Technology landscape
How reported AI classifications spread across agencies, missions, lifecycle stages and sourcing. Each record carries one reported classification, so categories do not overlap. A classification describes the technique, not a specific commercial model.
Lifecycle by technology
Share of each technology's recordsSourcing by technology
Where reportedDeveloped in-house: 2 (20.0%)Classical / predictive ML
Contract and in-house: 3 (30.0%)Classical / predictive ML
Purchased from vendor: 5 (50.0%)
Technology adoption by agency
Row share: each agency's records by classification · 16 largest portfolios in the filterTechnology by topic area
Row share within each topicHigh-impact designation by technology
High-impact: 3 (75.0%)Natural language processing
Not high-impact: 1 (25.0%)
Governance disclosure by technology
High-impact records: reported in place / scope| Technology | High-impact | Testing | Impact assess. | Indep. review | Monitoring | Training |
|---|---|---|---|---|---|---|
| Classical / predictive ML | 7 | 7 / 7 | 5 / 7 | 5 / 7 | 7 / 7 | 6 / 7 |
| Natural language processing | 3 | 2 / 3 | 1 / 3 | 1 / 3 | 1 / 3 | 0 / 3 |
| Computer vision | 6 | 6 / 6 | 4 / 6 | 4 / 6 | 5 / 6 | 5 / 6 |
Shows counts reported in place against all high-impact records of that technology. The remainder includes in-progress, not applicable and unanswered. Full governance view
Systems, vendors and technology are different things
18 of 20 records name a vendor (90%)Vendor: the supplier the agency names in a free-text field. Matched to a standard list of companies; one record may name several.
System name: the agency's name for the system (reported for 85% of records).
AI classification: the technique category the agency selected. A vendor name does not show which model or technique is used, and this platform does not infer it.