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

Custom inventory report

Filter: agency = DOL; AI type = unknown; sourcing = unknown

Generated 2026-10-12 13:33 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 = DOL; AI type = unknown; sourcing = unknown · 11 records

Key findings

  • 11 use-case records from 1 agencies: 0 deployed (0%), 0 pilots, 0 in development or acquisition, 11 retired, 0 with no stage reported.
  • 0 records are designated high-impact; 0 of them (n/a) answered at least one minimum-practice question.
  • Sourcing is reported for 0% of use cases. Where reported, n/a involve in-house development.

Lifecycle

StageRecordsShare
Retired11100%

AI technology

ClassificationRecordsShareDeployed
Not reported11100%0

Agencies

AgencyRecordsDeployedHigh-impactCompleteness
DOL · Department of Labor110017%

High-impact designation

DesignationRecords
Not high-impact11

Governance evidence: use cases designated high-impact

PracticeIn placeIn progressNot in placeN/A or precludedOtherNo answerIn scope
Pre-deployment testing0000000
AI impact assessment0000000
Independent review0000000
Ongoing monitoring0000000
Operator training0000000
Fail-safe0000000
Appeal process0000000
User and public consultation0000000

"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 11 records.

RecordAgency IDAgencyUse caseStage
R1273DOL-1-CDOLDetermine Occupation Codes from Text (NIOCCS)Retired
R1277DOL-05DOLClaims Document ProcessingRetired
R1278DOL-06DOLWebsite Chatbot AssistantRetired
R1280DOL-10DOLOfficial Document ValidationRetired
R1284DOL-14DOLAutomatic Data Processing Workflow with Form Recognizer (9130/9178 Reconciliation Project)Retired
R1286DOL-16DOLOccupation Code Suggestion For Job Duties DataRetired
R1287DOL-17DOLNotice of Deficiency (NOD) Text Generation using Generative AI modelRetired
R1288DOL-18DOLCase Recording summarizationRetired
R1294DOL-24DOLInitial Determinations for incoming applicationsRetired
R1295DOL-26DOLWeb Scraping to Identify Potentially Fraudulent Multiple Employer Welfare Arrangements (MEWAs)Retired
R1299DOL-30DOLOIICS CodingRetired

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