GreatNorthCollective/greatnorth-us-federal-ai-inventory huggingface dataset:
US federal AI use case: CAP Automation
Agency: Tennessee Valley Authority - Enterprise Analytics & Innovation
Purpose and benefits: Use NLP to classify condition reports as C, E, or WO level
Topic area: Energy and Environment
US federal AI use case: CR intelligent search
Agency: Tennessee Valley Authority - Enterprise Analytics & Innovation
Purpose and benefits: Use NLP to search through CRs. Also tool to include pattern recognition and adding additional safety data to search for and do topic modeling on
Topic area: Energy and Environment
US federal AI use case: Heliviewer
Agency: Tennessee Valley Authority - Enterprise Analytics & Innovation
Purpose and benefits: Use of helicopter image data for survey and project insights
Topic area: Energy and Environment
US federal AI use case: ICI camera
Agency: Tennessee Valley Authority - Enterprise Analytics & Innovation
Purpose and benefits: Use computer vision to detect rate of change of water temperature with thermal image data which is indicative of dam leakage
Topic area: Energy and Environment
US federal AI use case: Load Forecasting
Agency: Tennessee Valley Authority - Enterprise Planning
Purpose and benefits: Improved efficiency and productivity
Topic area: Energy and Environment
US federal AI use case: Talkwalker
Agency: Tennessee Valley Authority - External Communications
Purpose and benefits: Improved visibility of brand reputation
Topic area: Admin Functions
US federal AI use case: ArcGIS
Agency: Tennessee Valley Authority - GIS
Purpose and benefits: Improved efficiency and productivity, access to information and insights
Topic area: Energy and Environment
US federal AI use case: SEEQ AI
Agency: Tennessee Valley Authority - Generation
Purpose and benefits: It serves multiple functional roles to enhance productivity, accelerate insights, and bridge knowledge gaps for users working with time series data.
Topic area: Energy and Environment
US federal AI use case: Generation Project Funding Estimates
Agency: Tennessee Valley Authority - Generation
Purpose and benefits: Increased efficiency and productivity, reduced errors
Topic area: Energy and Environment
US federal AI use case: GET Enhancement
Agency: Tennessee Valley Authority - Generation Projects & Fleet Services
Purpose and benefits: The requested updates will augment the GET application by adding the ability to subset and display SSL Confidence Band plots within the user interface, alongside other planned bug fixes and performance enhancements.
Topic area: Energy and Environment
US federal AI use case: GMET Enhancement
Agency: Tennessee Valley Authority - Generation Projects & Fleet Services
Purpose and benefits: This update allows TVA staff to filter, visualize, and export model results on demand, reducing reliance on static reports and improving operational efficiency.
Topic area: Energy and Environment
US federal AI use case: GMET Multivariate analysis
Agency: Tennessee Valley Authority - Generation Projects & Fleet Services
Purpose and benefits: Increased efficiency and productivity, faster searching and access to information
Topic area: Energy and Environment
US federal AI use case: GET
Agency: Tennessee Valley Authority - Generation Projects & Fleet Strategy
Purpose and benefits: Groundwater evaluation Tool - The GET Tool is designed to provide statistical analysis of groundwater monitoring data required under State regulatory programs and the federal Coal Combustion Residuals (CCR) rule. It uses state-of-the-art statistical and predictive methods to evaluate geochemical and geotechnical data under three phases of groundwater monitoring: Detection, Assessment, and Corrective Action. In “Detection”, background data is used to construct prediction limits for use in identifying statistically significant changes from background levels. In “Assessment” and “Corrective Action”, compliance data is used to compute confidence intervals and confidence bands to assess violations of groundwater protection standards (GWPS) to inform of corrective action needs.
Topic area: Energy and Environment
US federal AI use case: GMET
Agency: Tennessee Valley Authority - Generation Projects & Fleet Strategy
Purpose and benefits: The Groundwater Modeling Evaluation Tool (GMET) is an R Shiny application that uses Phreeqc geochemical models and analysis to evaluate groundwater chemistry data at each of TVA’s CCR sites
Topic area: Energy and Environment
US federal AI use case: AI-Enhanced Search
Agency: Tennessee Valley Authority - IT Operations
Purpose and benefits: Portal users can find answers more quickly and easily with features like auto-complete search queries, natural language support, and typo handling.
