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: 30 (28.3%)Generative AI
Pilot: 29 (27.4%)Generative AI
Pre-deployment: 47 (44.3%)
Deployed: 13 (13.7%)Classical / predictive ML
Pilot: 11 (11.6%)Classical / predictive ML
Pre-deployment: 71 (74.7%)
Deployed: 2 (25.0%)Computer vision
Pilot: 1 (12.5%)Computer vision
Pre-deployment: 5 (62.5%)
Sourcing by technology
Where reportedDeveloped in-house: 42 (39.6%)Generative AI
Contract and in-house: 28 (26.4%)Generative AI
Purchased from vendor: 15 (14.2%)Generative AI
Not reported: 21 (19.8%)
Developed in-house: 19 (20.0%)Classical / predictive ML
Contract and in-house: 5 (5.3%)Classical / predictive ML
Purchased from vendor: 7 (7.4%)Classical / predictive ML
Not reported: 64 (67.4%)
Developed in-house: 1 (8.3%)Natural language processing
Contract and in-house: 2 (16.7%)Natural language processing
Purchased from vendor: 3 (25.0%)Natural language processing
Not reported: 6 (50.0%)
Developed in-house: 3 (37.5%)Computer vision
Contract and in-house: 1 (12.5%)Computer vision
Purchased from vendor: 2 (25.0%)Computer vision
Not reported: 2 (25.0%)
Developed in-house: 5 (41.7%)Agentic AI
Contract and in-house: 2 (16.7%)Agentic AI
Purchased from vendor: 1 (8.3%)Agentic AI
Not reported: 4 (33.3%)
Developed in-house: 1 (20.0%)Reinforcement learning
Contract and in-house: 2 (40.0%)Reinforcement learning
Purchased from vendor: 1 (20.0%)Reinforcement learning
Not reported: 1 (20.0%)
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 | Other | Not reported | n | |
|---|---|---|---|---|---|---|---|---|---|
| Science | 15% | 73% | 4% | 4% | 4% | 1% | 84 | ||
| Information Technology | 70% | 11% | 7% | 11% | 2% | 46 | |||
| Administrative Functions | 76% | 5% | 8% | 8% | 3% | 38 | |||
| Energy and the Environment | 29% | 54% | 3% | 3% | 6% | 6% | 35 | ||
| Other | 33% | 3% | 3% | 61% | 33 | ||||
| Cybersecurity | 38% | 50% | 13% | 8 | |||||
| Procurement and Financial Management | 50% | 17% | 17% | 17% | 6 | ||||
| Human Resources | 100% | 5 | |||||||
| Emergency Management | 50% | 50% | 2 | ||||||
| Transportation | 50% | 50% | 2 | ||||||
| Health and Medical | 100% | 1 | |||||||
| International Affairs | 100% | 1 |
High-impact designation by technology
High-impact: 7 (7.4%)Classical / predictive ML
Presumed high-impact, determined not: 3 (3.2%)Classical / predictive ML
Not high-impact: 85 (89.5%)
Governance disclosure by technology
High-impact records: reported in place / scope| Technology | High-impact | Testing | Impact assess. | Indep. review | Monitoring | Training |
|---|---|---|---|---|---|---|
| Generative AI | 15 | 0 / 15 | 0 / 15 | 0 / 15 | 0 / 15 | 0 / 15 |
| Classical / predictive ML | 7 | 0 / 7 | 0 / 7 | 0 / 7 | 0 / 7 | 0 / 7 |
| Natural language processing | 0 | – | – | – | – | – |
| Computer vision | 1 | 0 / 1 | 0 / 1 | 0 / 1 | 0 / 1 | 0 / 1 |
| Agentic AI | 2 | 0 / 2 | 0 / 2 | 0 / 2 | 0 / 2 | 0 / 2 |
| Reinforcement learning | 0 | – | – | – | – | – |
| Other | 2 | 0 / 2 | 0 / 2 | 0 / 2 | 0 / 2 | 0 / 2 |
| Not reported | 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
104 of 276 records name a vendor (38%)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 46% 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.