GreatNorthCollective/greatnorth-us-federal-ai-inventory huggingface dataset:
US federal AI use case: Agency Support Companion (ASC) chatbot
Agency: Social Security Administration - Chief Information Officer
Problem addressed: Generative AI model to create content, summarization and research capabilities
Purpose and benefits: Assist all internal users across the agency in their daily tasks related to content generation, analysis, refinement, and general research capabilities.
Topic area: IT
Development stage: Deployed
First used: 2025-04-16
US federal AI use case: Data Governance Product (DGP) -  Data cataloging and predictive analysis of data assets.
Agency: Social Security Administration - Chief Information Officer
Problem addressed: Vendor built in AI engine for data cataloging to automates the discovery, classification, and curation of data assets. And also provides predictive insights for data asset analytics. Uses Natural Language Processing (NLP) enables non-technical stakeholders to contribute to rule creation and facilitates the conversion of plain text into regular expression.
Purpose and benefits: 1. Reduced manual effort in assigning Business Terms to data assets in the Technical data catalog. 2. Reduced effort and time through generation of data quality rule code.
Topic area: IT
Development stage: Deployed
First used: 2014-11-01
US federal AI use case: Intelligent generation of modernized code.
Agency: Social Security Administration - Chief Information Officer
Problem addressed: The module uses AI techniques such as cluster analysis, pattern matching, templates, and programming language models to generate modernized code in a new target language.
These AI techniques enable it to perform efficient data analysis, processing, and intelligent generation of new code. AI powered approach provides structured standardized code that’s highly maintainable.
Purpose and benefits: The GenAI component accelerates legacy system modernization by automatically analyzing COBOL and other legacy code, generating consistent business requirements documentation, and performing refactoring and re-imagining to transform code into modern languages and frameworks (e.g., Java, Java Spring Boot). This capability reduces manual effort required for document creation, supports knowledge retention as subject matter experts retire, and shortens development cycles by enabling faster updates to systems that serve the public.
Topic area: IT
Development stage: Deployed
First used: 2024-10-01
US federal AI use case: Policy Assistance Tool (PAT)
Agency: Social Security Administration - Chief Information Officer
Problem addressed: The system is designed to help employees quickly and easily find accurate policy information, improving efficiency and the user experience for those who need to access agency policies.
Purpose and benefits: The system is expected to make it faster and easier for users to access accurate and up-to-date policy information. This will improve efficiency, streamline processes, and enhance service delivery, supporting the agency’s mission and benefiting the general public.
Topic area: Benefits Processing
Development stage: Pilot
Risk category: High-impact
First used: 2025-09-16
US federal AI use case: Coding Assistance
Agency: Social Security Administration - Chief Information Officer
Problem addressed: Increase developer efficiency through faster coding, time savings and cost reduction.
Purpose and benefits: Reduced task switching and maintain flow state
•	Enhanced developer experience
•	Improved developer retention
•	Improved code quality and maintainability
•	Improved customer experience
•	Reduced bugs and technical debt
•	Go to market faster
Topic area: IT
Development stage: Pre-deployment
First used: 2025-02-01
US federal AI use case: Mainframe code modernization assistant
Agency: Social Security Administration - Chief Information Officer
Problem addressed: Increase developer efficiency through faster coding, time savings and cost reduction.
Purpose and benefits: Reduced task switching and maintain flow state
•	Enhanced developer experience
•	Improved developer retention
•	Improved code quality and maintainability
•	Improved customer experience
•	Reduced bugs and technical debt
•	Go to market faster
Topic area: IT
Development stage: Pre-deployment
US federal AI use case: Enterprise Ticketing System (ETS)
Agency: Social Security Administration - Chief Information Officer
Problem addressed: This AI use case consolidates searching capabilities across multiple applications and portals to help employees find and locate the appropriate form to submit a request or problem they may have.
Purpose and benefits: The use care reduces the time and complexity involved with locating request forms.
Topic area: IT
Development stage: Deployed
First used: 2025-09-01
US federal AI use case: General Use Chatbot
Agency: Social Security Administration - Chief Information Officer
Problem addressed: Generative AI model to create content, summarization, analyzation and research capabilities
Purpose and benefits: Copilot can help with routine tasks (e.g.: writing emails/articles), provide suggestions for improving content, offer valuable data insights and image generation.
Topic area: IT
Development stage: Pilot
First used: 2025-08-01
US federal AI use case: AI Comment Analysis
Agency: Social Security Administration - Chief Information Officer
Problem addressed: The AI comment analysis system supports the decision-making of SSA public comment reviewing staff by making preliminary designations as to whether a given public comment (or select attachment content) contains any of a set of predefined types of flagged content, such as personally identifiable information (PII), offensive content, and other staff-defined categories. The process of reviewing public contents, which can sometimes volumes in the hundreds of thousands, is slow and resource intensive for the agency.  The AI system helps streamline the process by directing staff attention to areas of potential interest.
Purpose and benefits: Improved efficiency of public comment review compared to purely manual methods.  Potential improvements to the consistency and quality of comment review decision-making by introducing a consistent preliminary screen to support decision-making.