Topic area: IT
US federal AI use case: Copilot
Agency: Tennessee Valley Authority - Information Technology
Purpose and benefits: Increased efficiency and productivity
Topic area: Admin Functions
US federal AI use case: Github Copilot
Agency: Tennessee Valley Authority - Information Technology
Purpose and benefits: Increased efficiency and productivity
Topic area: IT
US federal AI use case: Data Services Business Context Definition
Agency: Tennessee Valley Authority - Information Technology
Purpose and benefits: Increased efficiency and productivity
Topic area: IT
US federal AI use case: Cisco ML
Agency: Tennessee Valley Authority - Information Technology
Purpose and benefits: Insights, Increased efficiency, increased productivity
Topic area: Cybersecurity
US federal AI use case: Datum
Agency: Tennessee Valley Authority - Information Technology
Purpose and benefits: Datum is a virtual knowledge employee for Teams. The system can search data and provide analysis, it can be taught any additional knowledge within the group’s data or the group’s objective s and can generate reports and output along with analysis on the output. The system can also create new work the same way an Analyst can using the internal data to transform it to desired output. For example, the system can get your unit data and run a unit commitment on it and then analyze the output. You can refine it by giving it input in English. The final product can be saved so other users can use the same instructions (it can take inputs though of dates/units, etc. that you specify so users can run it with different input each time). It will simulate having your own internal Analyst and IT resource in one.
Topic area: IT
US federal AI use case: AWS Q
Agency: Tennessee Valley Authority - Information Technology
Purpose and benefits: Use of AWS Q will help IT be more efficient and increase productivity
Topic area: IT
US federal AI use case: ChatSPP
Agency: Tennessee Valley Authority - Information Technology
Purpose and benefits: Increased efficiency and productivity, faster searching and access to information
Topic area: Admin Functions
US federal AI use case: COBIT and ATAD Prediction
Agency: Tennessee Valley Authority - Information Technology
Purpose and benefits: Increased efficiency and productivity
Topic area: IT
US federal AI use case: Land Management Records
Agency: Tennessee Valley Authority - Information Technology
Purpose and benefits: AI system to efficiently help find information for public inquiries related to land managment, dock permits, and annual reviews.
Topic area: Energy and Environment
US federal AI use case: Environmental Documentation
Agency: Tennessee Valley Authority - Information Technology
Purpose and benefits: Increased efficiency and productivity
Topic area: Energy and Environment
US federal AI use case: Bill of Material
Agency: Tennessee Valley Authority - Information Technology
Purpose and benefits: Increased efficiency and productivity, faster searching and access to information
Topic area: Energy and Environment
US federal AI use case: TVA Today AI
Agency: Tennessee Valley Authority - Information Technology
Purpose and benefits: Increased efficiency, productivity, and access to information
Topic area: Energy and Environment
US federal AI use case: Non-NPG CAP
Agency: Tennessee Valley Authority - Information Technology
Purpose and benefits: Increased efficiency and productivity
Topic area: Energy and Environment
US federal AI use case: AWS Transcribe
Agency: Tennessee Valley Authority - Information Technology
Purpose and benefits: Extract key business insights from customer calls, video files, clinical conversations, and more. -Improve business outcomes with state of the art speech recognition models that are fully managed and continuously trained. -Enhance accuracy with custom models that understand your domain specific vocabulary. -Ensure customer privacy and safety by masking sensitive information.
Topic area: HR
US federal AI use case: Amazon Connect
Agency: Tennessee Valley Authority - Information Technology
Purpose and benefits: Improved customer support for helpdesk
Topic area: IT
US federal AI use case: Enscape
Agency: Tennessee Valley Authority - Information Technology
Purpose and benefits: Enhanced visuals for economic development efforts
Topic area: IT
US federal AI use case: Thinklabs
Agency: Tennessee Valley Authority - Innovation & Research
Purpose and benefits: Run TVA PSSE models, train a graph neural net on those results, utilize reinforcement learning on top of the GNN to optimally answer user questions such as "Where are the top 5 optimal places for a new battery?" or "what is the optimal transmission investment set to accomodate these 5 new generators and 15 new loads?"
Topic area: Energy and Environment
US federal AI use case: Specification Intelligence
Agency: Tennessee Valley Authority - Innovation & Research
Purpose and benefits: Phase1: it would simply include a chat window for users to ask questions of our specs. Phase 2: it would break our specs into concepts and create a matrix, allowing users to help harmonize our specs. This is part of a larger effort within TVA Projects around standardization
Topic area: Energy and Environment
US federal AI use case: Prism Models for MDM
Agency: Tennessee Valley Authority - Monitoring Diagnostics Management
Purpose and benefits: Anomaly detection
Topic area: Energy and Environment
US federal AI use case: Advanced Network Anomaly Detection
Agency: Tennessee Valley Authority - Network
Purpose and benefits: These tools use a massive amount of data and provide intelligence beyond what could be seen from a single vector. Correlated network traffic data with proxy communications help identify compromised systems and networks.
Topic area: IT
US federal AI use case: Perimeter Defense
Agency: Tennessee Valley Authority - Network
Purpose and benefits: Using a combination of ruleset definitions specifically designed to detect malicious activity and augmented by a proprietary machine learning algorithm, this tool protects web applications regardless of location. Models trained based on millions of sampled network traffic enables this tool to proactively detect and prevent malicious network activity from reaching and affecting web applications.
