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: 8 (14.5%)Generative AI
Pilot: 8 (14.5%)Generative AI
Pre-deployment: 39 (70.9%)
Deployed: 36 (47.4%)Classical / predictive ML
Pilot: 6 (7.9%)Classical / predictive ML
Pre-deployment: 34 (44.7%)
Deployed: 24 (42.1%)Natural language processing
Pilot: 6 (10.5%)Natural language processing
Pre-deployment: 27 (47.4%)
Sourcing by technology
Where reportedDeveloped in-house: 3 (5.5%)Generative AI
Contract and in-house: 6 (10.9%)Generative AI
Purchased from vendor: 7 (12.7%)Generative AI
Not reported: 39 (70.9%)
Developed in-house: 11 (14.5%)Classical / predictive ML
Contract and in-house: 10 (13.2%)Classical / predictive ML
Purchased from vendor: 21 (27.6%)Classical / predictive ML
Not reported: 34 (44.7%)
Developed in-house: 14 (24.6%)Natural language processing
Contract and in-house: 6 (10.5%)Natural language processing
Purchased from vendor: 10 (17.5%)Natural language processing
Not reported: 27 (47.4%)
Developed in-house: 1 (1.2%)Computer vision
Contract and in-house: 1 (1.2%)Computer vision
Purchased from vendor: 66 (81.5%)Computer vision
Not reported: 13 (16.0%)
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 | Reinforcement learning | Not reported | n | |
|---|---|---|---|---|---|---|---|---|
| Health and Medical | 10% | 24% | 19% | 43% | 4% | 166 | ||
| Government Benefits Processing | 30% | 19% | 22% | 30% | 27 | |||
| Administrative Functions | 28% | 24% | 28% | 16% | 4% | 25 | ||
| Information Technology | 39% | 33% | 17% | 6% | 6% | 18 | ||
| Other | 25% | 42% | 33% | 12 | ||||
| Procurement and Financial Management | 50% | 17% | 8% | 25% | 12 | |||
| Service Delivery | 25% | 25% | 25% | 8% | 8% | 8% | 12 | |
| Cybersecurity | 11% | 67% | 22% | 9 | ||||
| Human Resources | 29% | 29% | 29% | 14% | 7 | |||
| Law Enforcement | 60% | 40% | 5 | |||||
| Science | 50% | 50% | 2 |
High-impact designation by technology
High-impact: 52 (68.4%)Classical / predictive ML
Not high-impact: 24 (31.6%)
High-impact: 24 (42.1%)Natural language processing
Not high-impact: 33 (57.9%)
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 |
| Reinforcement learning | 0 | – | – | – | – | – |
| 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 367 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.