GreatNorthCollective/greatnorth-us-federal-ai-inventory huggingface dataset:
US federal AI use case: Geospatial Tools
Agency: Department of Justice - Department of Justice / Department wide
Problem addressed: DOJ personnel need a way to process, map, visualize, and analyze geographic data to protect the American public, further investigations, and facilitate information exchange with federal, state, local, and foreign partners.
Purpose and benefits: This use case enables DOJ to apply advanced AI/ML capabilities to mission-enabling geographic data in order to enhance data mapping, visualization, and integration.
Topic area: Law Enforcement
Development stage: Deployed
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
First used: 2025-01-01
US federal AI use case: Generating Recommendations, Outlines, and Summaries
Agency: Department of Justice - Department of Justice / DEA
Problem addressed: DEA needs a way to analyze unstructured and structured data to support providing recommendations, outlines, data classification, summaries, and other business operation support.
Purpose and benefits: To accelerate insights and tool development to advance DEA's business operations and better serve the public.
Topic area: Admin Functions
Development stage: Pre-deployment
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
US federal AI use case: FOIA Production Tools
Agency: Department of Justice - Department of Justice / Department wide
Problem addressed: Enhances and streamlines the processing of Freedom of Information Act (FOIA) requests. Automates tasks such as document classification, intelligent identification and redaction of sensitive or confidential information, and deduplication of documents.
Purpose and benefits: The AI capabilities enable more accurate and efficient organization and retrieval of FOIA-related documents. Additionally, AI optimizes workflows by automating repetitive tasks and minimizing human error, leading to faster processing times and increased operational efficiency. Overall, the incorporation of AI into FOIAXpress is designed to improve the efficiency, accuracy, and compliance of FOIA request processing, enabling staff to respond more promptly, reduce operational costs, and maintain higher standards of transparency and accountability.
Topic area: Admin Functions
Development stage: Deployed
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
First used: 2025-01-01
US federal AI use case: Fingerprint (Friction Ridge) Optical Character Recognition (OCR)
Agency: Department of Justice - Department of Justice / DEA
Problem addressed: DEA, when conducting fingerprint analysis to identify individuals who may be connected to evidence, needs to be able to compare friction ridge prints to other prints within the boundaries of a case. Product enables linking of cases where individuals are not necessarily identified.
Purpose and benefits: This use case saves time and provides information for human decision-making.
Topic area: Law Enforcement
Development stage: Deployed
Risk category: High-impact
First used: 2025-01-01
US federal AI use case: Extracting Data from Receipts to Speed Travel Reimbursement or Provide Logbook Documentation
Agency: Department of Justice - Department of Justice / DEA
Problem addressed: Gas receipts need to be reconciled / logged into FIRM – the AI would capture the data and can be used to record the receipt (reducing loss of paper) and eventually upload into FIRM reducing human data entry and time. IN also inspects receipts as part of their inspection. The laboratories also audit their OGV logbooks more than once annually. This would be a great pilot to expand into scanning and recording information from other purchases into UFMS and automate that process as well.
Purpose and benefits: Cost savings, live data entry of OGV use (miles and fuel consumption), streamlining of voucher packet creation
Topic area: Admin Functions
Development stage: Pilot
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
First used: 2025-09-01
US federal AI use case: EOIR Adjudicator Notice/Order Writing Assistance
Agency: Department of Justice - Department of Justice / EOIR
Problem addressed: To reduce time for EOIR adjudicators to draft notices and orders for immigration cases.  After reviewing the facts in the case and conducting a legal analysis of the issues presented, EOIR adjudicators and legal support staff determine their legal conclusions.  Technology could be utilized to assist in preparation of a draft document for review by EOIR personnel based on the adjudicator's legal conclusions.
Purpose and benefits: Improvement in the quality of writing (grammar, spelling, clarity, conciseness, etc.), as well as improvements to quality of decisions with more robust citations to the relevant facts in the case and the legal authority used to support the legal conclusions. Reduced time for drafting lengthy orders or notices. Reduced time to complete immigration cases.