Topic area: IT
US federal AI use case: CAP Enhancement
Agency: Tennessee Valley Authority - Nuclear
Purpose and benefits: Increased efficiency and productivity
Topic area: Energy and Environment
US federal AI use case: Azure Nuclear Permitting Solution
Agency: Tennessee Valley Authority - Nuclear
Purpose and benefits: Increased efficiency and productivity, faster searching and access to information, improved compliance
Topic area: Energy and Environment
US federal AI use case: Westlaw
Agency: Tennessee Valley Authority - Office of General Counsel
Purpose and benefits: Reduces the time necessary to perform legal research and provides a tool to check for accuracy in legal writing.
Topic area: Other
US federal AI use case: Vegetation Management
Agency: Tennessee Valley Authority - Right of Way
Purpose and benefits: Monitoring of vegetation around transmission line and tower and predictive analytics on when/where to trim.
Topic area: Energy and Environment
US federal AI use case: Azure FEWS CUA
Agency: Tennessee Valley Authority - River Management
Purpose and benefits: Increased efficiency and productivity, faster access to information
Topic area: Energy and Environment
US federal AI use case: River Forecast
Agency: Tennessee Valley Authority - Riverfleet Management Services
Purpose and benefits: A multi-scale graph neural network-based autoregressive model. It is trained on historical weather data from ECMWF's ERA5 reanalysis archive. The tool generates predictions at 6-hour time steps for a set of surface and atmospheric variables.
Topic area: Energy and Environment
US federal AI use case: Transmission analytics
Agency: Tennessee Valley Authority - Safety & Shared Services
Topic area: Energy and Environment
US federal AI use case: Materials Intelligent Catalog Assistant
Agency: Tennessee Valley Authority - Supply Chain
Purpose and benefits: Faster insights, access to information, and reduction of duplicates
Topic area: Energy and Environment
US federal AI use case: Materials tracking
Agency: Tennessee Valley Authority - Supply Chain
Purpose and benefits: Use predictive analytics and confidence levels to track materials as they go through the supply chain process and risk on being delivered on time
Topic area: Energy and Environment
US federal AI use case: Network Anomaly Detection
Agency: Tennessee Valley Authority - Transmission
Purpose and benefits: Real-time visibility into network communications, assets, connections, and protocols.
Topic area: Energy and Environment
US federal AI use case: Trade Chat
Agency: Tennessee Valley Authority - Transmission
Purpose and benefits: Improved code of conduct chat tool functions
Topic area: Energy and Environment
US federal AI use case: ESRI GIS AI
Agency: Tennessee Valley Authority - Transmission System Support
Purpose and benefits: Increased efficiency and productivity
Topic area: Energy and Environment
US federal AI use case: Natural Reader
Agency: Tennessee Valley Authority - Workforce Development
Purpose and benefits: Text-to-speech desktop software for individual use. This easy-to-use software with natural-sounding voices can read any text such as Microsoft Word files, webpages, PDF files, and E-mails.
Topic area: Admin Functions
US federal AI use case: OCC.Chat
Agency: Department of the Treasury - Office of the Comptroller of the Currency (OCC)
Problem addressed: GenAI chatbot that generates human-like responses to user questions using public knowledge for reference
Purpose and benefits: The AI improves operational efficiency by quickly delivering relevant information, which reduces the manual burden on staff and enhances overall productivity. For the general public, it enhances service delivery by providing instant and consistent responses to their queries, thereby improving user satisfaction and engagement.
Topic area: IT
Development stage: Deployed
Impact assessment: Generic AI tool set that will serve basic needs but not specific needs to support critical agency function, however this might be foundation for other use cases.
First used: 2024-07-01
US federal AI use case: Adobe Photoshop
Agency: National Science Foundation - Office for Legislative and Public Affairs (OLPA)
Problem addressed: Office for Legislative and Public Affairs (OLPA) Creative Services team will use Photoshop's AI-powered tools to refine edits of photos and graphics, particularly the retouching of portraits.
Development stage: Pre-deployment
First used: 2023-06-01
US federal AI use case: Newsletter Content Support
Agency: Department of the Treasury - Office of the Comptroller of the Currency (OCC)
Problem addressed: Creating newsletter content requires staff to synthesize updates, draft clear narratives, and format information for broad audiences. This process can be time-consuming, especially when staff must balance writing tasks with other operational responsibilities. The AI is intended to ease this burden by producing initial draft content that captures key messages and themes, allowing staff to focus on refinement rather than starting from scratch.
Purpose and benefits: The AI increases efficiency by accelerating the creation of consistent, well-structured newsletter drafts, helping teams communicate more regularly and effectively. This supports the agency’s mission by improving internal and external information sharing, reducing administrative workload, and ensuring timely dissemination of updates. For the public or broader Treasury stakeholders, clearer and more consistent communication enhances transparency and understanding of agency activities.
Topic area: IT
Development stage: Pre-deployment
Impact assessment: This draft-newsletter use case simply prepares informational content and plays no role in decisions that could affect rights, benefits.