Topic area: Service Delivery
Development stage: Pilot
First used: 2025-09-21
US federal AI use case: Modernized Development Worksheet (MDW)
Agency: Social Security Administration - Chief Information Officer, Analytics and Improvements
Problem addressed: This AI use case reviews data during case development so it can be better categorized. The use case reduces processing time and customer wait times.
Purpose and benefits: Reduce considerable workloads from the Processing Centers by eliminating the manual categorization of MDWs
Topic area: Benefits Processing
Development stage: Deployed
First used: 2023-12-01
US federal AI use case: Pre-Effectuation Review (PER) / Targeted Denial Review (TDR) Models
Agency: Social Security Administration - Chief Information Officer, Analytics and Improvements
Problem addressed: This AI use case identifies high likelihood of error in certain claims and refers them for review. This use case reduces incorrect benefits payment.
Purpose and benefits: Pre-Effectuation Review (PER) and Targeted Denial Review (TDR) benefit public, taxpayers, and claimants in ensuring that SSA provides benefits for those who qualify for benefits based on the SSA policy and guidelines.
Topic area: Benefits Processing
Development stage: Deployed
Risk category: High-impact
First used: 2003-12-01
US federal AI use case: Continuing Disability Review Model
Agency: Social Security Administration - Chief Information Officer, Analytics and Improvements
Problem addressed: This AI use case identifies disability cases with the greatest likelihood of medical improvement and flag them for a continuing disability review to improve the accuracy of program administration.
Purpose and benefits: Improving accurate claim processing: ensuring that only those who qualify for benefits remain on the rolls.
Topic area: Benefits Processing
Development stage: Deployed
Risk category: High-impact
First used: 2023-09-30
US federal AI use case: Social Security Income (SSI) Redetermination Model
Agency: Social Security Administration - Chief Information Officer, Analytics and Improvements
Problem addressed: This AI use case identifies SSI overpayment cases that have highest expected overpayments for review.
Purpose and benefits: Helps prioritize important program activities and contributes to overall public program efficiency and effectiveness.
Topic area: Benefits Processing
Development stage: Deployed
Risk category: High-impact
First used: 1999-01-01
US federal AI use case: Proactive Triage and Analysis of Hearings (PATH)
Agency: Social Security Administration - Chief Information Officer, Analytics and Improvements
Problem addressed: This AI use case flags high likelihood favorable claims and refers them to human adjudicators for further review to determine eligibility for on-the-record hearing decisions.
Purpose and benefits: The use case improves case flow, speeds up eligibility decision, increases consistency and accuracy, and provides better service to the public.
Topic area: Benefits Processing
Development stage: Deployed
Risk category: High-impact
First used: 2024-11-01
US federal AI use case: Generative Artificial Intelligence (AI) for Analytic Insights
Agency: Social Security Administration - Chief Information Officer, Analytics and Improvements
Problem addressed: Generative AI model to analyze SSA's National 800 Number and Field Office call transcripts as well as Interactive Voice Response (IVR) system call logs to provide insights into caller intent, call resolution, and call topics.
Purpose and benefits: The insights help identify areas for improvement in policies and processes, leading to better customer service and reduced wait times. Ongoing analysis and monitoring support more effective system performance and enhance the overall customer experience.
Topic area: IT
Development stage: Deployed
First used: 2023-09-30
US federal AI use case: Customer Insight Tool
Agency: Social Security Administration - Chief Information Officer, Analytics and Improvements
Problem addressed: SSA uses a survey system to deliver and manage customer surveys. Part of the deployed system includes an AI capability for performing text analytics for identifying and tracking customer sentiments and key trends.
Purpose and benefits: The AI-powered text analytics capability within SSA’s survey system helps the agency better understand customer experiences by analyzing unstructured feedback. It outputs sentiment ratings, categorized themes, suggested actions, customer effort indicators, and translated text. These insights enable early detection of emerging trends and provide a clearer view of positive and negative drivers in customer interactions, supporting more responsive and informed service improvements for the public.
Topic area: Service Delivery
Development stage: Deployed
First used: 2021-08-01
US federal AI use case: Benefit and Earnings Public Use File
Agency: Social Security Administration - Chief Information Officer, Analytics and Improvements
Problem addressed: Generate high fidelity synthetic benefits and earnings data for external researches to support policy research and decision making while protecting privacy.
Purpose and benefits: Enhanced data privacy; inform policies to support data driven decision making
Topic area: Other
Development stage: Deployed
First used: 2025-05-01
US federal AI use case: Mobile Wage Reporting
Agency: Social Security Administration - Chief Information Officer, Digital Customer Solutions
Problem addressed: Uses AI to extract text/data from scanned images/documents representing pay stubs or payroll information to enable faster processing.
Purpose and benefits: Increased speed and accuracy
Topic area: Benefits Processing
Development stage: Deployed
First used: 2022-05-14
US federal AI use case: SSA 800# Public Question & Answer Bot and OIG Hotline recording of fraud, waste and abuse.
