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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: AI type = classical_ml; function = document_processing

Generated 2026-10-12 19:23 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: AI type = classical_ml; function = document_processing · 24 records

Key findings

  • 24 use-case records from 8 agencies: 12 deployed (50%), 3 pilots, 9 in development or acquisition, 0 retired, 0 with no stage reported.
  • 3 records are designated high-impact; 2 of them (67%) answered at least one minimum-practice question.
  • DOJ, HHS, FRB report 17 of 24 use cases (71%).
  • 0% of reported deployed use cases (0 of 12) are classified as generative or agentic AI.
  • Of 2 deployed high-impact use cases, 0 report a completed AI impact assessment and 0 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 63% of use cases. Where reported, 60% involve in-house development.

Governance evidence: all use cases in the current filter

PracticeIn placeIn progressNot in placeN/A or precludedOtherNo answerIn scope
Pre-deployment testing020002224
AI impact assessment020002224
Independent review020002224
Ongoing monitoring020002224
Operator training020002224
Fail-safe020002224
Appeal process020002224
User and public consultation020002224

"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
DOJ220 of 16
VA100 of 8

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

All 24 records.

RecordAgency IDAgencyUse caseStage
R0559FRB-0003FRBPDF Optical Character Recognition (Text)Deployed
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
R1476DOJ-0001DOJAdobe Suite ApplicationsDeployed
R1588DOJ-0143DOJAutomated Medication Dispensing CabinetDeployed
R1720DOJ-0295DOJFOIA Production ToolsDeployed
R1721DOJ-0296DOJFingerprint (Friction Ridge) Optical Character Recognition (OCR)Deployed
R1959DHS-399DHSCyber Threat Analysis (Recorded Future)Deployed
R1990DHS-16DHSELIS Evidence Classifier ServiceDeployed
R203235EPAMicrosoft Power Automate (custom document processing model)Deployed
R2330VA-25-733VAAuto Doc IDDeployed
R0446NASA-841NASANeural Posterior Estimation for X-ray reflection spectroscopy: Training on complex physical models and AGN Observation-Driven Parameter Grids.Pre-deployment
R0560FRB-0004FRBPDF Optical Character Recognition (Images)Pre-deployment
R0723HHSBeryllium exposure reconstructionPre-deployment
R0868HHSData Ingestion and Content Explorer (DICE)Pilot
R1462USDA-164USDAAlisha OCR ReaderPilot
R1538DOJ-0073DOJData & Analytics: Transportation OCRPre-deployment
R1698DOJ-0273DOJOptical Character Recognition Tool 3Pilot
R1726DOJ-0301DOJEnabling eDiscovery Platform AIPre-deployment
R1728DOJ-0303DOJDocument ProcessingPre-deployment
R1748DOJ-0323DOJBig Data Visualization ToolsPre-deployment
R1751DOJ-0326DOJAWS TextractPre-deployment
R2070VA-25-2455VALexis+Pre-deployment

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