC43 OIM)
Problem addressed: Reduce human effort and increase efficiency in identifying Lessons Learned to work planning.
Purpose and benefits: Increase awareness and use of Lessons Learned.
Topic area: Other
Development stage: Deployed
Impact assessment: Impact of system failure or erroneous results is negligible.
First used: 2022-01-01
US federal AI use case: Natural Language Processing
Agency: Department of Energy - NETL - National Energy Technology Laboratory (FECM)
Problem addressed: Developed natural language processing (NLP) algorithms will be used to help categorize and understand various energy storage efforts in the R&D communities. Additionally, trends within the discovered and selected topical focus areas in energy storage
Purpose and benefits: Categorize and understand energy storage efforts
Topic area: Energy and Environment
Development stage: Pre-deployment
Impact assessment: Limited to a specific area of research
US federal AI use case: DOE AI Data Infrastructure System
Agency: Department of Energy - NETL - National Energy Technology Laboratory (FECM)
Problem addressed: Leveraging generative AI and cloud-enabled data infrastructure to improve carbon capture and storage user experience
Purpose and benefits: Improve connectivity and create adaptive user interface
Topic area: Energy and Environment
Development stage: Pre-deployment
Impact assessment: Limited to a specific area of research
US federal AI use case: Creation of polymer datasets and inverse design of polymers with targeted backbones having 
High CO2 permeability and high CO2/N2 selectivity.
Agency: Department of Energy - NETL - National Energy Technology Laboratory (FECM)
Problem addressed: Creation of polymer datasets and inverse design of polymers with targeted backbones having 
High CO2 permeability and high CO2/N2 selectivity.
Purpose and benefits: Predict permeability and selectivity of polymers
Topic area: Energy and Environment
Development stage: Pre-deployment
Impact assessment: Limited to a specific area of research
US federal AI use case: To use AI to calibrate the simulation model by matching simulation data with production history data.
Agency: Department of Energy - NETL - National Energy Technology Laboratory (FECM)
Problem addressed: To use AI to calibrate the simulation model by matching simulation data with production history data.
Purpose and benefits: Calibrate simulation models
Topic area: Energy and Environment
Development stage: Pre-deployment
Impact assessment: Limited to a specific area of research
US federal AI use case: Data discovery, processing, and generation using machine learning for a range of CCS data and information
Agency: Department of Energy - NETL - National Energy Technology Laboratory (FECM)
Problem addressed: Data discovery, processing, and generation using machine learning for a range of carbon capture and storage data and information
Purpose and benefits: Data compression, clustering, mapping
Topic area: Energy and Environment
Development stage: Pre-deployment
Impact assessment: Limited to a specific area of research
US federal AI use case: Machine Learning for geophysical data inversion
Agency: Department of Energy - NETL - National Energy Technology Laboratory (FECM)
Problem addressed: Leak detection.
Purpose and benefits: Faster/better leak detection.
Topic area: Energy and Environment
Development stage: Deployed
Impact assessment: R&D use case that is NOT being used to control or significantly influence a decision or outcome about individuals and does not have an approved agreement for transition into agency operations.