Agency: Social Security Administration - Chief Information Officer, Digital Customer Solutions
Problem addressed: The Q&A bot answers caller’s questions using approved FAQs found on SSA.GOV. Support is provided in both English and Spanish. Calls answered solely by the bot reduce the wait for other callers needing agent service. A bot will also ask questions and populate responses from the public as a record of their interaction when reporting fraud, waste and abuse.
Purpose and benefits: Improved service to the public by answering calls faster and lowering expense to handle transactions.
Topic area: Service Delivery
Development stage: Deployed
First used: 2023-06-05
US federal AI use case: Digital Identity Verification Services
Agency: Social Security Administration - Chief Information Officer, Digital Customer Solutions
Problem addressed: The AI is intended to solve the problem of securely verifying and authenticating individuals’ identities online, ensuring that users can prove and share their identity safely for digital services.
Purpose and benefits: The expected benefits of the AI include reducing identity theft and fraud, ensuring compliance with security standards, increasing operational efficiency by minimizing manual reviews, enabling users to access multiple services with a single verification, and improving access for underserved populations through alternative verification methods.
Topic area: Cybersecurity
Development stage: Deployed
Risk category: High-impact
First used: 2020-06-05
US federal AI use case: Insight
Agency: Social Security Administration - Chief Information Officer, Disability Information Systems
Problem addressed: This AI use case is decision support software used by hearings and appeals-level Disability Program adjudicators to help maximize the quality, speed, and consistency of their decision making.  The use case analyzes the free text of disability decisions and other case data to offer adjudicators real-time alerts on potential quality issues and case-specific reference information within a web application.  The use case increases decision quality and reduces human error.
Purpose and benefits: The use case increases decision quality and reduces human error.
Topic area: Benefits Processing
Development stage: Deployed
First used: 2017-10-01
US federal AI use case: Intelligent Medical Language Analysis Generation (IMAGEN)
Agency: Social Security Administration - Chief Information Officer, Disability Information Systems
Problem addressed: This AI use case helps employees visualize, search, and more easily identify relevant clinical content in medical records.  The use case improves efficiency and accuracy of disability determinations/decisions.
Purpose and benefits: The use case improves efficiency and accuracy
Topic area: Benefits Processing
Development stage: Deployed
Risk category: High-impact
First used: 2021-08-20
US federal AI use case: Speech to Text Video Transcription
Agency: Social Security Administration - Chief Information Officer, Disability Information Systems
Problem addressed: Generate transcript from recorded audio of disability hearings
Purpose and benefits: The Speech-to-Text Video Transcription solution improves efficiency and accuracy in disability hearings by auto-generating searchable transcripts, reducing manual work, and enabling faster, more informed decisions that benefit both the agency and the public.
Topic area: Benefits Processing
Development stage: Deployed
First used: 2024-05-06
US federal AI use case: Vocational Assessment Assistant Tool  (VAAT)
Agency: Social Security Administration - Chief Information Officer, Disability Information Systems
Problem addressed: The AI is intended to address the problem of a manual, time-consuming, and expertise-dependent process for researching job codes and analyzing transferable skills, which can result in inconsistent outcomes among different examiners and offices.
Purpose and benefits: The expected benefits of the AI include streamlining and speeding up vocational analysis, increasing consistency and standardization in decision-making, improving the quality and reliability of determinations, and allowing staff to dedicate more time to complex case analysis rather than routine manual tasks. These outcomes support the agency’s mission and benefit the general public by promoting more efficient and equitable service delivery.
Topic area: Benefits Processing
Development stage: Deployed
Risk category: High-impact
First used: 2025-09-30
US federal AI use case: Application Observability Support
Agency: Social Security Administration - Chief Information Officer, System Operations and Hardware Engineering
Problem addressed: To assist OCIO users in monitoring critical applications for performance and availability management on premises and in the cloud environment.  AI is used to create a baseline based on a weeks’ worth of data.  When the data collected significantly deviates from the baseline alerts are sent to appropriate OCIO user base.
Purpose and benefits: Performance issues are addressed as soon as possible to avoid critical applications failure that would impact SSA's business processes. Incident summary produced creates an opportunity for future  risk avoidance and mitigation processes through after actions steps.
Topic area: Cybersecurity
Development stage: Deployed
First used: 2025-04-03
US federal AI use case: Therapy Chatbot - Text-Based Mental Health Support for SSA Employees
Agency: Social Security Administration - Human Resources
Problem addressed: This AI use case is a therapy chatbot that employees can access on their own personal devices and is designed to provide confidential, immediate mental health support to employees, helping address stress, emotional challenges, and limited access to traditional counseling services.
Purpose and benefits: The chatbot promotes employee well-being, reduces stress, and enhances resilience, which supports a healthier workforce and improves overall agency performance and public service delivery.
Topic area: Health and Medical
Development stage: Deployed
First used: 2023-09-01
US federal AI use case: Training Interaction Simulator
Agency: Social Security Administration - Human Resources
Problem addressed: Employees do not have an avenue to practice interactions with a variety of clients/coworkers with a range of attitudes.
Purpose and benefits: Users gain practice with simulated conversations and receive constructive feedback on their responses.
