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

Executive briefing ↗Explore 5 use cases →
Agency
Stage1
High-impact
Topic
AI type1
Sourcing
Vendor
Function
Start year

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

AI type: Natural language processingfailsafe: not_applicableStage: Deployed
5 Reported AI use cases4 agencies5 Deployed0 Pilots3 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
DHS2DOL1DOI1DOE1
Deployed5Largest portfolio: 2 · 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

5 records
Explore lifecycle stages and impact
Within each stageHigh-impact · Gen./agentic
Deployed60%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

DHS, DOL, DOI report 4 of 5 use cases (80%).

Understand the methodology →

Evolution of reported AI use cases

By agency-reported start year · click a year to filter
0<15'15'16'17'18'19'20'21'22'23'243'25'26
Generative or agenticOther or unclassified5 of 5 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, 60% involve in-house development.

High-impact AI

Agency self-designation under M-25-21Governance view
5records
Minimum practices · 3 high-impactin place
Pre-deployment testing67%
AI impact assessment33%
Independent review33%
Ongoing monitoring33%
Operator training33%
Fail-safe0%
Appeal process67%
User and public consultation33%
Reported in placeReported in progressNot applicableOther or ambiguous answer

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. 100% of high-impact records answer any practice question.

Analytical observations

Computed from the current filter; reproducible
  • FindingDHS, DOL, DOI report 4 of 5 use cases (80%).
  • Finding0% of reported deployed use cases (0 of 5) are classified as generative or agentic AI. View records
  • FindingOf 3 deployed high-impact use cases, 1 report a completed AI impact assessment and 0 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, 60% involve in-house development.
AI classification reported100%
Stage not reported0
Sourcing reported100%