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

Federal AI at a glance

11 agencies · 132 reported use cases · OMB 2025 Inventory. Portfolio size reflects reporting, not performance.

Agency
Stage
High-impact1
Topic
AI type1
Sourcing
Vendor
Function
Start year

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

AI type: Classical / predictive MLHigh-impact: High-impact
132 Reported AI use cases11 agencies86 Deployed6 Pilots132 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
VA52DOJ41
In development/acquisition40Pilot6Deployed86Largest portfolio: 52 · 11 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

132 records
Explore lifecycle stages and impact
Within each stageHigh-impact · Gen./agentic
Pre-deployment100%0%
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, DOJ, DHS report 106 of 132 use cases (80%).

Understand the methodology →

Evolution of reported AI use cases

By agency-reported start year · click a year to filter
051015<15'15'16'17'18'19'20'21'22'2318'24'25'26
Generative or agenticOther or unclassified61 of 132 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 67% of records

Each square is 1% of filtered records. Where reported, 44% involve in-house development.

High-impact AI

Agency self-designation under M-25-21Governance view
132records
Minimum practices · 132 high-impactin place
Pre-deployment testing14%
AI impact assessment12%
Independent review12%
Ongoing monitoring14%
Operator training14%
Fail-safe12%
Appeal process5%
User and public consultation5%
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. 39% of high-impact records answer any practice question.

Analytical observations

Computed from the current filter; reproducible
  • FindingVA, DOJ, DHS report 106 of 132 use cases (80%).
  • Finding0% of reported deployed use cases (0 of 86) are classified as generative or agentic AI. View records
  • FindingOf 86 deployed high-impact use cases, 16 report a completed AI impact assessment and 34 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 67% of use cases. Where reported, 44% involve in-house development.
AI classification reported100%
Stage not reported0
Sourcing reported67%