Topic area: HR
Development stage: Deployed
First used: 2025-06-03
US federal AI use case: Human Resource Chatbot
Agency: Social Security Administration - Human Resources
Problem addressed: Generative AI chatbot grounded in SSA Personnel Policy Manual and other HR related documents that provides HR staff with the ability to search HR policy and related documents using natural language to answer SSA employee inquiries, analyze policies and HR law, and create needed updates to personnel documentation.
Purpose and benefits: Reduce the time to retrieve HR policy information by allowing HR staff to ask HR policy-related questions using natural language and follow-up questions to refine responses. Provide the ability to analyze HR policy documents as well as more quickly respond to HR inquiries from SSA employees.
Topic area: HR
Development stage: Deployed
First used: 2025-04-30
US federal AI use case: Training Audio and Video Generation
Agency: Social Security Administration - Human Resources
Problem addressed: Generative AI model to create audio and visual content for SSA training products
Purpose and benefits: Quickly generating custom audio and visual content for training products.
Topic area: HR
Development stage: Pilot
First used: 2025-09-08
US federal AI use case: Quick Disability Determinations Model
Agency: Social Security Administration - Law and Policy, Disability Policy
Problem addressed: Used to screen initial applications to identify cases where a favorable disability determination is highly likely and medical evidence is readily available to prioritize this workload and expedite case processing.
Purpose and benefits: QDD predictive model quickly identifies and prioritizes disability claims processing for individuals with severe, life-threatening, or life-altering conditions. This approach reduces processing times, improves access to benefits for those in urgent need, and allows the agency to allocate resources more efficiently, ultimately enhancing service delivery for the public.
Topic area: Benefits Processing
Development stage: Deployed
Risk category: High-impact
First used: 2008-02-01
US federal AI use case: AI Input in Translation
Agency: Department of State - A/PRI
Problem addressed: Leveraging machine-based tools to streamline workflows in translation work. Machine output is carefully post-edited by professional human translators to ensure highest quality product.
Purpose and benefits: Reduced time, reduced cost, and improved accuracy of translated documents.
Topic area: Other
Development stage: Deployed
First used: 2024-01-19
US federal AI use case: FOIA Web ML Document Indexer
Agency: Department of State - A/SKS
Development stage: Retired
US federal AI use case: AI-Augmented Declassification Review
Agency: Department of State - A/SKS
Problem addressed: The amount of documents, particularly cables and emails, that require declassification review increases exponentially in the next few years. Manual review is unsustainable and expensive given the number of cables (in the hundreds of thousands) and emails (increasing from hundreds of thousands to millions).
Purpose and benefits: The expected benefits and positive outcomes from using AI are cost savings by reducing the need of manual reviews, reduce labor in cable review by up to 80%, reduce the time needed for annual review, and create more consistency in the review process.
Topic area: Admin Functions
Development stage: Deployed
Risk category: High-impact
First used: 2023-02-02
US federal AI use case: BudgetChat AI Tool
Agency: Department of State - BP
Problem addressed: Inputting large amounts of data from paper forms into a digital system using AI.
Purpose and benefits: Time and cost savings, improved ability to identify crucial supplemental information available in other budget documents, improved accuracy in identifying key budget information in individual documents.
Topic area: Admin Functions
Development stage: Pilot
First used: 2024-09-12
US federal AI use case: Evaluating Customer Feedback and Sentiments with AI
Agency: Department of State - CA
Problem addressed: To leverage Natural Language Processing (NLP) and secure Large Language Models (LLM) on unstructured text data to identify actionable insights to drive customer improvement initiatives.
Purpose and benefits: Greater insights about user experiences with consular services and the impact of service changes.
Topic area: Service Delivery
Development stage: Pilot
First used: 2024-07-01
US federal AI use case: Consular Affairs FaceVACS
Agency: Department of State - CA
Problem addressed: To automatically check passport photo quality during the Online Passport Renewal (OPR) process, providing instant feedback to ensure submitted images meet requirements.
Purpose and benefits: Instant feedback to ensure submitted images meet requirements.
Topic area: Service Delivery
Development stage: Pre-deployment
US federal AI use case: Travel.State.Gov (TSG) Enhanced Search and Chatbot
Agency: Department of State - CA
Development stage: Retired
US federal AI use case: Travel.state.gov (TSG) Content Refinement with AI Text Editor
Agency: Department of State - CA
Development stage: Retired
US federal AI use case: Predictive Analytics Platform
Agency: Department of State - CA
Development stage: Retired
US federal AI use case: Innovation and Transformation Measurement and Prediction
Agency: Department of State - CA
Development stage: Retired
US federal AI use case: CodeGen - AI-assisted IT Application Development
Agency: Department of State - CA
Development stage: Retired
US federal AI use case: Translation of Consular Content using AI
Agency: Department of State - CA
Development stage: Retired
US federal AI use case: NIV Adjudication Review Recommendation Engine (ARRE)
Agency: Department of State - CA
Problem addressed: ARRE is used to make post-adjudication managerial quality assurance review time more efficient. The current required managerial review of cases includes a randomly selected portion, which is not optimized to help managers allocate time toward cases where secondary review is most likely to surface documentation gaps, policy-complex adjudications, or process compliance issues. As a result, managers may spend review capacity on routine cases while missing opportunities to identify coaching needs or quality issues within the fixed review window.