US federal AI use case: Meeting Minute Summarization
Agency: Department of the Treasury - Office of the Comptroller of the Currency (OCC)
Problem addressed: Ability to synthesize information based on extensive discussions, action items, and decisions that must be captured accurately in meeting minutes. Manual compilation of these minutes is time-consuming, varies in quality, and can distract staff from active participation. The AI is intended to streamline this process by producing clear, organized summaries of meeting discussions, reducing the burden on staff and improving consistency in how meeting outcomes are documented.
Purpose and benefits: The AI enhances efficiency by providing timely, reliable summaries of meeting minutes, helping staff quickly understand key decisions, responsibilities, and next steps. This supports the agency’s mission by improving coordination, ensuring accurate communication of supervisory-relevant information, and enabling more timely follow-through on issues. Indirectly, the public benefits from stronger oversight and more effective execution of supervisory responsibilities.
Topic area: IT
Development stage: Pre-deployment
Impact assessment: This use case produces summaries for informational purposes and does not generate decisions that affect rights, access to services, safety, or any other outcomes defined in the high-impact criteria.
US federal AI use case: Visualization Alt-Text Generation
Agency: Department of the Treasury - Office of the Comptroller of the Currency (OCC)
Problem addressed: Charts, figures, and tables often lack descriptive alt-text, which is essential for accessibility and compliance with federal standards. Creating accurate alt-text manually is time-consuming and requires staff to interpret visual information and translate it into clear, concise narrative descriptions. The AI is intended to automate this process by analyzing visual elements and generating draft alt-text, reducing manual workload and improving consistency in accessibility documentation.
Purpose and benefits: The AI increases efficiency and ensures more consistent compliance with accessibility requirements, supporting the agency’s mission to provide inclusive and usable information to all stakeholders. Staff benefit from reduced time spent drafting alt-text, enabling them to focus on higher-value analytical and communication tasks. The general public—particularly individuals relying on assistive technologies—benefits from clearer, more accessible descriptions of charts and data visualizations.
Topic area: IT
Development stage: Pre-deployment
Impact assessment: The chart- and figure-summarization tool only provides descriptive summaries of visual data for user convenience and does not generate outputs that drive legal, regulatory, or service-impacting decisions. Because humans fully interpret and apply the information, and the tool’s output does not affect rights, benefits, or access to government services, it does not qualify as a High-Impact AI use case.
US federal AI use case: Handbook Highlights
Agency: Department of the Treasury - Office of the Comptroller of the Currency (OCC)
Problem addressed: The Comptroller’s Handbook contains extensive, detailed guidance that examiners must review and interpret to support supervisory activities. Manually navigating and summarizing this material is time-consuming and can delay exam preparation or issue analysis. The AI is intended to streamline this process by quickly summarizing relevant sections of the handbook, enabling staff to more efficiently access key concepts, expectations, and procedural guidance.
Purpose and benefits: The AI improves examiner efficiency by reducing time spent reading and synthesizing lengthy handbook materials, allowing staff to focus on deeper analysis and supervisory judgment. This supports the agency’s mission by promoting more consistent application of asset quality standards and strengthening the timeliness and effectiveness of examinations. The public benefits indirectly through stronger, more consistent oversight of asset quality risks and improved safety and soundness of financial institutions.
Topic area: IT
Development stage: Pre-deployment
Impact assessment: This use case only provides reference or clarification support and does not produce decisions that affect rights, access to services, safety.
US federal AI use case: Training Content Generation
Agency: Department of the Treasury - Office of the Comptroller of the Currency (OCC)
Problem addressed: Developing training materials for supervisory topics requires subject-matter expertise and significant staff time to research concepts, draft explanations, create examples, and format content for instructional use. This manual process can slow down the production of new or updated training modules. The AI is intended to automate portions of content creation by generating draft educational materials, helping training teams produce high-quality instructional content more efficiently.
Purpose and benefits: The AI improves the speed and consistency of training content development, enabling staff to more quickly access updated and comprehensive learning materials. This strengthens the agency’s mission by enhancing examiner competency, improving knowledge transfer, and supporting more effective supervision. Ultimately, the public benefits from better-trained examiners who can more effectively identify and address risks within financial institutions.
Topic area: IT
Development stage: Pre-deployment
Impact assessment: This use case supports training and learning activities and does not make decisions that affect rights, access to services, or other outcomes listed in the high-impact criteria.
US federal AI use case: Reporting Requirement Analysis
Agency: Department of the Treasury - Office of the Comptroller of the Currency (OCC)
Problem addressed: Reviewing lengthy, technical, and highly variable reports manually to ensure completeness, accuracy, and adherence to regulatory requirements is time-consuming and resource intensive. The AI is intended to streamline this process by analyzing the content for required elements, identifying gaps, and highlighting areas that may not meet reporting standards.
Purpose and benefits: The AI enhances efficiency and consistency, enabling staff to focus on higher-value evaluation and supervisory judgment. This supports the agency’s mission by improving the timeliness and quality of oversight related to information security and consumer data protection. The public benefits from stronger, more responsive supervision that promotes better safeguarding of sensitive customer information within financial institutions.
