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

Federal AI at a glance

10 agencies · 109 reported use cases · OMB 2025 Inventory. Portfolio size reflects reporting, not performance.

Executive briefing ↗Explore 109 use cases →
Agency
Stage
High-impact
Topic
AI type
Sourcing
Vendor
Function1
Start year

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

Function: Image and video analysisfeedback: blank
109 Reported AI use cases10 agencies29 Deployed17 Pilots14 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
DOI30NASA29DOC13USDA11VA10
In development/acquisition48Pilot17Deployed29Retired2Not reported13Largest portfolio: 30 · 10 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

3% generative or agentic. Each record carries one classification; not reported is shown hatched.

Mission areas

Topic area as reported

Lifecycle composition

109 records
Explore lifecycle stages and impact
Within each stageHigh-impact · Gen./agentic
Pre-deployment6%4%
Pilot0%0%
Deployed34%3%
Retired50%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

DOI, NASA, DOC report 72 of 109 use cases (66%).

Understand the methodology →

Evolution of reported AI use cases

By agency-reported start year · click a year to filter
05<15'15'16'17'18'19'20'21'22'23'249'25'26
Generative or agenticOther or unclassified36 of 109 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 42% of records

Each square is 1% of filtered records. Where reported, 65% involve in-house development.

High-impact AI

Agency self-designation under M-25-21Governance view
109records
Minimum practices · 14 high-impactin place
Pre-deployment testing0%
AI impact assessment0%
Independent review0%
Ongoing monitoring0%
Operator training0%
Fail-safe0%
Appeal process0%
User and public consultation0%
No 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. 0% of high-impact records answer any practice question.

Analytical observations

Computed from the current filter; reproducible
  • FindingDOI, NASA, DOC report 72 of 109 use cases (66%).
  • Finding3% of reported deployed use cases (1 of 29) are classified as generative or agentic AI. View records
  • FindingOf 10 deployed high-impact use cases, 0 report a completed AI impact assessment and 10 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 42% of use cases. Where reported, 65% involve in-house development.
  • Finding13 use cases (12%) have no reported development stage. View records
AI classification reported87%
Stage not reported13
Sourcing reported42%