Purpose and benefits: The primary purpose of ARRE is to support the post-adjudication, managerial quality assurance review workflow by helping managers efficiently meet existing review requirements through queue ordering and prioritization. This provides more efficient use of manager review time and more consistent post-adjudication oversight by better targeting the fixed, required managerial review effort toward cases with atypical attributes that warrant a second look for quality assurance purposes. The expected benefits are improved review consistency and improved documentation of decision-making.
Topic area: Admin Functions
Development stage: Pilot
First used: 2025-01-01
US federal AI use case: Live Consular AI Language Augmentation (LCALA) - Visa Interview Pilot
Agency: Department of State - CA
Problem addressed: Language gaps between applicants and non-native-speaker adjudicators create inconsistent, ad-hoc translation during brief (~3-minute) interviews or is limited to questions the adjudicator is familiar with asking, increasing the risk of misunderstanding (dialect/register, pronouns, named entities) and forcing repeat questions, delays, or uneven outcomes. Interpreter availability is limited, and reliance on bilingual staff is not scalable to demand and will impact other consular functions. These constraints reduce interview efficiency, strain officer workload, and can erode customer experience and perceived equity.
Purpose and benefits: More consistent comprehension in ~3-minute interviews; Improved efficiency and throughput; Equity and customer experience; Reduced interpreter burden; Operational resilience
Topic area: Other
Development stage: Pilot
Risk category: High-impact
First used: 2025-03-17
US federal AI use case: AI Programmatic Insights
Agency: Department of State - CA
Problem addressed: Regional Directors (RD) have to analyze current passport trends and data to determine overall performance and resource requirements to enable successful alignment to overall performance targets; however, the raw data requires analysis and doesn't currently allow for easy input to evaluate different scenarios, which results in RDs having to respond to passport performance with limited information.
Purpose and benefits: An AI-driven solution that empowers Regional Directors to forecast programmatic trends, anticipate demand cycles, and respond effectively to external factors. This solution empowers Regional Directors with data-driven insights to anticipate demand, optimize resources, and proactively address challenges impacting passport agencies.
Topic area: Other
Development stage: Deployed
First used: 2025-11-21
US federal AI use case: RegScale
Agency: Department of State - CA
Problem addressed: The AI in RegScale is intended to reduce the manual workload, complexity, and latency in compliance management. It automates the extraction and initial drafting of regulatory documentation, identifies control gaps, and provides plain-language explanations of requirements. The goal is to improve efficiency, accuracy, and continuous audit readiness while enabling small teams to scale compliance across multiple regulatory frameworks.
Purpose and benefits: The expected benefits of RegScale’s AI include reduced compliance costs, faster audit readiness, improved accuracy of regulatory reporting, and more efficient use of agency staff resources. For the general public, this translates into stronger protection of sensitive data, improved transparency, and quicker delivery of secure government services.
Topic area: Cybersecurity
Development stage: Pre-deployment
US federal AI use case: Live Consular AI Language Augmentation (LCALA) - OCS/ACS Pilot
Agency: Department of State - CA
Problem addressed: LCALA OCS/ACS Pilot aims to close language gaps in routine, time-sensitive citizen services by providing on-demand interpretation for calls and in-person interactions. Today, limited interpreter availability and uneven reliance on bilingual staff can cause delays, confusion, and repeat contacts when conveying guidance or coordinating with local authorities. LCALA seeks to improve clarity and timeliness of these communications, reducing callbacks and handoffs, while remaining assistive only and not replacing certified interpreters where required.
Purpose and benefits: Faster, clearer OCS/ACS communications; Fewer repeat contacts and escalations; Service equity and accessibility; Staff efficiency; Interagency coordination.
Topic area: Emergency Mgmt
Development stage: Pilot
First used: 2025-01-01
US federal AI use case: Within Grade Increase Data Extraction Automation
Agency: Department of State - CGFS
Problem addressed: Moving large amounts of data from paper and/or digital forms into a digital system can be challenging, time intensive, and costly.
Purpose and benefits: Lower processing time and resources for cost savings.
Topic area: Procurement and Finance Mgmt
Development stage: Deployed
First used: 2023-10-17
US federal AI use case: DS-5528 Promissory Note Automation
Agency: Department of State - CGFS
Problem addressed: Moving large amounts of data from paper and/or digital forms into a digital system is challenging, time intensive, and costly.
Purpose and benefits: A reduction in processing time and needed resources to lower costs to complete tasks.
Topic area: Procurement and Finance Mgmt
Development stage: Deployed
First used: 2023-12-08
US federal AI use case: StateInsight
Agency: Department of State - CGFS
Problem addressed: The need to summarize documents to produce a description of procurement awards and to allow authorized users to ask questions of the documents.
Purpose and benefits: Time and cost savings through efficiency, improved contract management for better outcomes, and more continuity of contractor services.
