The executive briefing
From inventory to insight
A concise reading of federal AI portfolios, deployment and the evidence agencies report.
Read the briefingFederal AI landscape
Federal AI at a glance
11 agencies · 194 reported use cases · OMB 2025 Inventory. Portfolio size reflects reporting, not performance.
Scale & composition
Select an agency to exploreAgencies behind federal AI
In development/acquisition77Pilot17Deployed92Retired8Largest portfolio: 145 · 11 agencies
Conceptual agency landscape · positions do not represent deployment locations. Proximity does not imply a relationship.
AI technology mix
Reported classification · click to cross-filter16% generative or agentic. Each record carries one classification; not reported is shown hatched.
Mission areas
Topic area as reportedLifecycle composition
194 recordsExplore lifecycle stages and impact
Within each stageHigh-impact · Gen./agentic
Pre-deployment49%29%
Pilot35%35%
Deployed72%4%
Retired75%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
VA, HHS, NASA report 183 of 194 use cases (94%).
Understand the methodology →Evolution of reported AI use cases
By agency-reported start year · click a year to filterGenerative or agenticOther or unclassified28 of 194 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 58% of recordsEach square is 1% of filtered records. Where reported, 44% involve in-house development.
Minimum practices · 116 high-impactin place
Pre-deployment testing2%
AI impact assessment1%
Independent review1%
Ongoing monitoring2%
Operator training2%
Fail-safe2%
Appeal process0%
User and public consultation1%
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. 3% of high-impact records answer any practice question.
Analytical observations
Computed from the current filter; reproducible- FindingVA, HHS, NASA report 183 of 194 use cases (94%).
- Finding4% of reported deployed use cases (4 of 92) are classified as generative or agentic AI. View records
- FindingOf 66 deployed high-impact use cases, 1 report a completed AI impact assessment and 62 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 58% of use cases. Where reported, 44% involve in-house development.
AI classification reported96%
Stage not reported0
Sourcing reported58%