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 recordsDeployed: 23 (60.5%)Classical / predictive ML
Pilot: 3 (7.9%)Classical / predictive ML
Pre-deployment: 12 (31.6%)
Sourcing by technology
Where reportedDeveloped in-house: 1 (12.5%)Generative AI
Contract and in-house: 1 (12.5%)Generative AI
Purchased from vendor: 2 (25.0%)Generative AI
Not reported: 4 (50.0%)
Developed in-house: 13 (34.2%)Classical / predictive ML
Contract and in-house: 5 (13.2%)Classical / predictive ML
Purchased from vendor: 8 (21.1%)Classical / predictive ML
Not reported: 12 (31.6%)
Contract and in-house: 5 (33.3%)Natural language processing
Purchased from vendor: 3 (20.0%)Natural language processing
Not reported: 7 (46.7%)
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 topic| Generative AI | Classical / predictive ML | Natural language processing | Computer vision | Agentic AI | Not reported | n | |
|---|---|---|---|---|---|---|---|
| Law Enforcement | 48% | 38% | 14% | 21 | |||
| Administrative Functions | 27% | 36% | 27% | 9% | 11 | ||
| Health and Medical | 50% | 20% | 20% | 10% | 10 | ||
| Cybersecurity | 25% | 75% | 8 | ||||
| Service Delivery | 25% | 50% | 25% | 4 | |||
| Government Benefits Processing | 33% | 33% | 33% | 3 | |||
| Information Technology | 33% | 67% | 3 | ||||
| Other | 100% | 3 | |||||
| Procurement and Financial Management | 33% | 33% | 33% | 3 | |||
| Science | 100% | 3 | |||||
| Human Resources | 50% | 50% | 2 |
High-impact designation by technology
High-impact: 12 (31.6%)Classical / predictive ML
Presumed high-impact, determined not: 6 (15.8%)Classical / predictive ML
Not high-impact: 20 (52.6%)
High-impact: 10 (66.7%)Natural language processing
Not high-impact: 5 (33.3%)
Governance disclosure by technology
High-impact records: reported in place / scope| Technology | High-impact | Testing | Impact assess. | Indep. review | Monitoring | Training |
|---|---|---|---|---|---|---|
| Generative AI | 0 | – | – | – | – | – |
| Classical / predictive ML | 12 | 3 / 12 | 2 / 12 | 2 / 12 | 3 / 12 | 3 / 12 |
| Natural language processing | 10 | 1 / 10 | 1 / 10 | 1 / 10 | 1 / 10 | 1 / 10 |
| Computer vision | 1 | 0 / 1 | 0 / 1 | 0 / 1 | 0 / 1 | 0 / 1 |
| Agentic AI | 2 | 0 / 2 | 0 / 2 | 0 / 2 | 0 / 2 | 0 / 2 |
| Not reported | 1 | 0 / 1 | 0 / 1 | 0 / 1 | 0 / 1 | 0 / 1 |
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
20 of 73 records name a vendor (27%)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 38% 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.