Topic area: IT
Development stage: Pre-deployment
Impact assessment: AI assists with reviewing and interpreting security reports but does not generate binding decisions or actions that impact individuals’ rights, benefits, or access to critical services.
US federal AI use case: Resubmit Checker
Agency: National Science Foundation - Directorate for STEM Education (EDU)
Problem addressed: The resubmit checker takes a list of proposal IDs and returns a list of similar proposals submitted to NSF in the past, scored by their similarity. This is useful for identifying resubmitted proposals for several purposes: evaluating whether to return without review for lack of revision, ensuring continuity of merit review, and the analysis of broader resubmission trends.
Development stage: Pre-deployment
First used: 2024-06-01
US federal AI use case: OCC.InfoAssist
Agency: Department of the Treasury - Office of the Comptroller of the Currency (OCC)
Problem addressed: GenAI chatbot that generates human-like responses to user questions using OCC Comptroller handbooks and PPMs documents
Purpose and benefits: The AI improves operational efficiency by automating the response process, thereby reducing the manual workload on staff. It ensures that users receive consistent and accurate information quickly, which enhances user satisfaction and supports the agency’s mission of providing timely access to critical information. This leads to improved service delivery and better-informed decision-making across the agency.
Topic area: IT
Development stage: Pilot
Impact assessment: Generic AI tool set that will serve basic needs but not specific needs to support critical agency function, however this might be foundation for other use cases.
First used: 2024-07-01
US federal AI use case: Software Code Generation
Agency: Department of the Treasury - Office of the Comptroller of the Currency (OCC)
Problem addressed: Developing software code and producing the associated documentation requires significant time and technical expertise. Routine coding tasks, boilerplate creation, and documentation drafting can slow down development cycles and divert staff from higher-value design and analysis work. The AI is intended to assist by generating code snippets, templates, and initial documentation drafts, reducing manual effort and accelerating development processes.
Purpose and benefits: The AI increases development efficiency by automating repetitive coding tasks and improving documentation consistency. This enables technical staff to focus more on systems design, security review, and integration work, supporting the agency’s mission through faster delivery of high-quality technical solutions. The public benefits indirectly through enhanced operational efficiency, improved reliability of supporting systems, and reduced development backlogs that contribute to more effective regulatory and supervisory activities.
Topic area: IT
Development stage: Pilot
Impact assessment: The code generation tool assists developers by producing draft code snippets that are fully reviewed, tested, and validated by human engineers before use, ensuring it does not autonomously influence systems or services. Because its output does not make decisions affecting rights, benefits, access, or critical government functions, it does not meet the threshold for a High-Impact AI use case.
First used: 2025-07-01
US federal AI use case: Amazon Web Services(AWS) Assisted Software Development (DIS AI Assisted Development)
Agency: National Science Foundation - Office of Information and Resource Management (OIRM)
Problem addressed: Within software development, AI-driven tools, such as Amazon Web Services (AWS) CodeWhisperer, Amazon Q and Bedrock, and integration with development workflow, promise to elevate developer productivity and refine code quality. The objective of this pilot is to explore potential integration of these AWS services with the Division of Information Systems (DIS) Developers Integrated Development Environments (IDEs), Jenkins automation, Bitbucket, laying the groundwork for secure AI Assisted Development  at NSF.
Development stage: Pre-deployment
First used: 2024-06-01
US federal AI use case: OCC Writing Style Adherence
Agency: Department of the Treasury - Office of the Comptroller of the Currency (OCC)
Problem addressed: Examiners must ensure that written supervisory products consistently adhere to the OCC Writing Style Manual before submitting them to their EICs for review. Manually checking documents for clarity, tone, structure, grammar, and style compliance can be time-consuming and may lead to inconsistencies across teams. The AI is intended to provide a first-pass review that identifies deviations from writing guidelines and highlights areas needing refinement, reducing the burden on staff.
Purpose and benefits: The AI improves the quality and consistency of written supervisory communications by helping examiners align their drafts with OCC writing standards before formal review. This supports the agency’s mission by promoting clearer, more professional, and more effective supervisory messaging. The public benefits indirectly from improved clarity and coherence in supervisory documents, which strengthen the transparency and reliability of regulatory communications.
Topic area: IT
Development stage: Pre-deployment
Impact assessment: This use case only checks examiner writing against style guidelines and does not produce decisions that affect rights, access to services or safety.
US federal AI use case: Policy Development Editorial Assistant
Agency: Department of the Treasury - Office of the Comptroller of the Currency (OCC)
Problem addressed: Maintaining and updating the Policies and Procedures Manual (PPM) and Office- or Management-Level Policies and Procedures (OMPPs) requires staff to manually identify where changes are needed, ensure alignment across documents, and verify that no conflicts or duplications exist. This process is time-consuming and prone to oversight, leading to inconsistent guidance or outdated content. The AI is intended to streamline this workflow by detecting conflicting or duplicative information, identifying documents impacted by policy changes, and generating draft PPMs or updates to reduce manual errors and accelerate the policy development cycle.
