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Snapshot · OMB 2025 inventory · processed Oct 11, 2026
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Federal AI Intelligence · U.S. Government AI Observatory

Governance disclosure assessment

Filtered: function = document_processing

Generated 2026-10-12 03:51 UTCDataset: 2025 Federal Agency AI Use Case Inventory (individually reported use cases), Office of Management and Budget (OMB). Version 2025-inventory@62d5baa65fa3, processed 2026-10-11, rules 2026.10.1. Static snapshot.Applied filters: function = document_processing · 131 records

Key findings

  • 131 use-case records from 21 agencies: 59 deployed (45%), 20 pilots, 46 in development or acquisition, 6 retired, 0 with no stage reported.
  • 19 records are designated high-impact; 8 of them (42%) answered at least one minimum-practice question.
  • HHS, DOJ, VA report 69 of 131 use cases (53%).
  • 22% of reported deployed use cases (13 of 59) are classified as generative or agentic AI.
  • Of 11 deployed high-impact use cases, 0 report a completed AI impact assessment and 3 leave every minimum-practice field blank.
  • Interpretation: Blank practice fields are missing evidence, not evidence that a safeguard is absent. They mark where follow-up questions to the agency are most useful.
  • Sourcing is reported for 62% of use cases. Where reported, 68% involve in-house development.

Governance evidence: deployed high-impact use cases

PracticeIn placeIn progressNot in placeN/A or precludedOtherNo answerIn scope
Pre-deployment testing08000311
AI impact assessment08000311
Independent review08000311
Ongoing monitoring08000311
Operator training06002311
Fail-safe08000311
Appeal process08000311
User and public consultation08000311

"In place" means the agency reported the practice as established. "No answer" means the field was blank; it says nothing about whether the practice exists.

Agencies with high-impact records

AgencyHigh-impactAnswered any practicePractice answers in place
DOJ960 of 72
VA800 of 64
DHS220 of 16

Method

All figures are computed directly from the normalised inventory records. Category labels are normalised from the source answer options; original values are kept on each record. Governance answers are classified as in place, in progress, not in place, not applicable, precluded, waived, other or no answer, and blanks are never read as "no". See the Methodology page for full rules.

Limitations

  • Figures are what agencies reported in the 2025 inventory. They are not verified, and registration of use cases is not complete for every agency.
  • A blank answer is missing evidence, not evidence that a practice or safeguard is absent.
  • Counts are use-case records. A larger portfolio does not indicate better performance or greater AI maturity, and agencies differ in how they split systems into use cases.
  • The inventory has no budget, cost, accuracy or outcome data. None is shown or inferred here.
  • This is a disclosure analysis. It is not an audit, a compliance determination or an official government assessment.

Source records

First 40 of 131 records, deployed first. The full list is available as CSV from the explorer with the same filters.

RecordAgency IDAgencyUse caseStage
R0026SEC-33SECOptical Character Recognition (OCR) for Records AnalysisDeployed
R0033SEC-40SECExtracting data from FOIA request formsDeployed
R0118NASA-26NASANextGen Data Analytics: Letters of AgreementDeployed
R0559FRB-0003FRBPDF Optical Character Recognition (Text)Deployed
R0600HHSStructuring Notice of Concern DataDeployed
R0617HHSDocument Review for Alignment with Executive Orders: Position DescriptionsDeployed
R0618HHSDocument Review for Alignment with Executive Orders: Grant MaterialsDeployed
R0619HHSGrant management support: structuring information in applicationsDeployed
R0669HHSCDC ChatbotDeployed
R0821HHSQuality Surveillance Dashboard (QSD)Deployed
R0822HHSAnnual Report CMCDeployed
R0823HHSRenamed: Application References Previously: Application-DMF ReferenceDeployed
R0824HHSRenamed: Extracting DMF Facilities from unstructured documents Previously: DMF (Drug Master File) FacilitiesDeployed
R0825HHSRenamed: Information Visualization Platform (InfoViP) to Support Analysis of FAERS safety reports Previously: Information Visualization Platform (InfoViP) to Support Analysis of adverse event reportsDeployed
R0827HHSRenamed: Module 3 Facilities Extraction Previously: Module 3 FacultiesDeployed
R0828HHSPackaging Materials and SuppliersDeployed
R0830HHSReal World Data/EvidenceDeployed
R0831HHSRegulatory Starting MaterialDeployed
R0841HHSCategory Subcategory Classification - Safety Reports BotDeployed
R0842HHSData Extraction from IND Safety Reports using OCR/AI TechnologiesDeployed
R0876HHSMachine Learning as a Service: Translate and extract text from images using AIDeployed
R0877HHSMachine Learning as a Service: Extract data from product labels, business forms, and image filesDeployed
R0912HHSDAIT AIDS-Related Research SolutionDeployed
R0927HHSNCI-DOE Collaboration, MOSSAIC project (Modeling Outcomes using Surveillance Data and Scalable AI for Cancer)Deployed
R0945HHSTB Case Browser Image Text DetectionDeployed
R1283DOL-13DOLAutomatic Document ProcessingDeployed
R1337USDA-033USDAAutomated PDF Document Processing and Information ExtractionDeployed
R1349USDA-048USDADam Inspection Report Document ProcessingDeployed
R1476DOJ-0001DOJAdobe Suite ApplicationsDeployed
R1478DOJ-0003DOJUnmanned Aerial Systems (UAS)Deployed
R1518DOJ-0048DOJThomson Reuters CLEAR - License Plate RecognitionDeployed
R1571DOJ-0123DOJOCR and TranslationDeployed
R1586DOJ-0138DOJLanguage Translation, Optical Character Recognition (OCR), Object Detection, Language Detection, Alert Noise ReductionDeployed
R1588DOJ-0143DOJAutomated Medication Dispensing CabinetDeployed
R1635DOJ-0198DOJNlets Nationwide License Plate Reader Pointer IndexDeployed
R1700DOJ-0275DOJOptical Character Recognition Tool 2Deployed
R1720DOJ-0295DOJFOIA Production ToolsDeployed
R1721DOJ-0296DOJFingerprint (Friction Ridge) Optical Character Recognition (OCR)Deployed
R1911DHS-2577DHSMobile FortifyDeployed
R1912DHS-2666DHSLicense Plate Capture and AnalysisDeployed

Prepared with Federal AI Intelligence by Irakli Petriashvili. Source: https://github.com/ombegov/2025-Federal-Agency-AI-Use-Case-Inventory