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HHS Releases AI Strategy Centered On Governance And Risk Management

The new OneHHS approach calls for centralized oversight structures and risk-proportionate controls to guide artificial intelligence use across the department.

The U.S. Department of Health and Human Services (HHS) released a department-wide artificial intelligence strategy designed to expand AI use across internal operations, research, and public health functions. The plan, unveiled Dec. 4, outlines a “OneHHS” approach to coordinate AI efforts across agencies, including the Centers for Disease Control and Prevention, the Food and Drug Administration, and the National Institutes of Health. The strategy is part of broader federal efforts to integrate AI tools while managing risk and improving efficiency.

The department’s AI Strategy identifies five core pillars for implementation:

  • Ensure governance and risk management to maintain public trust. 
  • Design infrastructure and platforms to meet user needs.
  • Promote workforce development and burden reduction to improve efficiency.
  • Foster health research and reproducibility through gold standard science.
  • Enable modernization of care and public health delivery to improve outcomes. 

The department said the strategy seeks to make AI more accessible to the federal workforce and to enhance core functions, from internal workflows to scientific research. Officials also described the effort as an initial step in a broader transformation of how HHS uses emerging technologies. The document aligns with related federal guidance and AI initiatives across government.

HHS Deputy Secretary Jim O’Neill emphasized AI’s potential to drive innovation in health and human services. At the same time, officials highlighted that the strategy will evolve as technology and use cases develop. The OneHHS framework is designed to streamline collaboration among HHS divisions and ensure consistent cybersecurity and technology standards for AI implementation.

Critics of expanded AI use in health settings raised questions about data privacy and oversight, particularly when tools are applied to sensitive health information. Observers note that effective governance will be crucial to balancing innovation with protections for patients and the public.

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