Topic area: Procurement and Finance Mgmt
Development stage: Pre-deployment
US federal AI use case: Violence Against Civilians Model
Agency: Department of State - CSO
Development stage: Retired
US federal AI use case: Mass Mobilization Model
Agency: Department of State - CSO
Development stage: Retired
US federal AI use case: Senturion Alpha
Agency: Department of State - CSO
Development stage: Retired
US federal AI use case: User and Entity Behavior Analytics (UEBA)
Agency: Department of State - DS
Development stage: Retired
US federal AI use case: Diplomatic Security - Legal Instruction Unit
Agency: Department of State - DS
Problem addressed: Insufficient personnel and resources available to create multimedia, conduct necessary research, and develop required curriculum.
Purpose and benefits: Cost savings due to increased efficiency and decreased contracts/personnel to meet the needs of the Department.
Topic area: Law Enforcement
Development stage: Pilot
First used: 2025-08-01
US federal AI use case: Data.State Analytics and AI Funhouse
Agency: Department of State - DT
Problem addressed: Data scientists require a cybersecure platform for data science experiments, learning, and workflow deployment. Funhouse provides secure and documented access to GenAI and ML tools in an authorized and auditable platform.
Purpose and benefits: Provide cybersecure analytics and AI experimentation to support mission delivery and process efficiency, increased mission efficiency, accelerated AI innovation, and cost savings.
Topic area: IT
Development stage: Deployed
First used: 2025-01-10
US federal AI use case: FOIA 360 AI Matching Tool
Agency: Department of State - DT
Development stage: Retired
US federal AI use case: Property and Procurement Analytics
Agency: Department of State - DT
Problem addressed: The need to expand analytics within the Integrated Logistics Management System (ILMS) through development of a machine learning model for detecting patterns of potential anomalous activity in property and procurement.
Purpose and benefits: The identification and reduction of anomalous procurement activity in overseas posts.
Topic area: Admin Functions
Development stage: Pre-deployment
US federal AI use case: AI Accelerator
Agency: Department of State - DT
Problem addressed: The need to quickly discover answers to common questions about using AI at the Department, locate tools and services, and get help with new AI needs - including guidance and requirements, available tools and solutions, and related processes.
Purpose and benefits: Enhanced user experience to accelerate AI use at the Department, operational efficiencies to free up time for more complex tasks, and scalability to quickly incorporate new knowledge and related tasks.
Topic area: Admin Functions
Development stage: Pre-deployment
US federal AI use case: AI Research Engine (AIRE)
Agency: Department of State - DT
Problem addressed: The need to improve the quality of reporting from the continuously growing sources of information through the categorization, summarization, and translation of information. Includes formerly titled use case "J Reports Data Collection & Management Tool (DCT)."
Purpose and benefits: AI enables the quick categorization, summarization, and translation of data to make it easily accessible for quicker drafting of higher quality reports, resulting in staff time savings, reduced redundant workload, and better information to support the mission. Significant reduction in time and costs required to create higher quality reports.
Topic area: IT
Development stage: Deployed
First used: 2024-02-15
US federal AI use case: PFCS Proving Ground
Agency: Department of State - DT
Problem addressed: The need for an experimentation platform to promote the development and adoption of AI solutions.
Purpose and benefits: The ability for personnel and teams to experiment with developing innovative AI solutions to address mission delivery or back office processes. Efficiency and effectiveness.
Topic area: IT
Development stage: Deployed
First used: 2025-05-01
US federal AI use case: DT Data Analytics and Assessment (DAA) AI Use Case ITCP Data Harvest
Agency: Department of State - DT
Development stage: Retired
US federal AI use case: POA&M Orchestration
Agency: Department of State - DT
Development stage: Retired
US federal AI use case: StateChat
Agency: Department of State - DT
Problem addressed: The need to safely and securely access, share, summarize, and research Sensitive But Unclassified (SBU) Department information. Improve and reduce time to translating documents, summarizing reports, and drafting emails. StateChat is the Department's enterprise Generative AI-powered chatbot.
Purpose and benefits: Delivers greater operational efficiency and makes personnel better collaborators and competitors on the front lines of diplomacy, delivering decision advantages, negotiation preparation, and preparedness through simulation. Reduced costs and more consistent documents referencing SBU information.
Topic area: IT
Development stage: Deployed
First used: 2024-03-04
US federal AI use case: J Reports Data Collection & Management Tool (DCT)
Agency: Department of State - DT
Development stage: Retired
US federal AI use case: Electronic Health Record AI Enhancements
Agency: Department of State - DT
Problem addressed: Provide efficient, accurate, and comprehensive medical electronic health record (EHR) management, patient care, and administrative workflows by leveraging AI-powered tools, including large language models (LLMs) and natural language processing (NLP).
Purpose and benefits: Improved operational efficiency, reduction of errors, and greater focus on delivering quality patient care. Improved patient data and safety with cost savings and operational efficiencies, transparency, and security. Enhanced clinical decision-making by summarizing patient information, identifying discrepancies, and generating referrals based on historical data and current inputs.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
First used: 2025-03-03
US federal AI use case: TIP Report Research Translation
Agency: Department of State - DT
Problem addressed: The TIP Report Translation AI system provides informal, unofficial translations for materials related to the annual Trafficking in Persons report.  This capability saves staff time and allows researchers and drafters to focus on critical report needs, such as identifying and resolving data gaps.