Topic area: Admin Functions
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Entity Resolution
Agency: Department of Justice - Department of Justice / FBI
Problem addressed: Entity Extraction and Resolution
Purpose and benefits: Faster FBI operations
Topic area: IT
Development stage: Deployed
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
First used: 2025-03-01
US federal AI use case: Entity Extraction and Summarization
Agency: Department of Justice - Department of Justice / FBI
Problem addressed: Data triage
Purpose and benefits: Faster FBI operations
Topic area: Law Enforcement
Development stage: Pre-deployment
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
US federal AI use case: Enabling eDiscovery Platform AI
Agency: Department of Justice - Department of Justice / CIV
Problem addressed: Migrate CORA data to Relativity One or Everlaw, cloud based solutions to enable Relativity's and Everlaw's AI tools for review prioritization, privilege review and other advanced eDiscovery utilities. Utilize internal or third party-tools for AI-assisted collection and data processing, including image and voice recognition and analysis of complex data formats. Integrate E-Discovery tools into case management processes. This initiative transforms litigation support capabilities by leveraging AI to accelerate document review processes, reduce discovery costs, and improve case preparation efficiency and effectiveness.
Purpose and benefits: (1) Increases data availability and accessibility for integration with AI platforms through hosting on a scalable platform, in alignment with DOJ Data Strategy Goal #1 "Enterprise Data Management." Creates replicable enterprise capabilities that other DOJ components can adopt.                                                                                                                                                                                                                                   (2)  Allows migration to our existing environments more quickly. Discovery process will be streamlined with increased prioritization of review and lessens the time for manual privilege reviews.                                                                                                                                                                                                                                                                  (3) AI enabled workflows available to Division litigating teams for privilege review, case strategy and prioritized document review.
Topic area: IT
Development stage: Pre-deployment
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
US federal AI use case: Email Organization Plugin
Agency: Department of Justice - Department of Justice / TAX
Problem addressed: More efficient filing of email
Purpose and benefits: Reduced time spent on administrative record retention requirements
Topic area: Admin Functions
Development stage: Pre-deployment
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
US federal AI use case: Document Processing
Agency: Department of Justice - Department of Justice / TAX
Problem addressed: Use natural language processing to convert spoken audio to text for employees with vision or mobility limitations.
Purpose and benefits: Machine extraction and arrangement of data facilitates review and can allow human reviewers to locate relationships and patterns that would not otherwise be obvious.
Topic area: Law Enforcement
Development stage: Pre-deployment
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
US federal AI use case: Diagram Creation
Agency: Department of Justice - Department of Justice / TAX
Problem addressed: Make effective diagrams and illustrations quickly from text prompts for use in briefs and as demonstratives at hearings and trial
Purpose and benefits: More effective advocacy and reduced time in generating effective illustrations
Topic area: Law Enforcement
Development stage: Pre-deployment
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
US federal AI use case: Data Triage and Processing
Agency: Department of Justice - Department of Justice / FBI
Problem addressed: Transcription, translation, summarization, and object detection in audio and video
Purpose and benefits: Faster FBI operations
Topic area: Law Enforcement
Development stage: Pilot
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
First used: 2025-01-01
US federal AI use case: Data Triage
Agency: Department of Justice - Department of Justice / FBI
Problem addressed: Manual search for data through many reports
Purpose and benefits: Faster FBI operations
Topic area: Admin Functions
Development stage: Pre-deployment
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
US federal AI use case: Data outlier detection
Agency: Department of Justice - Department of Justice / FBI
Problem addressed: Validation of data given to FBI by checking for outliers
Purpose and benefits: Better data quality through targeted human review
Topic area: Law Enforcement
Development stage: Pre-deployment
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
US federal AI use case: Data Call Code Assist Tool
Agency: Department of Justice - Department of Justice / FBI
Problem addressed: Automating administrative tasks
Purpose and benefits: Increased efficiency and cost savings, and improved team productivity.
Topic area: Admin Functions
Development stage: Pilot
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
First used: 2025-10-01
US federal AI use case: Customer Service AI Agent/ChatBot
Agency: Department of Justice - Department of Justice / EOIR
Problem addressed: Members of the public visiting EOIR's website have trouble locating information on the website.
