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

Federal AI at a glance

6 agencies · 24 reported use cases · OMB 2025 Inventory. Portfolio size reflects reporting, not performance.

Agency
Stage
High-impact1
Topic
AI type1
Sourcing1
Vendor
No options match.
Function
Start year

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

AI type: Classical / predictive MLHigh-impact: High-impactSourcing: Developed in-house
24 Reported AI use cases6 agencies21 Deployed3 Pilots24 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
VA10DHS5SSA5
Pilot3Deployed21Largest portfolio: 10 · 6 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

24 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

VA, DHS, SSA report 20 of 24 use cases (83%).

Understand the methodology →

Evolution of reported AI use cases

By agency-reported start year · click a year to filter
056<15'15'16'17'18'19'20'21'22'23'24'25'26
Generative or agenticOther or unclassified14 of 24 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
24records
Minimum practices · 24 high-impactin place
Pre-deployment testing42%
AI impact assessment42%
Independent review42%
Ongoing monitoring42%
Operator training42%
Fail-safe33%
Appeal process8%
User and public consultation4%
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. 46% of high-impact records answer any practice question.

Analytical observations

Computed from the current filter; reproducible
  • FindingVA, DHS, SSA report 20 of 24 use cases (83%).
  • Finding0% of reported deployed use cases (0 of 21) are classified as generative or agentic AI. View records
  • FindingOf 21 deployed high-impact use cases, 10 report a completed AI impact assessment and 10 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%