Purpose and benefits: This capability saves staff time and allows researchers and drafters to focus on critical report needs, such as identifying and resolving data gaps.
Topic area: Other
Development stage: Deployed
First used: 2023-11-01
US federal AI use case: ECA Program Management and Outreach - Summarization
Agency: Department of State - ECA
Development stage: Retired
US federal AI use case: Natural Language Processing (NLP) for Foreign Assistance Appropriations Analysis
Agency: Department of State - F/FAO
Problem addressed: Summarizing the key points of a lengthy report using AI.
Purpose and benefits: The NLP application reduces the time needed to extract congressional directives from the annual appropriations bill which ultimately shortens the cycle time for generating the report detailing the annual allocation of U.S. foreign assistance funds to foreign countries and international organizations (i.e. the 653(a) report).
Topic area: Service Delivery
Development stage: Deployed
First used: 2021-08-05
US federal AI use case: ForeignAssistance.gov Processing for Mismatched Data
Agency: Department of State - F/FAO
Development stage: Retired
US federal AI use case: FA.gov PII Picker
Agency: Department of State - F/FAO
Problem addressed: The need to streamline a process, improve accuracy, and provide validation checks. The previous process to identify Personally Identifying Information (PII) required additional layers of manual verification.
Purpose and benefits: Additional support to ensure data and privacy protections in public facing databases with less manual time and effort.
Topic area: International Affairs
Development stage: Deployed
First used: 2024-04-30
US federal AI use case: Integrated Country Strategy (ICS) Turbo
Agency: Department of State - F/FAO
Problem addressed: The need to conduct thematic analysis on large volumes of Integrated Country Strategy (ICS) data in a comprehensive and time efficient manner.
Purpose and benefits: Increased capacity of personnel to identify lessons learned and best practices by leveraging historical documentation.  This is intended to be accomplished by decreasing the time and effort spent reading, synthesizing, and categorizing the contents of historical Integrated Country Strategies (ICS).
Topic area: International Affairs
Development stage: Deployed
First used: 2025-06-11
US federal AI use case: FA.gov RedactAid
Agency: Department of State - F/FAO
Problem addressed: The need to improve data quality of information and prevent sensitive data from being published to ForeignAssistance.gov.
Purpose and benefits: Reduced effort and improved consistency and accuracy in protecting sensitive information from getting published in public-facing databases.
Topic area: International Affairs
Development stage: Deployed
First used: 2024-12-13
US federal AI use case: Digital Media Analytics Platform
Agency: Department of State - GPA
Problem addressed: Using open-source neural machine translation models to translate global media articles and Department and public foreign social media posts into English.
Purpose and benefits: The use case reduces labor in producing media summary reports.
Topic area: International Affairs
Development stage: Deployed
First used: 2024-03-01
US federal AI use case: AI Tools to Enhance PD Workflows
Agency: Department of State - GPA
Development stage: Retired
US federal AI use case: Rosie Chat Bot
Agency: Department of State - MGT
Problem addressed: The need for employees to locate consistent, accurate answers to HR-related questions quickly based on internal information.
Purpose and benefits: Cost savings, reduced wait times, improved access to information, enhanced efficiency, scalability, and consistency in communication.
Topic area: HR
Development stage: Pilot
First used: 2025-09-02
US federal AI use case: Utility Invoices Data Extraction
Agency: Department of State - MGT
Problem addressed: The need to reconcile and process payments faster.
Purpose and benefits: Reduced time and labor costs through a more efficient and accurate process that automatically identifies key information to issue payments.
Topic area: Admin Functions
Development stage: Deployed
First used: 2023-10-04
US federal AI use case: Database for Arrivals
Agency: Department of State - MGT
Problem addressed: Automating the extraction of personnel information to create a centralized database for arrivals and departures.
Purpose and benefits: Enhances collaboration and coordination among management sections, streamlining operations.
Topic area: HR
Development stage: Pre-deployment
US federal AI use case: AI SharePoint Chatbot
Agency: Department of State - MGT
Problem addressed: The need for efficient access to post-specific information.
Purpose and benefits: Improves productivity, engagement, and access to post-specific information.
Topic area: IT
Development stage: Pre-deployment
US federal AI use case: Databricks Code Assistant
Agency: Department of State - MGT
Problem addressed: Determining potential billing problems for Department mobile plans can be time consuming and prone to errors.
Purpose and benefits: Improve efficiency, save costs, and save time conducting analyses of mobile plans, bills, and usage.
Topic area: IT
Development stage: Pre-deployment
US federal AI use case: Automatic Detection of Authentic Material
Agency: Department of State - NFATC
Problem addressed: The need to detect/identify authentic materials in target languages, reducing the time to develop language curricula and tests.
Purpose and benefits: Reduced staff hours and improved variety of materials in foreign languages.
Topic area: Other
Development stage: Pilot
First used: 2023-11-10
US federal AI use case: Office of the Historian (OH) Historical Analysis for Negotiations
Agency: Department of State - NFATC
Problem addressed: The need for historical information in real time to assist with analysis by the Office of the Historian (OH) and decision making.