Purpose and benefits: Improving access to information on the EOIR website.
Topic area: Admin Functions
Development stage: Pre-deployment
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
US federal AI use case: Conduit AI
Agency: Department of Justice - Department of Justice / EOUSA
Problem addressed: Platform is meant to provide a generative AI that can be used for document review and other use cases as a comparison point to other commercially available alternatives.
Purpose and benefits: Increased efficiency, reduced costs, and improved customer experience through its conversational AI platform.
Topic area: Law Enforcement
Development stage: Pilot
Risk category: High-impact
First used: 2025-06-01
US federal AI use case: CoHost AI (Podcast hosting service feature)
Agency: Department of Justice - Department of Justice / FBOP
Problem addressed: Completing an entire production hosted and published.
Purpose and benefits: Completing an entire production hosted and published in a fraction of the time it would take to complete it manually.
Topic area: Admin Functions
Development stage: Deployed
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
First used: 2025-03-01
US federal AI use case: Code Development
Agency: Department of Justice - Department of Justice / Department wide
Problem addressed: More efficient writing and maintenance of code.
Purpose and benefits: Improve developer productivity and streamline development lifecycle.
Topic area: IT
Development stage: Deployed
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
First used: 2025-01-01
US federal AI use case: Cocounsel AI
Agency: Department of Justice - Department of Justice / EOUSA
Problem addressed: Platform is meant to provide a generative AI that can be used for document review and other use cases as a comparison point to other commercially available alternatives.
Purpose and benefits: Increases USAO efficiency through rapid analysis of legal documents, improves accuracy by reducing manual review errors, and assists offices that are not fully staffed by doing more routine tasks and allowing legal professionals to focus on strategic and high-value work
Topic area: Law Enforcement
Development stage: Pilot
Risk category: High-impact
First used: 2024-03-01
US federal AI use case: Claims Program Predictive Fraud Analytics
Agency: Department of Justice - Department of Justice / CIV
Problem addressed: Deploy advanced AI analytics to detect fraudulent claims and suspicious patterns in compensation claims programs, including the September 11th Victims Compensation Fund, Radiation Exposure Compensation Act, Camp LeJeune Justice Act, and other federal victim assistance programs. This initiative protects program integrity, ensures resources reach legitimate claimants, and maintains public trust in federal compensation systems. Aligns with Administration priorities on combating fraud, protecting taxpayer funds, and ensuring justice for claimants.
Purpose and benefits: (1) Strengthens the Civil Division's capabilities in administering victim compensation programs by identifying potentially fraudulent medical claims, duplicate submissions, and identity fraud.
(2) Builds upon existing Civil Division case management systems and medical claim review processes. Leverages ongoing fraud detection initiatives across DOJ components, integrates with established medical record verification systems, and utilizes existing partnerships with healthcare providers and medical review contractors. (3) Improvement in fraudulent claim detection rates, prevention of fraudulent payouts annually, reduction in false positive flags affecting legitimate claimants, faster claim processing times for verified submissions, and improved coordination metrics with investigative agencies on fraud referrals.
Topic area: Admin Functions
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Civil Rights Public Reporting Portal
Agency: Department of Justice - Department of Justice / CRT
Problem addressed: With limited staff, we use AI to summarize incoming public complaints to assist in determining if a complaint is actionable by our teams.
Purpose and benefits: Lower backlog and faster response to the public.
Topic area: Admin Functions
Development stage: Pre-deployment
Risk category: Presumed high-impact (determined not high)
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
US federal AI use case: Chatbot to Answer Internal Employee Policy Queries
Agency: Department of Justice - Department of Justice / DEA
Problem addressed: It is often challenging for DEA employees to manually search through our voluminous collection of manuals, books, CBP chemical codes, CFR, U.S.C., etc. to find an answer to their specific questions about policy, law, and rules. Training the AI on these materials enables it to answer employee queries comprehensively and quickly, thereby saving employees a lot of time.
