Federal AI Intelligence
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Snapshot · OMB 2025 inventory · processed Oct 11, 2026
Federal AI landscape

Federal AI at a glance

4 agencies · 9 reported use cases · OMB 2025 Inventory. Portfolio size reflects reporting, not performance.

Executive briefing ↗Explore 9 use cases →
Agency
Stage
High-impact1
Topic
AI type1
Sourcing1
Vendor
Function
Start year

Only records with a parseable start date match a year filter.

AI type: Natural language processingHigh-impact: High-impactSourcing: Contract and in-house
9 Reported AI use cases4 agencies8 Deployed1 Pilots9 Designated high-impact
Decorative federal AI network visualization; not a representation of agency deployment locations or relationships.
Scale & composition

Agencies behind federal AI

Select an agency to explore
Ring shows composition · node area shows use cases
DOJ3DHS3VA2DOL1
Pilot1Deployed8Largest portfolio: 3 · 4 agencies

Conceptual agency landscape · positions do not represent deployment locations. Proximity does not imply a relationship.

AI technology mix

Reported classification · click to cross-filter

0% generative or agentic. Each record carries one classification; not reported is shown hatched.

Mission areas

Topic area as reported

Lifecycle composition

9 records
Explore lifecycle stages and impact
Within each stageHigh-impact · Gen./agentic
Pilot100%0%
Deployed100%0%

Impact and technology shares use each stage's records as the denominator.

From development and acquisition to retirement. Select a stage to explore its reported use cases.

Reading the inventory

Evidence, with its limits visible

DOJ, DHS, VA report 8 of 9 use cases (89%).

Understand the methodology →

Evolution of reported AI use cases

By agency-reported start year · click a year to filter
0<15'15'16'17'18'19'20'21'22'233'24'25'26
Generative or agenticOther or unclassified7 of 9 records report a parseable start date

Start dates are agency-reported operational or pilot dates, not inventory submission dates. 2026 values are planned or early-year. Undated records are excluded from this chart only.

Sourcing

Reported for 100% of records

Each square is 1% of filtered records. Where reported, 100% involve in-house development.

High-impact AI

Agency self-designation under M-25-21Governance view
9records
Minimum practices · 9 high-impactin place
Pre-deployment testing44%
AI impact assessment22%
Independent review22%
Ongoing monitoring22%
Operator training22%
Fail-safe11%
Appeal process22%
User and public consultation22%
Reported in placeReported in progressNot applicableOther or ambiguous answerNo answer reported

High-impact is the agency's own classification, not an independent risk rating. No answer reported is missing evidence, not evidence that a practice is absent. 67% of high-impact records answer any practice question.

Analytical observations

Computed from the current filter; reproducible
  • FindingDOJ, DHS, VA report 8 of 9 use cases (89%).
  • Finding0% of reported deployed use cases (0 of 8) are classified as generative or agentic AI. View records
  • FindingOf 8 deployed high-impact use cases, 2 report a completed AI impact assessment and 2 leave every minimum-practice field blank. View records
  • InterpretationBlank practice fields are missing evidence, not evidence that a safeguard is absent. They mark where follow-up questions to the agency are most useful.
  • FindingSourcing is reported for 100% of use cases. Where reported, 100% involve in-house development.
AI classification reported100%
Stage not reported0
Sourcing reported100%