First used: 2025-09-26
US federal AI use case: To help automate data discovery and preparations to support a range of CS models, tools, and products
Agency: Department of Energy - NETL - National Energy Technology Laboratory (FECM)
Problem addressed: To help automate data discovery and preparations to support a range of CS models, tools, and products
Purpose and benefits: Automate data dicovery
Topic area: Science
Development stage: Pre-deployment
Impact assessment: Limited to a specific area of research
US federal AI use case: ORNL: Foundational AI Research
Agency: Department of Energy - ORNL - Oak Ridge National Laboratory (SC43 OIM)
Problem addressed: accelerate scientific discovery
Purpose and benefits: accelerate scientific discovery
Topic area: Science
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: ORNL: AI for Materials Science
Agency: Department of Energy - ORNL - Oak Ridge National Laboratory (SC43 OIM)
Problem addressed: accelerate scientific discovery
Purpose and benefits: accelerate scientific discovery
Topic area: Science
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: ORNL: AI for Experimental Facilities Operations
Agency: Department of Energy - ORNL - Oak Ridge National Laboratory (SC43 OIM)
Problem addressed: accelerate scientific discovery
Purpose and benefits: accelerate scientific discovery
Topic area: Science
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: ORNL: AI for Transportation and Mobility
Agency: Department of Energy - ORNL - Oak Ridge National Laboratory (SC43 OIM)
Problem addressed: accelerate scientific discovery
Purpose and benefits: accelerate scientific discovery
Topic area: Science
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: ORNL: AI for Energy Generation and Distribution
Agency: Department of Energy - ORNL - Oak Ridge National Laboratory (SC43 OIM)
Problem addressed: accelerate scientific discovery
Purpose and benefits: accelerate scientific discovery
Topic area: Science
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: ORNL: AI for Advanced Manufacturing
Agency: Department of Energy - ORNL - Oak Ridge National Laboratory (SC43 OIM)
Problem addressed: improve manufacturing
Purpose and benefits: improve manufacturing
Topic area: Science
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: ORNL: AI for Bio and Health Sciences
Agency: Department of Energy - ORNL - Oak Ridge National Laboratory (SC43 OIM)
Problem addressed: improve health
Purpose and benefits: improve health
Topic area: Science
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: ORNL: AI for the Smart Laboratory
Agency: Department of Energy - ORNL - Oak Ridge National Laboratory (SC43 OIM)
Problem addressed: accelerate scientific discovery
Purpose and benefits: accelerate scientific discovery
Topic area: Science
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: ORNL: AI for Neutron Science
Agency: Department of Energy - ORNL - Oak Ridge National Laboratory (SC43 OIM)
Problem addressed: accelerate scientific discovery
Purpose and benefits: accelerate scientific discovery
Topic area: Science
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: ORNL: AI for Earth Systems
Agency: Department of Energy - ORNL - Oak Ridge National Laboratory (SC43 OIM)
Problem addressed: accelerate scientific discovery
Purpose and benefits: accelerate scientific discovery
Topic area: Energy and Environment
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: ORNL: AI for Fusion Energy
Agency: Department of Energy - ORNL - Oak Ridge National Laboratory (SC43 OIM)
Problem addressed: accelerate scientific discovery
Purpose and benefits: accelerate scientific discovery
Topic area: Science
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Network Security and Analysis
Agency: Department of Energy - IM-60 - IM Enterprise Operations and Shared Services (IM)
Problem addressed: behavior of attack, triage
Purpose and benefits: Vectra AI is a Structured and Unstructured machine learning (ML) and  Security -Led Artifical Intelligence (AI) tool used to detect patterns, anomalous or previously unseen activities inside petabytes of network and log data within the DOE HQ EITS networking boundary and cloud environments.
Topic area: Cybersecurity
Development stage: Deployed
Impact assessment: It does not meet the requirements to be high impact
First used: 2019-12-05
US federal AI use case: Advancing Market-Ready Building Energy Management by Cost-Effective Differentiable Predictive Control
Agency: Department of Energy - PNNL - Pacific Northwest National Laboratory (SC43 OIM)
Problem addressed: Enhance building energy management with predictive control, safety verification, and optimization.
Purpose and benefits: Lowers building energy costs while ensuring safe, resilient operations.
Topic area: Energy and Environment
Development stage: Deployed
Impact assessment: Does not meet any requiremnts for high Impact use case
First used: 2023-10-01
US federal AI use case: Adaptive Cyber-Physical Resilience for Building Control Systems
Agency: Department of Energy - PNNL - Pacific Northwest National Laboratory (SC43 OIM)
Problem addressed: How to maintain efficient, reliable, and secure operation of building control systems in the face of disruptions, changing conditions, or cyber-physical threats.
Purpose and benefits: Improves drug safety and reduces adverse health impacts in vulnerable populations.
Topic area: Energy and Environment
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: Elucidating Genetic and Environmental Risk Factors for Antipsychotic-induced Metabolic Adverse Effects Using AI
Agency: Department of Energy - PNNL - Pacific Northwest National Laboratory (SC43 OIM)
Problem addressed: Identifying individuals at higher risk for adverse metabolic effects from antipsychotic medications through predictive modeling of genetic and environmental data.
Purpose and benefits: Improves drug safety and reduces adverse health impacts in vulnerable populations.