Purpose and benefits: AI can provide comprehensiveness answers to employees' questions much more quickly than if the employees had to search and find the answers themselves. In addition, the AI can identify content that needs to be revised or added to effectively provide answers.
Topic area: Law Enforcement
Development stage: Pilot
Risk category: High-impact
First used: 2025-01-01
US federal AI use case: Chatbot
Agency: Department of Justice - Department of Justice / FBI
Problem addressed: General AI assistance
Purpose and benefits: Faster FBI operations
Topic area: Law Enforcement
Development stage: Pre-deployment
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
US federal AI use case: Case Management System Integration
Agency: Department of Justice - Department of Justice / TAX
Problem addressed: Leverage AI capabilities to support case management, such as creating codes for events in cases in order to track their progress and estimating time to completion to help managers evaluate the resource needs of the case.
Purpose and benefits: Reduced administrative overhead and leaner management structure
Topic area: Admin Functions
Development stage: Pre-deployment
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
US federal AI use case: Camtasia
Agency: Department of Justice - Department of Justice / USMS
Problem addressed: This allows USMS training content creators to generate on-screen presenters and realistic narration from text for global accessibility.
Purpose and benefits: Enhancing the learners online learning experience by improving accuracy of services, supporting 508 compliance and reduce production time to release of training materials to USMS employees.
Topic area: Admin Functions
Development stage: Pilot
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
First used: 2025-09-01
US federal AI use case: Business Intelligence Tools
Agency: Department of Justice - Department of Justice / Department wide
Problem addressed: Assists with data discovery and visualization.
Purpose and benefits: The embedded data analytic capabilities will increase the efficiency and effectiveness to locate and analyze data.
Topic area: IT
Development stage: Deployed
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
First used: 2022-01-01
US federal AI use case: Business Form Generation
Agency: Department of Justice - Department of Justice / FBI
Problem addressed: Manual time-intensive process
Purpose and benefits: Faster FBI operations
Topic area: Procurement and Finance Mgmt
Development stage: Pre-deployment
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
US federal AI use case: Bloomberg (AI Assisted Legal Research)
Agency: Department of Justice - Department of Justice / ATR
Problem addressed: Provides AI-assisted research to help streamline legal research and document review.
Purpose and benefits: Increases the speed at which attorneys can review and evaluate case law to determine if it is applicable to their current investigations.
Topic area: Law Enforcement
Development stage: Pre-deployment
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
US federal AI use case: Big Data Visualization Tools
Agency: Department of Justice - Department of Justice / TAX
Problem addressed: Improving analytics and support for document review
Purpose and benefits: Open-source tools that we believe could assist us with graphing relationships and other forms of data visualization.
Topic area: Law Enforcement
Development stage: Pre-deployment
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
US federal AI use case: Background Searches
Agency: Department of Justice - Department of Justice / EOIR
Problem addressed: To perform background searches to inform an EOIR character and fitness determination for individuals applying to be an EOIR accredited representative.
Purpose and benefits: Timely, comprehensive, and efficient background check. Character and fitness determinations made based on accurate background information. EOIR approves accreditation applicants with the requisite character and fitness. Individuals in EOIR immigration proceedings are assisted by accredited representatives with the requisite character and fitness.
Topic area: Admin Functions
Development stage: Deployed
Risk category: High-impact
First used: 2025-01-01
US federal AI use case: Azure AI Foundry Platform
Agency: Department of Justice - Department of Justice / EOUSA
Problem addressed: This AI solution is meant to provide chatbot responses in a secure enclave. In addition, this platform is meant to provide a generative AI that can be used for document review and other use cases as a comparison point to other commercially available alternatives.
Purpose and benefits: Decreased cost to operate AI compared to other commercially available solutions.
Topic area: Law Enforcement
Development stage: Pilot
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
First used: 2026-03-01
US federal AI use case: AWS Textract
Agency: Department of Justice - Department of Justice / USMS
Problem addressed: AWS Textract would be used to read the content off of certain PDF's sent into USMS by partner agencies.  It will prepopulate screens for the user to review against a mailed in PDF.
Purpose and benefits: Reduce processing time by not having to rekey in information off of text based  documents.
