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

Federal AI landscape: executive briefing

Filtered: agency = HHS; AI type = nlp; sourcing = both

Generated 2026-10-13 23:33 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: agency = HHS; AI type = nlp; sourcing = both · 37 records

Key findings

  • 37 use-case records from 1 agencies: 30 deployed (81%), 7 pilots, 0 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.
  • 0% of reported deployed use cases (0 of 30) are classified as generative or agentic AI.
  • Sourcing is reported for 100% of use cases. Where reported, 100% involve in-house development.

Lifecycle

StageRecordsShare
Deployed3081%
Pilot719%

AI technology

ClassificationRecordsShareDeployed
Natural language processing37100%30

Agencies

AgencyRecordsDeployedHigh-impactCompleteness
HHS · Department of Health and Human Services37300100%

High-impact designation

DesignationRecords
Not high-impact37

Governance evidence: use cases designated high-impact

PracticeIn placeIn progressNot in placeN/A or precludedOtherNo answerIn scope
Pre-deployment testing0000000
AI impact assessment0000000
Independent review0000000
Ongoing monitoring0000000
Operator training0000000
Fail-safe0000000
Appeal process0000000
User and public consultation0000000

"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.

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 37 records.

RecordAgency IDAgencyUse caseStage
R0630HHSemPOWER AIDeployed
R0652HHSSidekick Comms bot Offering User-friendly Tips (SCOUT)Deployed
R0671HHSEDAV Azure DataFactory - Pipeline failure AnalysisDeployed
R0672HHS1CDP (SEDRIC) AIP for Advanced Foodborne Outbreak Investigation (AI Summarization and Receipt Reading)Deployed
R0675HHSNCIRD SmartFind ChatBots - Public and InternalDeployed
R0690HHSDHDSP NOFO Technical Assistance ChatbotDeployed
R0753HHSCMS Labor Analysis Wizard (CLAW)Deployed
R0755HHSAI WorkspaceDeployed
R0818HHSAnalytics-Driven Supplement Evaluation (ASE)Deployed
R0819HHSRenamed: FAR-based Facility Signal Detection Tool Previously: Post-market Surveillance Reports Signal Detection and Cluster Analysis.Deployed
R0820HHSMedWatch DashboardDeployed
R0821HHSQuality Surveillance Dashboard (QSD)Deployed
R0823HHSRenamed: Application References Previously: Application-DMF ReferenceDeployed
R0824HHSRenamed: Extracting DMF Facilities from unstructured documents Previously: DMF (Drug Master File) FacilitiesDeployed
R0825HHSRenamed: Information Visualization Platform (InfoViP) to Support Analysis of FAERS safety reports Previously: Information Visualization Platform (InfoViP) to Support Analysis of adverse event reportsDeployed
R0836HHSCDER PublicationsDeployed
R0838HHSCreating a development networkDeployed
R0844HHSUse case package 1: Empirical application of the Sentinel EHR and claims Data Partner network to address ARIA insufficient inferential requests (UC1)Deployed
R0845HHSCI5: Development and refinement of toolkits for routine use in the EHR and claims Data Partner networkDeployed
R0846HHSUse case package 2 (UC2): Empirical application of the Sentinel EHR and claims Data Partner network to enhance ARIA insufficient inferential requests and atypical descriptive requestsDeployed
R0847HHSFE5: Incorporate a range of frequently used engineering features from EHRs into the Sentinel common data model in the Sentinel EHR and claims linked Data Partner networkDeployed
R0848HHSDevelop an empirical algorithm to automate negative control identification in Sentinel System using the “Data-driven Automated Negative Control Estimation (DANCE)” algorithmDeployed
R0849HHSSupport tools that can be used in conjunction with Electronic Health Record (EHR) data, such as machine learning and natural language processing (NLP), and the use of Artificial Intelligence (AI) chart review toolsDeployed
R0850HHSSentinel System Task Order to address an Emerging Safety NeedDeployed
R0875HHSChatBot for Safety Reporting Portal Adverse Events and Product problems submissionsDeployed
R0879HHSElectronic translational services for regulatory documents for articles offered for importDeployed
R0927HHSNCI-DOE Collaboration, MOSSAIC project (Modeling Outcomes using Surveillance Data and Scalable AI for Cancer)Deployed
R0941HHSSRDMS NLP COIDeployed
R0984HHSAsk AithenaDeployed
R1031HHSGrantSolutions Text Analyzer ToolDeployed
R0650HHSRAPID Analysis of Policy and Program Documents (RAPID)Pilot
R0668HHSSchool LLM initial abstract review processPilot
R0692HHSDLS AI Assistant toolPilot
R0790HHSAI Agent Orchestrator POCPilot
R0957HHSAutomated approaches to analyzing scientific topicsPilot
R0982HHSMirBotPilot
R0998HHSOSPIDA RPAB Scientific Coding Assistance Tool (CAT)Pilot

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