Purpose and benefits: The AI improves policy accuracy, consistency, and timeliness by helping staff quickly identify needed updates and eliminating conflicting or duplicative language across PPMs and OMPPs. This strengthens the agency’s mission by enhancing internal governance, ensuring clearer policy guidance, and reducing administrative burden on staff. The public benefits indirectly from more reliable internal policy frameworks that support efficient and effective regulatory and supervisory operations.
Topic area: IT
Development stage: Pre-deployment
Impact assessment: This use case is used for drafting policies and procedures manuals (PPMs) and spotting inconsistencies, without producing decisions that affect rights, access to services or safety.
US federal AI use case: Mine Potential Reviewer's areas of expertise
Agency: National Science Foundation - Directorate for Technology, Innovation, and Partnership (TIP)
Problem addressed: Airtable is a low- code platform that incorporates OpenAI services  and the data is kept private to Airtable.  NSF TIP has been approved to use Airtable for several use cases, and Airtable has been certified as secure by the NSF OCIO security team.  TIP Team would like to get approval to use Airtable to trial Airtable's AI's ability to match potential reviewer expertise to the reviewer.
Development stage: Pre-deployment
First used: 2024-06-01
US federal AI use case: Regulatory Rule Analysis
Agency: Department of the Treasury - Office of the Comptroller of the Currency (OCC)
Problem addressed: Comment letters on major rulemakings can be lengthy and numerous, making it difficult for staff to quickly understand the range of viewpoints and the main arguments presented. The AI helps by reviewing these submissions and distilling them into clear summaries, saving time and reducing the burden of manually going through each document.
Purpose and benefits: By providing a faster way to understand feedback on the proposed rule, the AI supports more informed internal discussions and policy analysis. This helps ensure the agency remains aligned with evolving regulatory perspectives, ultimately contributing to stronger and more effective supervision practices that benefit the public and the financial system.
Topic area: Service Delivery
Development stage: Pre-deployment
Impact assessment: This use case focuses on summarizing or interpreting regulatory material.
US federal AI use case: Streamflow Duration Assessment Modeling
Agency: Environmental Protection Agency - OW
Problem addressed: Improved streamflow classification
Purpose and benefits: Because streamflow duration classes is unknown for most streams across the nation, the classifications from Streamflow Duration Assessment Methods (SDAMs) can inform ecological assessments and resource management decisions, such as setting restoration goals or applying appropriate water quality standards. SDAMs also support identifying waters that may be subject to regulatory jurisdiction under the Clean Water Act or other authorities.
Topic area: Science
Development stage: Deployed
Impact assessment: The output of this AI use case does not serve as a principal basis for decisions or actions that have a legal, material, binding, or significant effect on rights or safety.
First used: 2011-11-15
US federal AI use case: Use AI to populate reviewer "areas of expertise" and state of potential Regional Engines submitters (members of organizations)
Agency: National Science Foundation - Directorate for Technology, Innovation, and Partnership (TIP)
Problem addressed: TIP is authorized to use Airtable for project management, including reviewer volunteers and recruitment.  Airtable is a no-code platform that includes a built-in database.  This system does    not store any PII in the database except for "public PII"  such as name, position, work email address, areas of professional expertise, etc.  We have two specific use-cases for which we would like to employ Airtable AI:
1.	People who volunteer sometimes do not list all areas of their expertise, or expertise becomes stale.  We have been able to do a proof of concept where Airtable AI is prompted to look at the potential reviewer's Linked In profile and identify or update the potential reviewer's expertise in its database based on recent updates to professional experience in LinkedIn.  We would like permission to have AI complete this work.  Typically, an admin person or Program Director   will do this work and it is time-consuming and burdensome.  AI can do it much faster and a member of the staff can check it rather than complete it for 400-500 reviewers.
2.	We also have a database of potential Engines   submitters in Airtable -- people who have attended a webinar, roadshow, or submitted at an earlier time and asked to be contacted when new funding opportunities are available.  We track very similar information in the potential submitters data base as we do for reviewers who volunteer to review for the program. The information is used to support outreach to these potential submitters when new funding opportunities are announced, or a new Engines  event is announced.  We need to know the state associated with the particular submitters institution to determine which regional Engine   they should be mapped to geographically (state in the U.S.).  We have found that we can prompt the AI to look at the potential submitter's institution, and the AI can locate the state 100% of the time to identify the region that the submitter would be associated with if they were accepted to the program.  Currently, a staff person does this work, and it is burdensome.  The AI can do this work much faster, so that a member of the staff can redirect their time to more value-added work and then go back and validate the AI's work.  This permits the NSF Regional Innovation Engines  program   to segment outreach by event and regional engine .
The Airtable AI is an Airtable private instance of OpenAI.
Development stage: Pre-deployment
First used: 2024-06-01
US federal AI use case: Public Information Analysis
Agency: Department of the Treasury - Office of the Comptroller of the Currency (OCC)
Problem addressed: Review of transcripts can be time-consuming, especially when trying to compare themes, identify shifts in tone, or spot notable changes. The AI helps streamline this work by quickly analyzing the transcripts and pulling together the main similarities, differences, and key insights that normally require extensive manual review.
