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

Executive briefing ↗Explore 27 use cases →
Agency
Stage
High-impact
Topic
AI type
Sourcing
Vendor
Function
Start year

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

failsafe: affirmativefeedback: other
27 Reported AI use cases5 agencies18 Deployed2 Pilots15 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
DOE10DHS7SSA5SBA4
In development/acquisition7Pilot2Deployed18Largest portfolio: 10 · 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

30% generative or agentic. Each record carries one classification; not reported is shown hatched.

Mission areas

Topic area as reported

Lifecycle composition

27 records
Explore lifecycle stages and impact
Within each stageHigh-impact · Gen./agentic
Pre-deployment0%71%
Pilot50%50%
Deployed78%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

DOE, DHS, SSA report 22 of 27 use cases (81%).

Understand the methodology →

Evolution of reported AI use cases

By agency-reported start year · click a year to filter
0510<15'15'16'17'18'19'20'21'22'2311'24'25'26
Generative or agenticOther or unclassified27 of 27 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, 44% involve in-house development.

High-impact AI

Agency self-designation under M-25-21Governance view
27records
Minimum practices · 15 high-impactin place
Pre-deployment testing80%
AI impact assessment87%
Independent review87%
Ongoing monitoring80%
Operator training93%
Fail-safe100%
Appeal process20%
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
  • FindingDOE, DHS, SSA report 22 of 27 use cases (81%).
  • Finding11% of reported deployed use cases (2 of 18) are classified as generative or agentic AI. View records
  • FindingOf 14 deployed high-impact use cases, 13 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, 44% involve in-house development.
AI classification reported100%
Stage not reported0
Sourcing reported100%