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

Federal AI at a glance

5 agencies · 10 reported use cases · OMB 2025 Inventory. Portfolio size reflects reporting, not performance.

Agency
Stage
High-impact1
Topic
AI type
Sourcing
Vendor
No options match.
Function1
Start year

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

Function: Fraud, waste and improper paymentsHigh-impact: High-impact
10 Reported AI use cases5 agencies6 Deployed0 Pilots10 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
DOJ4DHS3
In development/acquisition4Deployed6Largest portfolio: 4 · 5 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

10% generative or agentic. Each record carries one classification; not reported is shown hatched.

Mission areas

Topic area as reported

Lifecycle composition

10 records
Explore lifecycle stages and impact
Within each stageHigh-impact · Gen./agentic
Pre-deployment100%0%
Deployed100%17%

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, HHS report 8 of 10 use cases (80%).

Understand the methodology →

Evolution of reported AI use cases

By agency-reported start year · click a year to filter
0<15'15'16'17'18'19'20'21'22'23'242'25'26
Generative or agenticOther or unclassified5 of 10 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 60% of records

Each square is 1% of filtered records. Where reported, 67% involve in-house development.

High-impact AI

Agency self-designation under M-25-21Governance view
10records
Minimum practices · 10 high-impactin place
Pre-deployment testing30%
AI impact assessment30%
Independent review30%
Ongoing monitoring30%
Operator training30%
Fail-safe30%
Appeal process10%
User and public consultation30%
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. 50% of high-impact records answer any practice question.

Analytical observations

Computed from the current filter; reproducible
  • FindingDOJ, DHS, HHS report 8 of 10 use cases (80%).
  • Finding17% of reported deployed use cases (1 of 6) are classified as generative or agentic AI. View records
  • FindingOf 6 deployed high-impact use cases, 3 report a completed AI impact assessment and 1 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 60% of use cases. Where reported, 67% involve in-house development.
AI classification reported100%
Stage not reported0
Sourcing reported60%