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: 38 (62.3%)Generative AI
Pilot: 6 (9.8%)Generative AI
Pre-deployment: 17 (27.9%)
Sourcing by technology
Where reportedDeveloped in-house: 15 (24.6%)Generative AI
Contract and in-house: 4 (6.6%)Generative AI
Purchased from vendor: 42 (68.9%)
Developed in-house: 3 (30.0%)Classical / predictive ML
Contract and in-house: 2 (20.0%)Classical / predictive ML
Purchased from vendor: 5 (50.0%)
Developed in-house: 1 (16.7%)Natural language processing
Contract and in-house: 3 (50.0%)Natural language processing
Purchased from vendor: 2 (33.3%)
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 | n | |
|---|---|---|---|---|---|---|---|
| Information Technology | 97% | 3% | 37 | ||||
| Administrative Functions | 92% | 8% | 13 | ||||
| Law Enforcement | 11% | 11% | 78% | 9 | |||
| Energy and the Environment | 14% | 57% | 29% | 7 | |||
| Procurement and Financial Management | 40% | 20% | 20% | 20% | 5 | ||
| Service Delivery | 50% | 50% | 4 | ||||
| Other | 67% | 33% | 3 | ||||
| Cybersecurity | 50% | 50% | 2 | ||||
| Government Benefits Processing | 100% | 2 | |||||
| Health and Medical | 100% | 1 | |||||
| Human Resources | 100% | 1 | |||||
| International Affairs | 100% | 1 | |||||
| Science | 100% | 1 | |||||
| Transportation | 100% | 1 |
High-impact designation by technology
High-impact: 2 (33.3%)Natural language processing
Not high-impact: 4 (66.7%)
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 | 2 | 2 / 2 | 2 / 2 | 2 / 2 | 2 / 2 | 2 / 2 |
| Natural language processing | 2 | 2 / 2 | 1 / 2 | 1 / 2 | 1 / 2 | 2 / 2 |
| Computer vision | 7 | 7 / 7 | 6 / 7 | 6 / 7 | 7 / 7 | 7 / 7 |
| Agentic AI | 0 | – | – | – | – | – |
| Other | 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
69 of 87 records name a vendor (79%)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 100% 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.