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

Federal AI at a glance

28 agencies · 440 reported use cases · OMB 2025 Inventory. Portfolio size reflects reporting, not performance.

Agency
Stage1
High-impact
Topic
AI type
Sourcing
Vendor
Function
Start year

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

Stage: Pilot
440 Reported AI use cases28 agencies0 Deployed440 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
DOI89HHS88DOE57USDA47DOJ25
Pilot440Largest portfolio: 89 · 28 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

39% generative or agentic. Each record carries one classification; not reported is shown hatched.

Mission areas

Topic area as reported

Lifecycle composition

440 records
Explore lifecycle stages and impact
Within each stageHigh-impact · Gen./agentic
Pilot5%39%

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

DOI, HHS, DOE report 234 of 440 use cases (53%).

Understand the methodology →

Evolution of reported AI use cases

By agency-reported start year · click a year to filter
0100200<15'15'16'17'18'19'20'21'22'23'24219'25'26
Generative or agenticOther or unclassified399 of 440 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 98% of records

Each square is 1% of filtered records. Where reported, 78% involve in-house development.

High-impact AI

Agency self-designation under M-25-21Governance view
440records
Minimum practices · 23 high-impactin place
Pre-deployment testing4%
AI impact assessment4%
Independent review4%
Ongoing monitoring0%
Operator training4%
Fail-safe9%
Appeal process0%
User and public consultation4%
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. 9% of high-impact records answer any practice question.

Analytical observations

Computed from the current filter; reproducible
  • FindingDOI, HHS, DOE report 234 of 440 use cases (53%).
  • FindingSourcing is reported for 98% of use cases. Where reported, 78% involve in-house development.
AI classification reported99%
Stage not reported0
Sourcing reported98%