Topic area: Law Enforcement
Development stage: Pre-deployment
Risk category: Presumed high-impact (determined not high)
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
US federal AI use case: AWS Rekognition
Agency: Department of Justice - Department of Justice / USMS
Problem addressed: AWS Rekognition suite would be used to prevent the creation of duplicate records in the USMS Capture System. The application would index faces already in the Capture system then search new entries against the existing database to flag and help determine if a possible existing record exists for a new subject.
Purpose and benefits: The expected benefits to the agency would be higher data quality, lowered risk of duplicate FID creation, and faster intakes.
Topic area: Law Enforcement
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Audio Clarity Tool
Agency: Department of Justice - Department of Justice / FBI
Problem addressed: Audio clarity
Purpose and benefits: Higher quality data
Topic area: Law Enforcement
Development stage: Pre-deployment
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
US federal AI use case: Audio and Written Transcription and Translation
Agency: Department of Justice - Department of Justice / DEA
Problem addressed: This technology automates the transcription and translation of Spanish and Mandarin Chinese audio files from lawfully seized devices and authorized communications.
Purpose and benefits: The immediate benefits are speed and lower cost, and to enable investigators to quickly identify which parts of the conversations should be reviewed and interpreted by human translators.
Topic area: Law Enforcement
Development stage: Pilot
Risk category: High-impact
First used: 2024-01-01
US federal AI use case: Audiate
Agency: Department of Justice - Department of Justice / USMS
Problem addressed: This allows USMS training content creators to utilize text-to-speech generation with audio from a wide range of voices and tones without the need of additional actors.
Purpose and benefits: Enhancing the learners online learning experience by improving accuracy of services, supporting 508 compliance and reduce production time to release of training materials to USMS employees
Topic area: Admin Functions
Development stage: Pilot
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
First used: 2025-09-01
US federal AI use case: ATR Generative Artificial Intelligence Test
Agency: Department of Justice - Department of Justice / ATR
Problem addressed: Facilitate access to AI tools by ATR personnel.
Purpose and benefits: This initiative will enable ATR to embrace AI technology responsibly consistent with Presidential Action and various departmental guidance, allowing ATR personnel to optimize and modernize their work processes.
Topic area: Admin Functions
Development stage: Pilot
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
First used: 2025-06-01
US federal AI use case: ATR Expert/Consulting with Bates White
Agency: Department of Justice - Department of Justice / ATR
Problem addressed: The AI tool will ingest all the data sets and work to standardize them so that the Bates White expert and team can use the data to run economic models.
Purpose and benefits: Assist in preliminary data processing, including document summarization, name standardization, and text extraction. This includes “cleaning” the data for additional processing, performing the equivalent of a “find and replace” function to standardize names. The Bates White system may use AI to summarize the general content of documents.
Topic area: Law Enforcement
Development stage: Deployed
Risk category: Presumed high-impact (determined not high)
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
First used: 2024-12-01
US federal AI use case: AI-powered Legal Research
Agency: Department of Justice - Department of Justice / CIV
Problem addressed: DOJ attorneys spend significant time manually researching case law and regulatory precedents across jurisdictions, often missing obscure authorities or evolving standards. This initiative deploys an AI-powered legal research platform that synthesizes case law, flags conflicts or shifts in standards, and provides confidence scores for relevance, automatically updating as new decisions are published. Aligns with E.O. 14179’s innovation directive and M-25-21’s efficiency requirements.
Purpose and benefits: (1) Enhances DOJ's litigation effectiveness by ensuring comprehensive legal research, reducing research time per case, and improving argument quality through better precedent identification. Strengthens government's ability to defend federal programs and policies with more thorough legal foundations. (2)  Builds on existing Westlaw/Lexis subscriptions, DOJ brief bank, and PACER databases. Integrates with current legal research workflows and citation management systems. (3) Reduction in research hours per brief; increase in relevant precedents cited; improved appellate success rates; measurable improvement in legal argument comprehensiveness.
