Technology landscape
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 recordsDeployedPilotPre-deploymentRetiredNot reported
Generative AI
Generative AI
Deployed: 42 (34.1%)Generative AI
Pilot: 22 (17.9%)Generative AI
Pre-deployment: 59 (48.0%)
123Deployed: 42 (34.1%)Generative AI
Pilot: 22 (17.9%)Generative AI
Pre-deployment: 59 (48.0%)
Classical / predictive ML
Classical / predictive ML
Deployed: 4 (50.0%)Classical / predictive ML
Pre-deployment: 3 (37.5%)Classical / predictive ML
Retired: 1 (12.5%)
8Deployed: 4 (50.0%)Classical / predictive ML
Pre-deployment: 3 (37.5%)Classical / predictive ML
Retired: 1 (12.5%)
Natural language processing
Natural language processing
Deployed: 13 (31.0%)Natural language processing
Pilot: 7 (16.7%)Natural language processing
Pre-deployment: 22 (52.4%)
42Deployed: 13 (31.0%)Natural language processing
Pilot: 7 (16.7%)Natural language processing
Pre-deployment: 22 (52.4%)
Sourcing by technology
Where reportedDeveloped in-houseContract and in-housePurchased from vendorNot reported
Generative AI
Generative AI
Developed in-house: 14 (11.4%)Generative AI
Contract and in-house: 34 (27.6%)Generative AI
Purchased from vendor: 16 (13.0%)Generative AI
Not reported: 59 (48.0%)
123Developed in-house: 14 (11.4%)Generative AI
Contract and in-house: 34 (27.6%)Generative AI
Purchased from vendor: 16 (13.0%)Generative AI
Not reported: 59 (48.0%)
Classical / predictive ML
Classical / predictive ML
Developed in-house: 2 (25.0%)Classical / predictive ML
Contract and in-house: 3 (37.5%)Classical / predictive ML
Not reported: 3 (37.5%)
8Developed in-house: 2 (25.0%)Classical / predictive ML
Contract and in-house: 3 (37.5%)Classical / predictive ML
Not reported: 3 (37.5%)
Natural language processing
Natural language processing
Developed in-house: 4 (9.5%)Natural language processing
Contract and in-house: 12 (28.6%)Natural language processing
Purchased from vendor: 3 (7.1%)Natural language processing
Not reported: 23 (54.8%)
42Developed in-house: 4 (9.5%)Natural language processing
Contract and in-house: 12 (28.6%)Natural language processing
Purchased from vendor: 3 (7.1%)Natural language processing
Not reported: 23 (54.8%)
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 | 50% | 4% | 29% | 12% | 6% | 52 | |||
| TREAS | 56% | 22% | 22% | 18 | |||||
| VA | 44% | 13% | 13% | 6% | 6% | 6% | 13% | 16 | |
| DOJ | 67% | 7% | 20% | 7% | 15 | ||||
| DHS | 50% | 7% | 36% | 7% | 14 | ||||
| DOE | 79% | 7% | 14% | 14 | |||||
| GSA | 55% | 45% | 11 | ||||||
| USDA | 91% | 9% | 11 | ||||||
| NASA | 80% | 10% | 10% | 10 | |||||
| SEC | 86% | 14% | 7 | ||||||
| DOT | 57% | 29% | 14% | 7 | |||||
| DOC | 100% | 7 | |||||||
| STATE | 80% | 20% | 5 | ||||||
| DOI | 50% | 25% | 25% | 4 | |||||
| SSA | 100% | 4 | |||||||
| DOL | 67% | 33% | 3 |
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 | |
|---|---|---|---|---|---|---|---|---|---|
| Information Technology | 65% | 10% | 18% | 8% | 51 | ||||
| Administrative Functions | 80% | 18% | 2% | 50 | |||||
| Service Delivery | 45% | 45% | 5% | 5% | 22 | ||||
| Science | 60% | 27% | 13% | 15 | |||||
| Other | 79% | 14% | 7% | 14 | |||||
| Health and Medical | 38% | 38% | 25% | 8 | |||||
| Human Resources | 86% | 14% | 7 | ||||||
| Law Enforcement | 33% | 50% | 17% | 6 | |||||
| Transportation | 60% | 20% | 20% | 5 | |||||
| Procurement and Financial Management | 75% | 25% | 4 | ||||||
| Cybersecurity | 33% | 33% | 33% | 3 | |||||
| Emergency Management | 100% | 1 | |||||||
| Energy and the Environment | 100% | 1 |
High-impact designation by technology
High-impactPresumed high-impact, determined notNot high-impactNot reported
Generative AI
Generative AI
High-impact: 1 (0.8%)Generative AI
Not high-impact: 116 (94.3%)Generative AI
Not reported: 6 (4.9%)
123High-impact: 1 (0.8%)Generative AI
Not high-impact: 116 (94.3%)Generative AI
Not reported: 6 (4.9%)
Classical / predictive ML8
Natural language processing
Natural language processing
High-impact: 1 (2.4%)Natural language processing
Presumed high-impact, determined not: 1 (2.4%)Natural language processing
Not high-impact: 35 (83.3%)Natural language processing
Not reported: 5 (11.9%)
42High-impact: 1 (2.4%)Natural language processing
Presumed high-impact, determined not: 1 (2.4%)Natural language processing
Not high-impact: 35 (83.3%)Natural language processing
Not reported: 5 (11.9%)
Governance disclosure by technology
High-impact records: reported in place / scope| Technology | High-impact | Testing | Impact assess. | Indep. review | Monitoring | Training |
|---|---|---|---|---|---|---|
| Generative AI | 1 | 0 / 1 | 0 / 1 | 0 / 1 | 0 / 1 | 0 / 1 |
| Classical / predictive ML | 1 | 0 / 1 | 0 / 1 | 0 / 1 | 0 / 1 | 0 / 1 |
| Natural language processing | 1 | 0 / 1 | 0 / 1 | 0 / 1 | 0 / 1 | 0 / 1 |
| Computer vision | 0 | – | – | – | – | – |
| Agentic AI | 1 | 0 / 1 | 0 / 1 | 0 / 1 | 0 / 1 | 0 / 1 |
| Reinforcement learning | 0 | – | – | – | – | – |
| Other | 0 | – | – | – | – | – |
| Not reported | 1 | 0 / 1 | 0 / 1 | 0 / 1 | 0 / 1 | 0 / 1 |
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
53 of 210 records name a vendor (25%)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 29% 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.