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: 1 (2.2%)Generative AI
Pilot: 10 (22.2%)Generative AI
Pre-deployment: 34 (75.6%)
Deployed: 34 (42.5%)Classical / predictive ML
Pilot: 6 (7.5%)Classical / predictive ML
Pre-deployment: 40 (50.0%)
Sourcing by technology
Where reportedDeveloped in-house: 3 (6.7%)Generative AI
Contract and in-house: 3 (6.7%)Generative AI
Purchased from vendor: 7 (15.6%)Generative AI
Not reported: 32 (71.1%)
Developed in-house: 13 (16.3%)Classical / predictive ML
Contract and in-house: 7 (8.8%)Classical / predictive ML
Purchased from vendor: 17 (21.3%)Classical / predictive ML
Not reported: 43 (53.8%)
Developed in-house: 1 (2.7%)Natural language processing
Contract and in-house: 3 (8.1%)Natural language processing
Purchased from vendor: 6 (16.2%)Natural language processing
Not reported: 27 (73.0%)
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 topic| Generative AI | Classical / predictive ML | Natural language processing | Computer vision | Agentic AI | Other | Not reported | n | |
|---|---|---|---|---|---|---|---|---|
| Health and Medical | 7% | 27% | 12% | 49% | 5% | 132 | ||
| Law Enforcement | 26% | 26% | 26% | 17% | 6% | 35 | ||
| Government Benefits Processing | 10% | 19% | 29% | 5% | 38% | 21 | ||
| Administrative Functions | 45% | 27% | 18% | 9% | 11 | |||
| Science | 36% | 45% | 18% | 11 | ||||
| Information Technology | 56% | 22% | 11% | 11% | 9 | |||
| Other | 38% | 25% | 13% | 25% | 8 | |||
| Human Resources | 43% | 43% | 14% | 7 | ||||
| Procurement and Financial Management | 86% | 14% | 7 | |||||
| Service Delivery | 14% | 57% | 14% | 14% | 7 | |||
| Cybersecurity | 17% | 67% | 17% | 6 | ||||
| Energy and the Environment | 40% | 40% | 20% | 5 | ||||
| Transportation | 25% | 75% | 4 |
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 | 45 | 0 / 45 | 0 / 45 | 0 / 45 | 0 / 45 | 0 / 45 |
| Classical / predictive ML | 80 | 0 / 80 | 0 / 80 | 0 / 80 | 0 / 80 | 0 / 80 |
| Natural language processing | 37 | 0 / 37 | 0 / 37 | 0 / 37 | 0 / 37 | 0 / 37 |
| Computer vision | 78 | 0 / 78 | 0 / 78 | 0 / 78 | 0 / 78 | 0 / 78 |
| Agentic AI | 21 | 0 / 21 | 0 / 21 | 0 / 21 | 0 / 21 | 0 / 21 |
| Other | 2 | 0 / 2 | 0 / 2 | 0 / 2 | 0 / 2 | 0 / 2 |
| Not reported | 55 | 0 / 55 | 0 / 55 | 0 / 55 | 0 / 55 | 0 / 55 |
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 318 records name a vendor (6%)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 7% 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.