Topic area: Admin Functions
Development stage: Pre-deployment
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
US federal AI use case: AI-generated Content Detector
Agency: Department of Justice - Department of Justice / CIV
Problem addressed: Federal litigators face increasing challenges with AI-manipulated evidence and documents from opposing parties. An AI tool could be used to flag potentially AI-generated content.
Purpose and benefits: (1) Enhanced litigation integrity by identifying potentially manipulated evidence, protecting court proceedings from AI-generated misinformation and ensuring compliance with local court rules.
(2) Builds on existing document review platforms and federal privilege protection protocols.
(3) Improved evidence verification accuracy; reduced risk of submitting hallucinated data; enhanced compliance with AI disclosure requirements; increased attorney confidence in document authenticity.
Topic area: Law Enforcement
Development stage: Pre-deployment
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
US federal AI use case: AI-Enabled Workflow Automation
Agency: Department of Justice - Department of Justice / CIV
Problem addressed: Office of Immigration Litigation (OIL) faces significant backlogs, with repetitive or frivolous claims slowing progress and foreign-language evidence creating bottlenecks. This initiative uses Natural Language Processing for triage and automate translation to accelerate case processing. It aligns with M-25-21’s innovation and governance principles by improving efficiency while preserving human oversight.
Purpose and benefits: (1) Reduces immigration case backlogs, ensures consistent treatment of claims, and improves responsiveness to federal courts.
(2) Builds on OIL case management systems, United States Citizenship and Immigration Services data feeds, and DOJ translation contract costs.(3) Reduced backlog size; fewer attorney hours per case; translation accuracy benchmarks met. Increase in fraudulent/frivolous and repetitive claims.
Topic area: Law Enforcement
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: AI-enabled Legal Argument Harmonization
Agency: Department of Justice - Department of Justice / CIV
Problem addressed: Conflicting arguments across DOJ branches can weaken credibility in appellate courts. This initiative deploys AI to mine arguments across briefs, harmonize DOJ positions, and validate citations. It advances M-25-21’s governance requirement for consistent positions and E.O. 14179’s push for efficiency.
Purpose and benefits: (1) Enhances DOJ credibility before the court; avoids conflicting arguments. (2) Uses DOJ appellate brief bank and legal research/citation tools.                                                                                                                                (3) Reduction in conflicting arguments; % of briefs citation-validated; improved appellate outcomes.
Topic area: Law Enforcement
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: AI-enabled Compliance Verification
Agency: Department of Justice - Department of Justice / CIV
Problem addressed: Federal agencies and recipients of federal funding must certify compliance with various civil rights statutes, but DOJ lacks efficient methods to verify the accuracy of these certifications. Manual review of compliance documentation is resource-intensive and often occurs only after complaints are filed, allowing violations to persist and potentially expand. False certifications can result in continued federal funding to non-compliant entities, undermining civil rights enforcement and wasting taxpayer resources. Aligns with E.O. 14179's innovation requirements and M-25-21's public trust and governance pillars.
Purpose and benefits: (1) Strengthens DOJ's ability to enforce civil rights laws through the False Claims Act by identifying clear-cut compliance violations earlier in the process. Protects taxpayer funds from flowing to entities that falsely certify compliance while ensuring federal programs achieve their intended civil rights objectives (2) Leverages FCA compliance databases, Civil Rights Division patterns, and initial whistleblower submission channels. (3) Focus on objective, verifiable metrics such as statistical disparities in outcomes, missing required documentation, or contradictions between certifications and published policies. Number of suspicious certifications flagged; investigations initiated; successful FCA settlements or recoveries.
Topic area: Law Enforcement
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: AI-Enabled Briefing Assistant
Agency: Department of Justice - Department of Justice / CIV
Problem addressed: Federal Programs Branch (FPB) attorneys face overwhelming records and pressure to maintain consistent arguments across circuits. FPB faces immense workloads defending statutes and federal programs, often requiring rapid analysis of massive records and consistent legal arguments across circuits. This initiative will deploy a retrieval-augmented generation (RAG) tool trained on DOJ filings and administrative records to accelerate drafting and ensure consistency. It directly aligns with E.O. 14179 (removing barriers to AI adoption) and OMB M-25-21 (innovation, governance, and public trust).
