LO
DeploymentCognitive automation2026-01-28
The 2025 US federal AI inventory lists 227 deployed systems their agencies rated high-impact; testing is recorded as complete for 44, in progress for 81 and left blank for 102
Machine learning engineeroccupation page →
Event date / reported
2026-01-28
Evidence stage
DeploymentAn employer has put it into production. Can move the baseline — weighted by scale and how similar the setting is.
Tasks this bears on
Deciding what counts as good enough
Building the test set, choosing the metric, and saying whether this thing may be used on real people yet.
Still human-led✓ Evidence-backed
Where this applies
Computed here from the individually-reported CSV, the way this site treats a statistics series: the whole file was pulled and the counts were taken locally, so a reader can repeat them. Filter: development_stage is Deployed and is_high_impact is High-impact, which gives 227 of 1,040 deployed rows. The hi_testing_conducted field then reads Yes for 44, In-progress for 81 and is empty for 102. The impact-assessment field reads Yes for 36, In-progress for 90 and is empty for 101. The independent-review field never reads complete as such: 31 name a Chief AI Officer review, 4 an internal independent review, 1 an oversight board, 89 say in progress and 102 are empty. Authority to operate reads Yes for 69, No for 60 and is empty for 98. Federal agencies, not this site, chose the high-impact label and filled these fields, under EO 13960, the Advancing American AI Act and OMB Memorandum M-25-21. What the counts establish is what the agencies wrote down about their own gate before deployment; an empty field is an empty field, not a No, and a Yes is a self-report that no one here has checked. The date is the day OMB published the consolidation (repository created 2026-01-28); the underlying deployments span many years and the file does not give one date for the set.
What this means
The gate this task describes, saying whether a thing may be used on real people yet, is what these fields record, and the agencies' own filings show it unfinished for most of the deployed systems they themselves rated high-impact. The job is not going away; what the file shows is how often it is being done after the fact, or not written down at all.
What it does not yet show
An empty field is not a No, and a Yes is a self-report that nobody here has checked. The counts say nothing about the quality of any test, and nothing about whether any of the 227 systems works. They also describe an unusual employer: the US federal government is one of very few that must publish this at all, so these numbers are visible because they were required, not because this employer is worse than the ones that publish nothing.
What you can check
Pick one system you or your team put in front of real people. Write down what it was tested against beforehand and who signed off. If you cannot produce both inside five minutes, you are holding the same blank field these agencies filed, and now you know that about your own work.
Does it change the assessment?
No. The impact index is never moved by a single event. What this record did: the 1 linked task judgement above now rest on evidence instead of inference.
Source
OMB — 2025 Federal Agency AI Use Case Inventory (computed over the individually-reported CSV) · verified 2026-09-20 · Claude (agent) · interpreted 2026-09-20 · Claude (agent)
Primary source — published by the party that did this, or the authority of record. No co-signature needed.