Purpose and benefits: Negotiators save time and achieve information advantage related to historical country relationships.
Topic area: International Affairs
Development stage: Pilot
First used: 2025-07-01
US federal AI use case: FSI Enterprise Operations - Gaming and Simulations
Agency: Department of State - NFATC
Development stage: Retired
US federal AI use case: Enhancing Training Effectiveness in FSILearn Using AI
Agency: Department of State - NFATC
Development stage: Retired
US federal AI use case: FSI Continuous Learning Solutions
Agency: Department of State - NFATC
Development stage: Retired
US federal AI use case: Creating Persistent Virtual Reality Personas for Dynamic Training
Agency: Department of State - NFATC
Problem addressed: There is a need to improve effectiveness of immersive training in the future. The team develops a dynamic integration between multiple AI tools to create stored/persistent "personas" that can be interacted with during training-related virtual reality (VR) exercises.
Purpose and benefits: Natural conversation-based simulations and more effective training scenarios.
Topic area: Other
Development stage: Pre-deployment
US federal AI use case: Natural Language Processing (NLP) to pull key information from unstructured texts
Agency: Department of State - PM
Development stage: Retired
US federal AI use case: Storyzy
Agency: Department of State - R/GEC
Development stage: Retired
US federal AI use case: Walter:  Generative AI Support Bot
Agency: Department of State - WHA
Problem addressed: The need to more effectively focus on critical customer requests with existing resources.
Purpose and benefits: Cost savings and reduced customer wait times by addressing Tier 0 and Tier 1 requests without human intervention.
Topic area: IT
Development stage: Deployed
First used: 2025-03-06
US federal AI use case: WHA/EX Information Management
Agency: Department of State - WHA
Problem addressed: Knowledge Management for administrative and IT related processes. Formerly known as "Low Earth Orbit (LEO) – Budget Office Inquiries" to answer questions frequently asked about budget.
Purpose and benefits: Cost savings and reduced customer wait times.
Topic area: IT
Development stage: Deployed
First used: 2025-03-03
US federal AI use case: Optiwatt EV Load Model
Agency: Tennessee Valley Authority - Commercial Energy Solutions
Purpose and benefits: Linear model to predict hourly unitized charging load from non-fleet EVs in a typical meteorological year (TMY).
Topic area: Energy and Environment
US federal AI use case: Cold-Weather Heat Pump Model
Agency: Tennessee Valley Authority - Commercial Energy Solutions
Purpose and benefits: KNN regression to predict hourly unitized impact of an upgraded CWHP in a residential home under historical and forecasted weather conditions.
Topic area: Energy and Environment
US federal AI use case: EE/DR Smart Thermostat Impact Model
Agency: Tennessee Valley Authority - Commercial Energy Solutions
Purpose and benefits: DR dispatch simulation to demonstrate hourly unitized impact of an EE/DR smart thermostat in a residential home under historical and forecasted weather & load conditions.
Topic area: Energy and Environment
US federal AI use case: Standard EE/BE Measure Impact Models
Agency: Tennessee Valley Authority - Commercial Energy Solutions
Purpose and benefits: Set of ~200 linear models for other EE & BE measures to predict hourly unitized impactunder historical and forecasted weather conditions. Based on a standardized set of calendar and weather features.
Topic area: Energy and Environment
US federal AI use case: EnergyRightPSPImpactsForecasting
Agency: Tennessee Valley Authority - Commercial Energy Solutions
Purpose and benefits: This app is (1) an ETL tool for ancillary data (2) a light-weight MLOps tool for the modeling of energy efficiency and electrification measure-level impact shapes, primarily as it relates to system planning assumptions and (3) a user interface to ES&P's forecast aggregation engine as a supply-side resource.
Topic area: Energy and Environment
US federal AI use case: CESASolarModel
Agency: Tennessee Valley Authority - Commercial Energy Solutions
Purpose and benefits: This app allows internal TVA users to generate sample bills for directly served and BCD-rate customers based on active wholesale rates, historical load, and expected shape/magnitude of new behind-the-meter solar arrays.
Topic area: Energy and Environment
US federal AI use case: CESAFCAAllocator
Agency: Tennessee Valley Authority - Commercial Energy Solutions
Purpose and benefits: Improved efficiency and productivity
Topic area: Energy and Environment
US federal AI use case: EnergyRightDERPortfolioEvaluation
Agency: Tennessee Valley Authority - Commercial Energy Solutions
Purpose and benefits: Enterprise Planning can now obtain aggregations of ES&P forecasts and ES&P can gain insight into evaluation methodologies. It also contains a connection to the ES&P forecast aggregation engine for reporting purposes and stochastic simulation tools.
Topic area: Energy and Environment
US federal AI use case: Arkio
Agency: Tennessee Valley Authority - Economic Development
Purpose and benefits: Enhanced visuals for economic development efforts
Topic area: IT
US federal AI use case: Extreme Load Analysis
Agency: Tennessee Valley Authority - Enteprise Planning
Purpose and benefits: Extreme load analysis involves estimating the likelihood of peaks in energy demand for different months of the year and hours of the day. This will aid in energy forecasting
Topic area: Energy and Environment