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: 252 (29.4%)Generative AI
Pilot: 154 (17.9%)Generative AI
Pre-deployment: 447 (52.1%)Generative AI
Retired: 5 (0.6%)
Deployed: 366 (32.9%)Classical / predictive ML
Pilot: 155 (13.9%)Classical / predictive ML
Pre-deployment: 591 (53.1%)Classical / predictive ML
Retired: 2 (0.2%)
Deployed: 201 (44.3%)Natural language processing
Pilot: 61 (13.4%)Natural language processing
Pre-deployment: 190 (41.9%)Natural language processing
Retired: 2 (0.4%)
Deployed: 162 (55.5%)Computer vision
Pilot: 30 (10.3%)Computer vision
Pre-deployment: 99 (33.9%)Computer vision
Retired: 1 (0.3%)
Sourcing by technology
Where reportedDeveloped in-house: 127 (14.8%)Generative AI
Contract and in-house: 138 (16.1%)Generative AI
Purchased from vendor: 206 (24.0%)Generative AI
Not reported: 387 (45.1%)
Developed in-house: 288 (25.9%)Classical / predictive ML
Contract and in-house: 114 (10.2%)Classical / predictive ML
Purchased from vendor: 154 (13.8%)Classical / predictive ML
Not reported: 558 (50.1%)
Developed in-house: 99 (21.8%)Natural language processing
Contract and in-house: 86 (18.9%)Natural language processing
Purchased from vendor: 80 (17.6%)Natural language processing
Not reported: 189 (41.6%)
Developed in-house: 29 (9.9%)Computer vision
Contract and in-house: 37 (12.7%)Computer vision
Purchased from vendor: 128 (43.8%)Computer vision
Not reported: 98 (33.6%)
Developed in-house: 18 (15.4%)Agentic AI
Contract and in-house: 14 (12.0%)Agentic AI
Purchased from vendor: 12 (10.3%)Agentic AI
Not reported: 73 (62.4%)
Developed in-house: 4 (33.3%)Reinforcement learning
Contract and in-house: 2 (16.7%)Reinforcement learning
Purchased from vendor: 1 (8.3%)Reinforcement learning
Not reported: 5 (41.7%)
Technology adoption by agency
Row share: each agency's records by classification · 16 largest portfolios in the filter| Generative AI | Classical / predictive ML | Natural language processing | Computer vision | Agentic AI | Reinforcement learning | Other | Not reported | n | |
|---|---|---|---|---|---|---|---|---|---|
| HHS | 31% | 19% | 26% | 4% | 6% | 2% | 11% | 447 | |
| NASA | 9% | 66% | 6% | 11% | 5% | 1% | 1% | 0% | 425 |
| VA | 15% | 21% | 16% | 22% | 7% | 0% | 20% | 367 | |
| DOE | 44% | 31% | 6% | 2% | 4% | 1% | 7% | 4% | 340 |
| DOJ | 28% | 34% | 20% | 10% | 1% | 6% | 314 | ||
| DOI | 6% | 69% | 6% | 8% | 2% | 0% | 3% | 5% | 247 |
| DHS | 26% | 24% | 13% | 21% | 1% | 14% | 238 | ||
| DOC | 100% | 223 | |||||||
| USDA | 20% | 48% | 9% | 10% | 2% | 12% | 162 | ||
| TREAS | 60% | 13% | 12% | 2% | 2% | 2% | 9% | 129 | |
| DOT | 21% | 7% | 4% | 6% | 61% | 70 | |||
| SEC | 40% | 23% | 3% | 7% | 5% | 2% | 20% | 60 | |
| STATE | 30% | 10% | 17% | 2% | 3% | 38% | 60 | ||
| TVA | 100% | 59 | |||||||
| ED | 100% | 56 | |||||||
| FDIC | 14% | 30% | 18% | 4% | 6% | 28% | 50 |
Technology 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 | 8% | 70% | 6% | 10% | 4% | 1% | 1% | 758 | |
| Administrative Functions | 48% | 19% | 20% | 6% | 3% | 0% | 3% | 1% | 430 |
| Information Technology | 57% | 18% | 13% | 2% | 7% | 2% | 3% | 394 | |
| Law Enforcement | 19% | 35% | 19% | 24% | 2% | 1% | 285 | ||
| Health and Medical | 17% | 25% | 26% | 28% | 4% | 1% | 272 | ||
| Other | 33% | 28% | 25% | 3% | 1% | 0% | 9% | 0% | 223 |
| Service Delivery | 43% | 23% | 26% | 5% | 2% | 1% | 1% | 150 | |
| Energy and the Environment | 13% | 37% | 4% | 7% | 2% | 2% | 4% | 31% | 131 |
| Procurement and Financial Management | 40% | 33% | 16% | 1% | 9% | 1% | 90 | ||
| Transportation | 13% | 22% | 9% | 9% | 4% | 1% | 43% | 79 | |
| Government Benefits Processing | 34% | 27% | 16% | 7% | 16% | 56 | |||
| Cybersecurity | 26% | 53% | 9% | 2% | 8% | 2% | 53 | ||
| Human Resources | 57% | 17% | 15% | 7% | 2% | 2% | 46 | ||
| Emergency Management | 12% | 48% | 24% | 9% | 3% | 3% | 33 |
High-impact designation by technology
High-impact: 60 (7.0%)Generative AI
Presumed high-impact, determined not: 20 (2.3%)Generative AI
Not high-impact: 740 (86.2%)Generative AI
Not reported: 38 (4.4%)
High-impact: 132 (11.8%)Classical / predictive ML
Presumed high-impact, determined not: 49 (4.4%)Classical / predictive ML
Not high-impact: 927 (83.2%)Classical / predictive ML
Not reported: 6 (0.5%)
High-impact: 56 (12.3%)Natural language processing
Presumed high-impact, determined not: 12 (2.6%)Natural language processing
Not high-impact: 368 (81.1%)Natural language processing
Not reported: 18 (4.0%)
High-impact: 118 (40.4%)Computer vision
Presumed high-impact, determined not: 23 (7.9%)Computer vision
Not high-impact: 147 (50.3%)Computer vision
Not reported: 4 (1.4%)
Governance disclosure by technology
High-impact records: reported in place / scope| Technology | High-impact | Testing | Impact assess. | Indep. review | Monitoring | Training |
|---|---|---|---|---|---|---|
| Generative AI | 60 | 3 / 60 | 4 / 60 | 4 / 60 | 2 / 60 | 5 / 60 |
| Classical / predictive ML | 132 | 19 / 132 | 16 / 132 | 16 / 132 | 19 / 132 | 18 / 132 |
| Natural language processing | 56 | 4 / 56 | 2 / 56 | 2 / 56 | 2 / 56 | 2 / 56 |
| Computer vision | 118 | 19 / 118 | 15 / 118 | 15 / 118 | 17 / 118 | 17 / 118 |
| Agentic AI | 22 | 0 / 22 | 0 / 22 | 0 / 22 | 0 / 22 | 0 / 22 |
| Reinforcement learning | 0 | – | – | – | – | – |
| Other | 2 | 0 / 2 | 0 / 2 | 0 / 2 | 0 / 2 | 0 / 2 |
| Not reported | 55 | 0 / 55 | 0 / 55 | 0 / 55 | 0 / 55 | 0 / 55 |
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
790 of 3,611 records name a vendor (22%)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 25% 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.