Purpose and benefits: (1) This initiative strengthens the federal government’s ability to protect statutory authority and defend policy actions across all agencies.                                                                                                                    (2) Reduction in attorney hours per brief; mitigation of hallucinated citations; measurable improvement in argument consistency across cases.                                                                                                                                                                                                                                              (3) Builds on DOJ’s existing “brief bank,” eDiscovery platforms, and PACER data archives.
Topic area: Law Enforcement
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: AI-driven Fraud Detection
Agency: Department of Justice - Department of Justice / CIV
Problem addressed: Fraud diverts billions in taxpayer funds but manual review of records is too slow to catch early misconduct. Fraud cases involve sifting through vast amounts of structured and unstructured data, often too large for manual review to detect early fraud signals. This initiative will apply AI-enabled anomaly detection to efficiently synthesize insights from vast data collections and uncover fraudulent patterns. It aligns with M-25-21’s public trust priority by safeguarding taxpayer funds and E.O. 14179’s innovation directive.
Purpose and benefits: (1) Bolsters DOJ’s mission to prevent waste, fraud, and abuse in taxpayer-funded health programs, strengthening enforcement under the FCA.                                                                                                                                                                                                                                         (2) Builds on existing Medicare/Medicaid data feeds, OIG case frameworks, previous FCA healthcare enforcement analytics, and ongoing interagency fraud task force initiatives.(3) Increase in early identification of false claims; recovery dollars secured; reduced investigation timelines.
Topic area: Law Enforcement
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: AI-assisted Settlement Data and Risk Analysis
Agency: Department of Justice - Department of Justice / CIV
Problem addressed: Settlements require knowledge of both valuation and risk for frequent types of litigation. An AI tool could pull both structured data from settlement databases, together with unstructured settlement memoranda, and analyze settlement risk, valuation, and qualitative factors. Users can use natural language to query one or both sources of data.
Purpose and benefits: (1) Improved settlement decision-making through comprehensive risk and valuation analysis, leading to more favorable outcomes for the government and taxpayers.
(2) Builds on existing Salesforce migration initiatives and settlement databases while adding natural language query capabilities.
(3) Reduced attorney time per settlement analysis; improved consistency in settlement valuations; better risk assessment accuracy; enhanced ability to identify settlement patterns and trends.
Topic area: Law Enforcement
Development stage: Pre-deployment
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
US federal AI use case: AI-assisted Legacy Code Modernization
Agency: Department of Justice - Department of Justice / CIV
Problem addressed: This initiative uses AI-assisted code translation and refactoring tools to automatically convert legacy code into modern, secure languages (e.g., Java, Python) while flagging logic gaps and optimizing for cloud environments. Aligns with E.O. 14179’s innovation directive and M-25-21’s governance requirements.
Purpose and benefits: (1) Modernized applications improve resilience, reduce security risk, and lower long-term IT O&M costs, directly supporting DOJ’s modernization and cybersecurity priorities. (2) Builds on DOJ CIO modernization roadmaps, Federal IT dashboards, and prior migration initiatives to cloud platforms.
(3) Reduction in legacy system maintenance costs, outages and performance loss; # of applications successfully migrated; cybersecurity vulnerabilities reduced.
Topic area: IT
Development stage: Pre-deployment
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
US federal AI use case: AI Sandbox for exploration and education on AI
Agency: Department of Justice - Department of Justice / OJP
Problem addressed: Help identify enhancement in mission capabilities
Explore Risk management
Help identify AI Use cases with OJP 
Educate AI enable workforce
Purpose and benefits: Enhance OJP workforce to work faster 
Reduce number of software that AI can achieve
Improving access to data
Topic area: IT
Development stage: Pre-deployment
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
US federal AI use case: AI Powered Data Governance
Agency: Department of Justice - Department of Justice / CIV
Problem addressed: This initiative deploys AI-driven data governance and metadata management to auto-tag, catalog, and enforce retention, while identifying duplicate/low-value files. Aligns with M-25-21 governance & E.O. 14179 innovation.