Topic area: Health and Medical
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: APT Analytics
Agency: Department of Energy - PNNL - Pacific Northwest National Laboratory (SC43 OIM)
Problem addressed: Automate analysis of atom probe tomography (APT) data for faster scientific insights.
Purpose and benefits: Speeds up materials research through automated nanoscale data analysis.
Topic area: Science
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: AI used for predictive modeling and real time control of traffic systems
Agency: Department of Energy - PNNL - Pacific Northwest National Laboratory (SC43 OIM)
Problem addressed: Produce high-quality, contextually relevant, and coherent responses or content based on user input.
Purpose and benefits: Reduces traffic congestion, energy use, and greenhouse gas emissions.
Topic area: Transportation
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: Laboratory Automation
Agency: Department of Energy - PNNL - Pacific Northwest National Laboratory (SC43 OIM)
Problem addressed: Automate SEM/TEM data acquisition by identifying regions of interest with machine learning.
Purpose and benefits: Increases efficiency and throughput of scientific imaging and analysis.
Topic area: Science
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: Scalable, Efficient and Accelerated Causal Reasoning Operators, Graphs and Spikes for Earth and Embedded Systems (SEA-CROGS)
Agency: Department of Energy - PNNL - Pacific Northwest National Laboratory (SC43 OIM)
Problem addressed: Improving Information Access, Understanding, and Productivity through Language Automation
Purpose and benefits: Accelerates scientific discovery and next-gen computing for earth and embedded systems.
Topic area: Science
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: Physics-Informed Learning Machines for Multiscale and Multiphysics Problems (PhILMs)
Agency: Department of Energy - PNNL - Pacific Northwest National Laboratory (SC43 OIM)
Problem addressed: Produce high-quality, contextually relevant, and coherent responses or content based on user input.
Purpose and benefits: Promotes sustainable, economically viable waste-to-energy transitions.
Topic area: Science
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: Managing curb allocation in cities
Agency: Department of Energy - PNNL - Pacific Northwest National Laboratory (SC43 OIM)
Problem addressed: Manage curb space dynamically in cities to address rising demand for curbside parking.
Purpose and benefits: Improves urban mobility and equitable access to curb space.
Topic area: Transportation
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: Regional waste feedstock conversion to biofuels
Agency: Department of Energy - PNNL - Pacific Northwest National Laboratory (SC43 OIM)
Problem addressed: Produce high-quality, contextually relevant, and coherent responses or content based on user input.
Purpose and benefits: Promotes sustainable, economically viable waste-to-energy transitions.
Topic area: Energy and Environment
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: Use of developed ML techniques to parse opensource text-based information.
Agency: Department of Energy - PNNL - Pacific Northwest National Laboratory (SC43 OIM)
Problem addressed: Parse open-source text to define disadvantaged communities for energy transition planning.
Purpose and benefits: Informs equitable energy transition policies for disadvantaged communities.
Topic area: IT
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: AI techniques for identification of suitable delivery parking spaces in an urban scenario
Agency: Department of Energy - PNNL - Pacific Northwest National Laboratory (SC43 OIM)
Problem addressed: Identify optimal urban delivery parking spaces to support EV freight adoption.
Purpose and benefits: Supports sustainable freight delivery and electric vehicle adoption.
Topic area: Science
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: Surrogate models for probabilistic Bayesian inference
Agency: Department of Energy - PNNL - Pacific Northwest National Laboratory (SC43 OIM)
Problem addressed: Estimate unknown model parameters using surrogate models for probabilistic Bayesian inference.
Purpose and benefits: Enables faster, more reliable insights from complex physical models.
Topic area: Science
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: AI for system design optimization (e.g., detector, accelerator)
Agency: Department of Energy - SLAC - SLAC National Accelerator Laboratory (SC43 OIM)
Development stage: Retired
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: FIMS Invoice BOT
Agency: Department of Energy - WAPA - Western Area Power Administration (PMA)
Purpose and benefits: Employee Reimbursements and Purchase Power processes
Development stage: Retired
Impact assessment: Retired – The use case was reported in the agency's prior year's inventory, but its development and/or use has since been discontinued.
US federal AI use case: PARSGPT
Agency: Department of Energy - PM HQ -  Office of Project Management (PM)
Problem addressed: Project Management internal investigations and audits
Purpose and benefits: The value-add is derived from providing an accessible way for PM Analysts to safely interact with LLM technology.
