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

Federal AI at a glance

5 agencies · 28 reported use cases · OMB 2025 Inventory. Portfolio size reflects reporting, not performance.

Executive briefing ↗Explore 28 use cases →
Agency
Stage1
High-impact
Topic
AI type
Sourcing
Vendor
Function
Start year

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

feedback: otherStage: Deployed
28 Reported AI use cases5 agencies28 Deployed0 Pilots23 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
DHS13DOE7SSA6
Deployed28Largest portfolio: 13 · 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

11% generative or agentic. Each record carries one classification; not reported is shown hatched.

Mission areas

Topic area as reported

Lifecycle composition

28 records
Explore lifecycle stages and impact
Within each stageHigh-impact · Gen./agentic
Deployed82%11%

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, DOE, SSA report 26 of 28 use cases (93%).

Understand the methodology →

Evolution of reported AI use cases

By agency-reported start year · click a year to filter
05<15'15'16'17'18'19'20'21'22'238'24'25'26
Generative or agenticOther or unclassified28 of 28 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, 54% involve in-house development.

High-impact AI

Agency self-designation under M-25-21Governance view
28records
Minimum practices · 23 high-impactin place
Pre-deployment testing91%
AI impact assessment83%
Independent review83%
Ongoing monitoring78%
Operator training83%
Fail-safe61%
Appeal process30%
User and public consultation0%
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, DOE, SSA report 26 of 28 use cases (93%).
  • Finding11% of reported deployed use cases (3 of 28) are classified as generative or agentic AI. View records
  • FindingOf 23 deployed high-impact use cases, 19 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, 54% involve in-house development.
AI classification reported100%
Stage not reported0
Sourcing reported100%