Purpose and benefits: With faster access to clear, consolidated insights from transcripts examiners and analysts can more effectively monitor trends, emerging risks, management perspectives. This strengthens supervisory awareness and supports more timely oversight, which in turn contributes to a safer banking environment that benefits the broader public.
Topic area: Service Delivery
Development stage: Pre-deployment
Impact assessment: This use case summarizes or analyzes publicly available financial discussions and does not produce decisions that impact rights, access to services or safety.
US federal AI use case: Enhancing Technology, Innovation and Partnerships (TIP) Awards: Efficient Tagging for the 10 Key Technology Areas (KTAs)
Agency: National Science Foundation - Directorate for Technology, Innovation, and Partnership (TIP)
Problem addressed: Per the "CHIPS and Science Act" mandate, TIP needs to know the investment portfolio based on the 10 KTAs.
Development stage: Pre-deployment
First used: 2024-06-01
US federal AI use case: Narrative Summary and Thematic Analysis
Agency: Department of the Treasury - Office of the Comptroller of the Currency (OCC)
Problem addressed: The AI helps cut down the time spent reading through lengthy reports. These documents can contain a lot of detail, and staff often need a quick understanding of the main points. The AI provides an easier way to get to the core issues without manually working through the full report.
Purpose and benefits: By giving teams faster access to the key concerns and trends, the AI supports more informed supervisory planning and internal coordination. This strengthens the agency’s ability to stay ahead of potential risks in the banking system, which ultimately contributes to better protection of consumers and the public.
Topic area: Admin Functions
Development stage: Pre-deployment
Impact assessment: This use case provides informational or administrative support.
US federal AI use case: AI Assistants in Esri Tools
Agency: Environmental Protection Agency - OFA
Problem addressed: This would help people use Esri software do more complex analysis in a shorter time and more easily.
Purpose and benefits: This would save staff time and allow for more complex data analysis and visualization that would assist with making better environmental decisions.
Topic area: Service Delivery
Development stage: Pilot
Impact assessment: The output of this AI use case does not serve as a principal basis for decisions or actions that have a legal, material, binding, or significant effect on rights or safety.
First used: 2025-09-01
US federal AI use case: Preparation of Brownfields Success Stories
Agency: Environmental Protection Agency - Region 1
Problem addressed: Preparing draft Brownfields success stories involves compiling and summarizing extensive data from technical reports about site history and environmental assessment/cleanup ads well as financial information about cleanup costs, grant funds, leveraged public/private investment, and jobs leveraged. this information comes from many different sources and can be much more quickly collected and compiled by using AI.
Purpose and benefits: By leveraging AI to do the heavy lifting of collecting and compiling the data, we can focus our efforts more on the narrative aspect of the success stories and shorten the overall amount of time it takes to prepare stories and publish them on our website, where they can provide inspiration and ideas to other communities who may be struggling with brownfield-related challenges of their own.
Topic area: Admin Functions
Development stage: Pilot
Impact assessment: The output of this AI use case does not serve as a principal basis for decisions or actions that have a legal, material, binding, or significant effect on rights or safety.
First used: 2025-08-15
US federal AI use case: Rulemaking Comment Analytics
Agency: Department of the Treasury - Office of the Comptroller of the Currency (OCC)
Problem addressed: The rulemaking process generates large volumes of public comments that require timely and consistent analysis. Manual review is labor-intensive, slow, and prone to variability, creating delays in identifying sentiment, themes, and stakeholder concerns. We need a more efficient, scalable method to analyze these comments so regulators can make informed decisions within required timeframes.
Purpose and benefits: The Comment Analytics use case leverages Gen AI to rapidly analyze public comments submitted during rulemaking, including identifying sentiment, key themes, and areas of concern. This significantly speeds up the review process, reduces manual workload, and provides consistent, data-driven insights to support more informed regulatory decision-making.
Topic area: Service Delivery
Development stage: Pre-deployment
Impact assessment: The AI-driven comment analytics tool does not make or directly influence binding policy or regulatory decisions; it only synthesizes and summarizes public input for human review. Because its outputs do not determine individuals’ rights, benefits, services, or access to government resources, it does not meet the definition of a High-Impact AI use case.
US federal AI use case: Requirements Elaboration Tool
Agency: Department of the Treasury - Office of the Comptroller of the Currency (OCC)
Problem addressed: Teams often start with high-level business needs that require additional clarification before work can move forward. The AI helps break down these broad statements into more detailed and precise requirements, reducing back-and-forth discussions and helping ensure everyone shares the same understanding of what needs to be delivered.
Purpose and benefits: More clearly defined requirements lead to smoother project execution and fewer misunderstandings, which supports timely delivery of technology and process improvements. These improvements strengthen internal operations and ultimately help the agency carry out its supervisory mission more effectively, yielding better outcomes for the public and the financial system.
