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: 34 (64.2%)Generative AI
Pilot: 7 (13.2%)Generative AI
Pre-deployment: 11 (20.8%)Generative AI
Retired: 1 (1.9%)
Deployed: 3 (25.0%)Classical / predictive ML
Pilot: 3 (25.0%)Classical / predictive ML
Pre-deployment: 6 (50.0%)
Sourcing by technology
Where reportedDeveloped in-house: 3 (5.7%)Generative AI
Contract and in-house: 5 (9.4%)Generative AI
Purchased from vendor: 45 (84.9%)
Developed in-house: 2 (16.7%)Classical / predictive ML
Contract and in-house: 2 (16.7%)Classical / predictive ML
Purchased from vendor: 8 (66.7%)
Developed in-house: 1 (25.0%)Natural language processing
Contract and in-house: 1 (25.0%)Natural language processing
Purchased from vendor: 2 (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 | Other | n | |
|---|---|---|---|---|---|---|
| Information Technology | 98% | 3% | 40 | |||
| Service Delivery | 78% | 22% | 9 | |||
| Administrative Functions | 60% | 20% | 20% | 5 | ||
| Energy and the Environment | 80% | 20% | 5 | |||
| Cybersecurity | 25% | 75% | 4 | |||
| Law Enforcement | 25% | 25% | 50% | 4 | ||
| Other | 50% | 25% | 25% | 4 | ||
| Health and Medical | 100% | 1 | ||||
| Science | 100% | 1 |
High-impact designation by technology
High-impact: 1 (1.9%)Generative AI
Presumed high-impact, determined not: 1 (1.9%)Generative AI
Not high-impact: 51 (96.2%)
High-impact: 1 (25.0%)Natural language processing
Not high-impact: 3 (75.0%)
Governance disclosure by technology
High-impact records: reported in place / scope| Technology | High-impact | Testing | Impact assess. | Indep. review | Monitoring | Training |
|---|---|---|---|---|---|---|
| Generative AI | 1 | 1 / 1 | 0 / 1 | 0 / 1 | 1 / 1 | 1 / 1 |
| Classical / predictive ML | 1 | 1 / 1 | 0 / 1 | 0 / 1 | 1 / 1 | 1 / 1 |
| Natural language processing | 1 | 1 / 1 | 0 / 1 | 0 / 1 | 0 / 1 | 1 / 1 |
| Computer vision | 3 | 2 / 3 | 0 / 3 | 0 / 3 | 1 / 3 | 1 / 3 |
| 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
71 of 73 records name a vendor (97%)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 97% 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.