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: 3 (23.1%)Generative AI
Contract and in-house: 4 (30.8%)Generative AI
Purchased from vendor: 6 (46.2%)
Developed in-house: 10 (40.0%)Classical / predictive ML
Contract and in-house: 7 (28.0%)Classical / predictive ML
Purchased from vendor: 8 (32.0%)
Developed in-house: 1 (16.7%)Natural language processing
Contract and in-house: 2 (33.3%)Natural language processing
Purchased from vendor: 3 (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 topic| Generative AI | Classical / predictive ML | Natural language processing | Computer vision | Agentic AI | n | |
|---|---|---|---|---|---|---|
| Law Enforcement | 39% | 61% | 18 | |||
| Information Technology | 33% | 33% | 25% | 8% | 12 | |
| Government Benefits Processing | 29% | 71% | 7 | |||
| Administrative Functions | 17% | 50% | 17% | 17% | 6 | |
| Energy and the Environment | 25% | 50% | 25% | 4 | ||
| Other | 67% | 33% | 3 | |||
| Service Delivery | 67% | 33% | 3 | |||
| Transportation | 67% | 33% | 3 | |||
| Health and Medical | 100% | 1 | ||||
| Procurement and Financial Management | 100% | 1 |
High-impact designation by technology
High-impact: 3 (23.1%)Generative AI
Presumed high-impact, determined not: 1 (7.7%)Generative AI
Not high-impact: 9 (69.2%)
High-impact: 1 (16.7%)Natural language processing
Not high-impact: 5 (83.3%)
Governance disclosure by technology
High-impact records: reported in place / scope| Technology | High-impact | Testing | Impact assess. | Indep. review | Monitoring | Training |
|---|---|---|---|---|---|---|
| Generative AI | 3 | 3 / 3 | 2 / 3 | 2 / 3 | 2 / 3 | 3 / 3 |
| Classical / predictive ML | 16 | 16 / 16 | 14 / 16 | 14 / 16 | 16 / 16 | 15 / 16 |
| Natural language processing | 1 | 1 / 1 | 1 / 1 | 1 / 1 | 1 / 1 | 1 / 1 |
| Computer vision | 13 | 13 / 13 | 11 / 13 | 11 / 13 | 13 / 13 | 13 / 13 |
| Agentic AI | 0 | – | – | – | – | – |
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
45 of 58 records name a vendor (78%)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 95% 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.