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Record STMT-W4496C0Soft law

Artificial Intelligence Strategy

Artificial Intelligence Strategy v3

Strategy Institutional policyNorthern America · USadopted

The U.S. Department of Health and Human Services (HHS) Artificial Intelligence Strategy outlines a comprehensive framework to integrate AI across health care, human services, and agency operations. It establishes a OneHHS approach built around five core pillars: governance and risk management, shared infrastructure, workforce upending and training, gold-standard scientific research, and modernization of health delivery. The strategy provides clear goals, preliminary maturity assessments, and metrics to ensure public trust, data security, and improved health outcomes.

Summary and content fields are drawn from the document text and are pending editorial review.

Who issued it

U.S. Department of Health and Human ServicesGovernment (executive) · US
Lead issuer
Legal forceSoft law
Under whose authorityInstitutional policy
Judged fromfull text

Who it governs

Public sector bodiesAI developers and providersAI deployers and usersResearchers and academics

This strategy is for HHS staff, leaders, researchers, and partners looking to understand the Department's roadmap for deploying and governing AI responsibly.

Sectors
Healthcare · health care and human servicesPublic administration · agency operations and public sectorResearch and science · biomedical research and science

What the document contains

What's covered

The document addresses the internal maturity assessment of agency AI use cases, the establishment of a shared OneHHS AI infrastructure commons, workforce training and burden reduction, principles for reproducibility in health research, and modernization of health and public health care delivery.

What's missing

The document does not provide binding statutory regulations or legally binding mandates for private sector healthcare providers outside of HHS vendor procurement requirements.

Key takeaways
  • HHS is implementing a unified 'OneHHS' approach to accelerate AI innovation across all component divisions.
  • The strategy is organized into five key pillars focusing on governance, user-centric infrastructure, workforce training, gold-standard scientific research, and care modernization.
  • The Department utilizes NIST AI frameworks and OMB guidance to manage high-impact AI risks and maintain public trust.
  • HHS aims to build an AI-ready workforce by providing role-based training programs, secure AI tools, and specialized support.
  • The strategy emphasizes FAIR data sharing principles, open standards, and robust reproducibility in health research.
Principles it states
Gold-Standard ScienceFairness, accessibility, interoperability, and reusability (FAIR)Outcomes-first approach to integrating AI
Outline
· Introductory Letter from the Deputy Secretary
· Introductory Letter from the HHS Chief AI Officer
· Executive Summary
· Section 1: Introduction, Purpose, and Guiding Principle
· Section 2: HHS AI Maturity — Preliminary Assessment
· Section 3: HHS AI Pillars
· Section 4: Conclusion
Issued30 September 2025
Length5,464 words · 21 pages
FormatNot recorded
Scopenational

How it scores

Pending review

Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.

Accountability

4/5

Clear responsibility for AI outcomes

First, the Strategy focuses on strengthening governance, risk management, and public trust through clear roles, comprehensive inventories of AI use cases, transparent risk-management practices, and respect for Americans’ rights

Executive Summary

screening score · 2026-10-24

Fairness

3/5

Non-discrimination and equitable treatment

Contracts will embed privacy and civil rights protections, avoid vendor lock-in through open and portable solutions, and bar any use of HHS data to train separate models without explicit consent.

Cross–Cutting Enablers

screening score · 2026-10-24

Human Dignity

3/5

Respect for the inherent worth of persons

The Department recognizes that good governance (clear policies, oversight mechanisms, and stakeholder engagement) is essential to harness AI effectively while managing its potential risks.

Section 3: HHS AI Pillars

screening score · 2026-10-24

Human Oversight

3/5

Humans remain in control of consequential decisions

AI will augment clinicians, caseworkers, and public health professionals, serving as a supportive tool that enhances human decision-making and efficiency without compromising the essential human touch

Pillar 5: Enable Care and Public Health Delivery Modernization for Better Outcomes

screening score · 2026-10-24

Privacy

4/5

Protection of personal data and private life

Consistent with legal requirements (e.g., Health Insurance Portability and Accountability Act (HIPAA) protections for Personal Health Information (PHI)), HHS encourages use of AI wherever it allows individuals to automate standardized administrative tasks

Pillar 3: Promote Workforce Development and Burden Reduction for Efficiency

screening score · 2026-10-24

Transparency

4/5

Openness about how AI systems work and are used

To maintain your trust, HHS is committed to the highest standards of transparency and accountability around how, when, and why we deploy AI.

Introductory Letter from the HHS Chief AI Officer

screening score · 2026-10-24

Enforcement

4/5

Consequences and compliance mechanisms with real force

Establish standardized minimum risk practices for high‑impact AI including pre‑deployment testing, AI impact assessments, independent review, monitoring, and safe termination if non‑compliant.

Pillar 1: Ensure Governance and Risk Management for Public Trust

screening score · 2026-10-24

Impact Assessment

4/5

Required assessment of an AI system's risks/impacts before or during use

Establish standardized minimum risk practices for high‑impact AI including pre‑deployment testing, AI impact assessments, independent review, monitoring, and safe termination if non‑compliant.

Pillar 1: Ensure Governance and Risk Management for Public Trust

screening score · 2026-10-24

Topics

artificial_intelligence health_care public_health data_governance workforce_development