Topic area: IT
Development stage: Pre-deployment
Impact assessment: This tool assists in the refinement of requirements and further detailing business necessities.
US federal AI use case: AI Use Case Review and Evaluation Workflow
Agency: Department of the Treasury - Office of the Comptroller of the Currency (OCC)
Problem addressed: Enable a structured assessment across five key dimensions—Bias, Ethics, Business Value, Risk, and Technical Excellence—to support informed value discussions for new AI services, including both Commercial off the Shelf (COTS) solutions and custom-developed capabilities
Purpose and benefits: This assessment framework provides a consistent, transparent method for evaluating AI solutions, ensuring that key considerations such as Bias, Ethics, Risk, and Technical Excellence are rigorously examined. It supports more informed decision-making, strengthens governance, and helps align AI investments with organizational value and compliance expectations.
Topic area: IT
Development stage: Pilot
Impact assessment: This tool provides a structured assessment across five key dimensions—Bias, Ethics, Business Value, Risk, and Technical Excellence—to support informed value discussions for new AI services
First used: 2026-01-15
US federal AI use case: Framework Analysis
Agency: Department of the Treasury - Office of the Comptroller of the Currency (OCC)
Problem addressed: Feedback on NPR's can be extensive and highly technical, making it challenging for staff to quickly absorb the main points raised by commenters. The AI helps by reviewing this feedback and organizing it into clear themes and insights, reducing the time needed to work through large volumes of material.
Purpose and benefits: By giving teams a faster understanding of the issues and concerns raised in comment letters, the AI supports more informed supervisory and policy discussions. This leads to better-quality analysis and decision-making related to capital rules, ultimately contributing to a stronger, more resilient banking system that benefits the public.
Topic area: Service Delivery
Development stage: Pre-deployment
Impact assessment: This use case summarizes and/or interprets regulatory content and does not generate decisions that affect rights, access to services or safety.
US federal AI use case: Survey Analysis
Agency: Department of the Treasury - Office of the Comptroller of the Currency (OCC)
Problem addressed: The AI is intended to address the difficulty of manually reviewing and interpreting large volumes of open-ended survey comments. Analysts often spend significant time reading through text responses to identify themes, concerns, or sentiment. The AI helps streamline this process by quickly mining, organizing, and highlighting meaningful insights from the survey data.
Purpose and benefits: By accelerating the analysis of survey feedback, the AI enables the agency to better understand employee or stakeholder perspectives and identify areas needing attention. Faster, more consistent insight extraction supports improved decision-making and enhances internal operations, which strengthens the agency’s overall effectiveness in carrying out its supervisory mission—ultimately benefiting the public through more informed regulatory oversight.
Topic area: Admin Functions
Development stage: Pre-deployment
Impact assessment: The Survey Analytics tool only aggregates and summarizes respondent feedback to support internal understanding and does not make decisions that affect individuals’ rights, benefits, or access to government services. Since all insights are interpreted and acted upon solely by humans, the tool does not qualify as a high-impact AI use case.
US federal AI use case: SF182 Form and Policy Assistant
Agency: Environmental Protection Agency - OFA
Problem addressed: This AI feature will solve the problem of the substantial confusion and miscommunication involved in submitting SF182 Training Requests.
Purpose and benefits: Significant reduction in FAQs, emails, messages, SF182 discrepancies, employee frustration, costs associated with improper SF182 routing and training cancellations.
Topic area: HR
Development stage: Pilot
Impact assessment: The output of this AI use case does not serve as a principal basis for decisions or actions that have a legal, material, binding, or significant effect on rights or safety.
First used: 2024-08-01
US federal AI use case: Research Suitability
Agency: Department of the Treasury - Office of the Comptroller of the Currency (OCC)
Problem addressed: The AI is intended to reduce the manual workload involved in reviewing and scoring materials used for symposiums. Evaluators currently spend considerable time assessing relevance, quality, and technical rigor. The AI helps streamline this process by providing an initial, consistent rating that supports quicker filtering and prioritization.
Purpose and benefits: By speeding up the presentation reference material selection process, the AI allows subject-matter experts to focus on deeper evaluation rather than preliminary screening. This improves efficiency and helps ensure that high-quality, policy-relevant research is highlighted for symposiums, ultimately supporting better-informed supervisory and regulatory perspectives that benefit the broader financial system and the public.
Topic area: IT
Development stage: Pre-deployment
Impact assessment: This use case assigns ratings to research papers and is a solely internal analytical task.
US federal AI use case: Microsoft Power Automate (custom document processing model)
Agency: Environmental Protection Agency - OFA
Problem addressed: Saving time and money by extracting only useful information from lengthy utility bills and putting it into an easy to read format automatically.
Purpose and benefits: Cost savings and reduced man hours.
Topic area: Admin Functions
Development stage: Deployed
Impact assessment: The output of this AI use case does not serve as a principal basis for decisions or actions that have a legal, material, binding, or significant effect on rights or safety.
First used: 2025-09-01