Topic area: Admin Functions
Development stage: Deployed
Impact assessment: AI is used for Project Management, internal investigations and audits.
First used: 2025-05-22
US federal AI use case: AI Incubator Sandbox
Agency: Department of Energy - PNNL - Pacific Northwest National Laboratory (SC43 OIM)
Problem addressed: Provide a secure, multimodal AI chatbot sandbox for experimentation without internet access.
Purpose and benefits: Produce high-quality, contextually relevant, and coherent responses or content based on user input.
Topic area: Science
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: ServiceNow Predictive Intelligence
Agency: Department of Energy - LANL - Los Alamos National Lab (LAFO)
Problem addressed: Improve helpdesk efficiency and data quality
Purpose and benefits: Provide better and more consistent classification of ticket data entered into ServiceNow
Topic area: IT
Development stage: Deployed
Impact assessment: General purpose business system
First used: 2024-01-01
US federal AI use case: AI-Enhanced Lab Assist
Agency: Department of Energy - PNNL - Pacific Northwest National Laboratory (SC43 OIM)
Problem addressed: Detect trends in lab planning/control data to improve efficiency and knowledge sharing.
Purpose and benefits: Integrating lessons learned into Lab Assist Activity Planning to enhance operational efficiency, improve information sharing leveraging best practices, and foster a culture of continuous improvement.
Topic area: Science
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: SWPA Generative AI
Agency: Department of Energy - SWPA - Southwestern Power Administration (PMA)
Development stage: Retired
Impact assessment: This was a testing instance and does not meet the defition of High Impact. This AI instance was not trained on any production data.
US federal AI use case: Microsoft 365 Copilot (Productivity Suite)
Agency: Department of Energy - PNNL - Pacific Northwest National Laboratory (SC43 OIM)
Problem addressed: Automate and streamline productivity tasks in Microsoft 365 apps for staff efficiency.
Purpose and benefits: This helps PNNL streamline workflows, improve efficiency, and allow researchers to focus more on innovation and less on administrative tasks, ultimately accelerating scientific research and operational effectiveness.
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: NLCOO AI for Lessons Learned tool
Agency: Department of Energy - LANL - Los Alamos National Lab (LAFO)
Problem addressed: Provide best Lessons Learned based on the Problem a user is trying to address.
Purpose and benefits: Better search to gain insights from exisitng lessons learned to improve how we do work.
Topic area: Other
Development stage: Deployed
Impact assessment: General purpose business system
First used: 2025-01-01
US federal AI use case: Spot for automated sensing, inspection, and capture
Agency: Department of Energy - PNNL - Pacific Northwest National Laboratory (SC43 OIM)
Problem addressed: Conduct automated sensing, inspection, and data capture in challenging environments with robots.
Purpose and benefits: Spot, a mobile robot, can navigate hazardous or hard-to-reach areas to perform inspections and gather precise data with its advanced sensors and cameras.
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: Microsoft Power Platform capability that provides AI to automate processes in Power Apps and Power Automate
Agency: Department of Energy - PNNL - Pacific Northwest National Laboratory (SC43 OIM)
Problem addressed: Automate workflows and processes within Microsoft Power Apps and Power Automate.
Purpose and benefits: By leveraging AI for automation, PNNL can automate routine tasks such as data entry, reporting, and workflow management, freeing up researchers and staff to focus on higher-value activities.
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: CAISY
Agency: Department of Energy - HC HQ -  Office of the Chief Human Capital Officer (HC)
Problem addressed: The feature's main objective is to mimic real-life situations in the workplace using predefined scenarios
Purpose and benefits: 1. CAISY provides interactive, scenario-based content powered by AI where a learner can practice new skills in a safe space. This AI simulation content allows learners to choose a role, practice specific skills by responding to AI prompts, and receive adaptive, personalized feedback to guide their development
2. The user  is introduced by an avatar that is generated with AI text-to-video. After the introduction, the learner can either interact by typing or using speech-to-text (STT) and text-to-speech (TTS) services for more immersive and natural interaction.
