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Snapshot · OMB 2025 inventory · processed Oct 11, 2026
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Federal AI Intelligence · U.S. Government AI Observatory

Governance disclosure assessment

Filtered: vendor = ServiceNow

Generated 2026-10-12 16:03 UTCDataset: 2025 Federal Agency AI Use Case Inventory (individually reported use cases), Office of Management and Budget (OMB). Version 2025-inventory@62d5baa65fa3, processed 2026-10-11, rules 2026.10.1. Static snapshot.Applied filters: vendor = ServiceNow · 19 records

Key findings

  • 19 use-case records from 6 agencies: 10 deployed (53%), 0 pilots, 9 in development or acquisition, 0 retired, 0 with no stage reported.
  • 0 records are designated high-impact; 0 of them (n/a) answered at least one minimum-practice question.
  • DOE, SBA, FHFA report 16 of 19 use cases (84%).
  • 10% of reported deployed use cases (1 of 10) are classified as generative or agentic AI.
  • Sourcing is reported for 100% of use cases. Where reported, 16% involve in-house development.

Governance evidence: all use cases in the current filter

PracticeIn placeIn progressNot in placeN/A or precludedOtherNo answerIn scope
Pre-deployment testing95000519
AI impact assessment86000519
Independent review95000519
Ongoing monitoring95000519
Operator training95000519
Fail-safe120020519
Appeal process71060519
User and public consultation15008519

"In place" means the agency reported the practice as established. "No answer" means the field was blank; it says nothing about whether the practice exists.

Agencies with high-impact records

AgencyHigh-impactAnswered any practicePractice answers in place

Method

All figures are computed directly from the normalised inventory records. Category labels are normalised from the source answer options; original values are kept on each record. Governance answers are classified as in place, in progress, not in place, not applicable, precluded, waived, other or no answer, and blanks are never read as "no". See the Methodology page for full rules.

Limitations

  • Figures are what agencies reported in the 2025 inventory. They are not verified, and registration of use cases is not complete for every agency.
  • A blank answer is missing evidence, not evidence that a practice or safeguard is absent.
  • Counts are use-case records. A larger portfolio does not indicate better performance or greater AI maturity, and agencies differ in how they split systems into use cases.
  • The inventory has no budget, cost, accuracy or outcome data. None is shown or inferred here.
  • This is a disclosure analysis. It is not an audit, a compliance determination or an official government assessment.

Source records

All 19 records.

RecordAgency IDAgencyUse caseStage
R0079FHFA-13FHFAWorkflow automation and predictive analytics using ServiceNowDeployed
R1558DOJ-0107DOJServiceNowDeployed
R203339EPAHelpdesk chat assistant for common data system tasksDeployed
R3123SSAEnterprise Ticketing System (ETS)Deployed
R3308DOE-430DOEServiceNow Predictive IntelligenceDeployed
R3316DOE-438DOEServiceNow Virtual AgentDeployed
R3367DOE-507DOEServiceNow Virtual Agent Natural Language UnderstandingDeployed
R3419DOE-563DOEServiceNow Classification PredictionDeployed
R3493DOE-637DOEServiceNow Cluster AnalysisDeployed
R3499DOE-643DOEServiceNow Similarity AnalysisDeployed
R3179SBA-20SBAEmployee Center AI SearchPre-deployment
R3187SBA-31SBAPredictive AIOpsPre-deployment
R3191SBA-35SBAAI Incident SummarizationPre-deployment
R3192SBA-36SBAAI Resolution Notes GenerationPre-deployment
R3193SBA-37SBAAI Vulnerability Ticket DeduplicationPre-deployment
R3194SBA-38SBAAI Vulnerability Remediation AssistancePre-deployment
R3513DOE-657DOEServiceNow Now AssistPre-deployment
R3539DOE-682DOEServiceNow LANL AI Portal IntegrationPre-deployment
R3576DOE-719DOEServiceNow AI SearchPre-deployment

Prepared with Federal AI Intelligence by Irakli Petriashvili. Source: https://github.com/ombegov/2025-Federal-Agency-AI-Use-Case-Inventory