Federal AI Intelligence
Menu
Snapshot · OMB 2025 inventory · processed Oct 11, 2026
← All report templates
Federal AI Intelligence · U.S. Government AI Observatory

Federal AI landscape: executive briefing

Filtered: agency = DOJ; AI type = classical_ml; sourcing = both

Generated 2026-10-12 17:18 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: agency = DOJ; AI type = classical_ml; sourcing = both · 8 records

Key findings

  • 8 use-case records from 1 agencies: 6 deployed (75%), 2 pilots, 0 in development or acquisition, 0 retired, 0 with no stage reported.
  • 2 records are designated high-impact; 1 of them (50%) answered at least one minimum-practice question.
  • 0% of reported deployed use cases (0 of 6) are classified as generative or agentic AI.
  • Of 1 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 100% of use cases. Where reported, 100% involve in-house development.

Lifecycle

StageRecordsShare
Deployed675%
Pilot225%

AI technology

ClassificationRecordsShareDeployed
Classical / predictive ML8100%6

Agencies

AgencyRecordsDeployedHigh-impactCompleteness
DOJ · Department of Justice862100%

High-impact designation

DesignationRecords
High-impact2
Not high-impact6

Governance evidence: use cases designated high-impact

PracticeIn placeIn progressNot in placeN/A or precludedOtherNo answerIn scope
Pre-deployment testing0100012
AI impact assessment0100012
Independent review0100012
Ongoing monitoring0100012
Operator training0100012
Fail-safe0100012
Appeal process0100012
User and public consultation0100012

"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.

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 8 records.

RecordAgency IDAgencyUse caseStage
R1481DOJ-0006DOJAzure Data FactoryDeployed
R1482DOJ-0007DOJAzure Zen 2 StorageDeployed
R1539DOJ-0081DOJData & Analytics: Chemistry Instrument LibraryDeployed
R1584DOJ-0136DOJTIPSDeployed
R1656DOJ-0228DOJJMIS: Route OptimizerDeployed
R1721DOJ-0296DOJFingerprint (Friction Ridge) Optical Character Recognition (OCR)Deployed
R1688DOJ-0263DOJRedaction Tool 1Pilot
R1754DOJ-0329DOJAudio and Written Transcription and TranslationPilot

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