Purpose and benefits: (1) Reduces costs, improves compliance with records management/FOIA, and data governance. Boosts transparency by making DOJ data discoverable and reusable. (2) DOJ records systems, NARA retention schedules, existing FOIA/eDiscovery platforms.                                                                                       (3) Measurable data storage savings; % of files tagged with metadata; improved FOIA response times.
Topic area: IT
Development stage: Pre-deployment
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
US federal AI use case: AI Personal Assistant
Agency: Department of Justice - Department of Justice / CIV
Problem addressed: Complex litigation requires intensive time and project management.  AI assistants can analyze calendars, emails, case-tracking sheets, and schedules. It can flag deadlines, note high-priority tasks, and suggest productivity techniques for managing complex projects. Attorneys could create additional notifications or project management integrations to improve efficiency.
Purpose and benefits: (1) Improved attorney productivity and case management efficiency, enabling better service delivery to client agencies and more effective litigation outcomes.
(2) Builds on existing calendar systems, email platforms, and case-tracking databases while maintaining attorney-client privilege protections.
(3) Reduced missed deadlines; improved task prioritization; enhanced productivity metrics; better work-life balance for attorneys; increased case management efficiency.
Topic area: Admin Functions
Development stage: Pre-deployment
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
US federal AI use case: AI Meeting Assistant
Agency: Department of Justice - Department of Justice / CIV
Problem addressed: This initiative deploys AI-enabled meeting assistants that provide real-time transcription, generate concise summaries, identify action items, and tag outcomes to case files. Aligns with E.O. 14179’s innovation goals and M-25-21’s efficiency and transparency pillars.
Purpose and benefits: (1) Increases productivity by ensuring institutional knowledge is captured, searchable, and integrated into case management systems, reducing duplication and oversight risks.  (2) Integrates with Microsoft Teams, Outlook, OneNote, and other knowledge management systems.                                                                          (3) Increase proficiency in % of meetings transcribed and summarized; attorney time saved; # of action items captured and completed.
Topic area: Admin Functions
Development stage: Pre-deployment
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
US federal AI use case: Mass Claim Tool
Agency: Department of Justice - Department of Justice / CIV
Problem addressed: Components with mass claims, such as RECA must respond to tens of thousands of similar claims within statutorily defined timelines, or the U.S. forfeits its defenses. Tools to quickly process mass claims, including template letter generation, claim categorization, and automated data entry of standardized filings could meet urgent needs.
Purpose and benefits: (1) Ensures statutory compliance for mass claims processing, protecting the government's legal defenses while providing timely relief to eligible claimants.
(2) Builds on existing RECA program infrastructure and mass claims databases while incorporating specialized medical data handling and privilege protections.
(3) Achievement of statutory processing deadlines; reduced attorney hours per claim; improved consistency in claim categorization; automated template generation; enhanced quality control processes; increased claimant satisfaction through faster processing.
Topic area: Law Enforcement
Development stage: Pre-deployment
Impact assessment: Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
US federal AI use case: AI Evidence and Claim Consolidation
Agency: Department of Justice - Department of Justice / CIV
Problem addressed: This initiative applies AI to synthesize records, summarize expert reports and depositions, and identify duplicate claims. It also uses AI to identify inconsistencies between records and plaintiff claims, identify red flag legal issues, and create templates to respond to frequent or high-volume litigation. It also allows for analysis of settlement and damages databases to identify outlier trends. It supports M-25-21’s public trust pillar and E.O. 14179’s innovation agenda.
Purpose and benefits: 1) Improves the government’s litigation posture in high-value torts, reduces exposure to excessive payouts, and ensures equitable and efficient claims processing.(2) Builds on DOJ medical record review systems and HHS/VA data integration, along with Relativity/CORA settlement, damages, and entitlement databases.                                                                                                                                                                                                                    (3) Faster evidence review; detection and elimination of duplicate claims; creating more effective and consistent settlements; increased dismissal or settlement of weak claims; attorney time saved.
Topic area: Law Enforcement
Development stage: Pre-deployment
Risk category: High-impact