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: 1 (4.8%)Generative AI
Contract and in-house: 3 (14.3%)Generative AI
Purchased from vendor: 17 (81.0%)
Developed in-house: 4 (10.0%)Classical / predictive ML
Contract and in-house: 5 (12.5%)Classical / predictive ML
Purchased from vendor: 31 (77.5%)
Developed in-house: 3 (15.8%)Natural language processing
Contract and in-house: 2 (10.5%)Natural language processing
Purchased from vendor: 14 (73.7%)
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 | n | |
|---|---|---|---|---|---|---|
| Law Enforcement | 20% | 37% | 32% | 10% | 2% | 41 |
| Administrative Functions | 19% | 52% | 19% | 10% | 21 | |
| Information Technology | 31% | 62% | 8% | 13 | ||
| Procurement and Financial Management | 25% | 75% | 4 | |||
| Cybersecurity | 67% | 33% | 3 | |||
| Service Delivery | 67% | 33% | 3 | |||
| Human Resources | 100% | 2 | ||||
| Transportation | 100% | 1 |
High-impact designation by technology
Presumed high-impact, determined not: 3 (14.3%)Generative AI
Not high-impact: 18 (85.7%)
Presumed high-impact, determined not: 11 (27.5%)Classical / predictive ML
Not high-impact: 29 (72.5%)
Presumed high-impact, determined not: 3 (15.8%)Natural language processing
Not high-impact: 16 (84.2%)
Governance disclosure by technology
High-impact records: reported in place / scope| Technology | High-impact | Testing | Impact assess. | Indep. review | Monitoring | Training |
|---|---|---|---|---|---|---|
| Generative AI | 0 | – | – | – | – | – |
| Classical / predictive ML | 0 | – | – | – | – | – |
| Natural language processing | 0 | – | – | – | – | – |
| Computer vision | 0 | – | – | – | – | – |
| 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
64 of 88 records name a vendor (73%)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.