When the conversation is over, the learner will receive a rating and evaluation
Topic area: Admin Functions
Development stage: Deployed
Impact assessment: CAISY is not designated HIGH IMPACT in reards to definitions indicated in OMB MEMO M-25-21
First used: 2024-08-21
US federal AI use case: ServiceNow Virtual Agent
Agency: Department of Energy - LANL - Los Alamos National Lab (LAFO)
Problem addressed: Provide chatbot services to help customers resolve issues or open service requests that do not require human intervention
Purpose and benefits: Improved automation
Topic area: IT
Development stage: Deployed
Impact assessment: ServiceNow's AI output is NOT a principal driver of a government decision that would meaningfully affects people's rights, safety, critical access, or strategic assets. AI in ServiceNow is strictly used to help manage IT resources for LANL.
First used: 2024-11-01
US federal AI use case: Databricks AI for Cloud Data Warehouse
Agency: Department of Energy - PNNL - Pacific Northwest National Laboratory (SC43 OIM)
Problem addressed: Streamline AI/ML solution building and governance in a unified cloud data warehouse.
Purpose and benefits: Efficiency in analytics and deployment of AL/ML models
Topic area: IT
Development stage: Deployed
Impact assessment: Does not meet any requiremnts for high Impact use case
First used: 2025-02-01
US federal AI use case: DOE Technical Standards
Agency: Department of Energy - EHSS HQ - Office of Environment Health Safety and Security (EHSS)
Problem addressed: Aid employees in improving the quality and technical accuracy of their work products.
Purpose and benefits: Enhance quality and accuracy of technical standards, supporting DOE's commitment to safety excellence.
Topic area: Admin Functions
Development stage: Deployed
Impact assessment: The use of AI in this office does not serve as the principal basis for decisions or actions that have legal, material, binding, or significant effect on rights or safety. Its use is to enhance quality and technical accuracy
First used: 2025-10-02
US federal AI use case: Microsoft Copilot for Security
Agency: Department of Energy - PNNL - Pacific Northwest National Laboratory (SC43 OIM)
Problem addressed: Strengthen cybersecurity with AI-driven threat detection, response, and vulnerability management.
Purpose and benefits: Proactively identify, mitigate, and respond to threats. Copilot assists in real-time monitoring, threat detection, incident response automation, and vulnerability management.
Topic area: Cybersecurity
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: Text To Speech Audio Generation
Agency: Department of Energy - KCNSC - Kansas City National Security Campus (KCFO)
Problem addressed: Inefficiencies with generating audio for training materials that does not include CUI, UCNI or Class material. Allows for quick generation and updates to course and video audio
Purpose and benefits: Reduction of time to create and modify training courses to ensure qualification of employees
Topic area: HR
Development stage: Deployed
Impact assessment: Does not match any of the identifed categories in M-25-21. Is used to generate audio in courses that do not have a direct impact to safety/data security.
First used: 2022-09-16
US federal AI use case: Lex Natural Language Interface
Agency: Department of Energy - NREL - National Renewable Energy Laboratory (EE)
Problem addressed: Find insights in a database with a LLM summarizing the results
Purpose and benefits: Create an efficient and user-friendly system that enables users to query project data, such as funding, AUs (allocation units), project focus, and fiscal years, with natural language prompts.
Topic area: IT
Development stage: Deployed
Impact assessment: This AI use case is strictly used for general purpose generative AI functionality. It is internal only, and no data is shared outside of NREL.
First used: 2025-06-01
US federal AI use case: Copilot Studio
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
Impact assessment: Doesn't meet criteria.
First used: 2024-03-11
US federal AI use case: Scopus AI
Agency: Department of Energy - NE INL - NE Idaho National Laboratory (NE)
Problem addressed: Not available
Purpose and benefits: Assist researchers by reducing time to find applicable research while increasing quality and accuracy of identified hits.
Topic area: Other
Development stage: Deployed
Impact assessment: Used for general purpose generative AI within a COTS product.
US federal AI use case: EnerGPT
Agency: Department of Energy - IM-50 - Architecture Engineering Technology and Innovation (IM)
Problem addressed: Improves efficiency of DOE staff.
Purpose and benefits: EnerGPT aims to enhance user productivity and reduce time spent on redundant tasks .
Topic area: Admin Functions
Development stage: Deployed
Impact assessment: It does not meet the definition defined by OMB.
First used: 2024-09-02