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: 28 (53.8%)Classical / predictive ML
Pilot: 3 (5.8%)Classical / predictive ML
Pre-deployment: 21 (40.4%)
Sourcing by technology
Where reportedDeveloped in-house: 1 (7.7%)Generative AI
Purchased from vendor: 3 (23.1%)Generative AI
Not reported: 9 (69.2%)
Developed in-house: 10 (19.2%)Classical / predictive ML
Contract and in-house: 5 (9.6%)Classical / predictive ML
Purchased from vendor: 16 (30.8%)Classical / predictive ML
Not reported: 21 (40.4%)
Developed in-house: 1 (4.2%)Natural language processing
Contract and in-house: 2 (8.3%)Natural language processing
Purchased from vendor: 5 (20.8%)Natural language processing
Not reported: 16 (66.7%)
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 | |
|---|---|---|---|---|---|---|---|
| Health and Medical | 7% | 27% | 12% | 49% | 5% | 132 | |
| Government Benefits Processing | 10% | 20% | 30% | 40% | 20 | ||
| Cybersecurity | 20% | 80% | 5 | ||||
| Law Enforcement | 50% | 50% | 4 | ||||
| Human Resources | 33% | 67% | 3 | ||||
| Administrative Functions | 50% | 50% | 2 | ||||
| Information Technology | 50% | 50% | 2 | ||||
| Other | 100% | 2 | |||||
| Procurement and Financial Management | 50% | 50% | 2 | ||||
| Service Delivery | 50% | 50% | 2 |
High-impact designation by technology
Governance disclosure by technology
High-impact records: reported in place / scope| Technology | High-impact | Testing | Impact assess. | Indep. review | Monitoring | Training |
|---|---|---|---|---|---|---|
| Generative AI | 13 | 0 / 13 | 0 / 13 | 0 / 13 | 0 / 13 | 0 / 13 |
| Classical / predictive ML | 52 | 0 / 52 | 0 / 52 | 0 / 52 | 0 / 52 | 0 / 52 |
| Natural language processing | 24 | 0 / 24 | 0 / 24 | 0 / 24 | 0 / 24 | 0 / 24 |
| Computer vision | 67 | 0 / 67 | 0 / 67 | 0 / 67 | 0 / 67 | 0 / 67 |
| Agentic AI | 18 | 0 / 18 | 0 / 18 | 0 / 18 | 0 / 18 | 0 / 18 |
| Not reported | 41 | 0 / 41 | 0 / 41 | 0 / 41 | 0 / 41 | 0 / 41 |
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
0 of 215 records name a vendor (0%)No records match the current filters.
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 0% 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.