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
1 agencies · 11 reported use cases · OMB 2025 Inventory. Portfolio size reflects reporting, not performance.
Scale & composition
Select an agency to exploreAgencies behind federal AI
In development/acquisition3Deployed8Largest portfolio: 11 · 1 agencies
Conceptual agency landscape · positions do not represent deployment locations. Proximity does not imply a relationship.
AI technology mix
Reported classification · click to cross-filter36% generative or agentic. Each record carries one classification; not reported is shown hatched.
Mission areas
Topic area as reportedLifecycle composition
11 recordsExplore lifecycle stages and impact
Within each stageHigh-impact · Gen./agentic
Pre-deployment0%67%
Deployed25%25%
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
25% of reported deployed use cases (2 of 8) are classified as generative or agentic AI.
Understand the methodology →Evolution of reported AI use cases
By agency-reported start year · click a year to filterGenerative or agenticOther or unclassified11 of 11 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 recordsEach square is 1% of filtered records. Where reported, 18% involve in-house development.
Minimum practices · 2 high-impactin place
Pre-deployment testing0%
AI impact assessment100%
Independent review100%
Ongoing monitoring0%
Operator training100%
Fail-safe100%
Appeal process0%
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- Finding25% of reported deployed use cases (2 of 8) are classified as generative or agentic AI. View records
- FindingOf 2 deployed high-impact use cases, 2 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, 18% involve in-house development.
AI classification reported100%
Stage not reported0
Sourcing reported100%