The "OneHHS" Era: Decoding The New Federal AI Strategy

For years, the Department of Health and Human Services (HHS) has approached Artificial Intelligence in pockets. The Food and Drug Administration (FDA) handled devices, the National Institute of Health (NIH) led the charge in research, and the Centers for Disease Control and Prevention (CDC) managed public health surveillance.

The release of the HHS AI Strategy (Version 1.0) on December 4, 2025, marks the end of that fragmented system and the beginning of the "OneHHS" era. This is a unified framework designed to dissolve barriers and accelerate AI adoption from the mailroom to the laboratory. It isn't a standalone initiative; it operationalizes the Administration’s AI Action Plan and Executive Order 14179 ("Removing Barriers to American Leadership in AI"), alongside the OMB's implementation guidance (M-25-21 and M-25-22).

For medical device manufacturers, life sciences companies, and health policy leaders, the message is clear: Federal AI adoption is no longer optional. It is a well-coordinated mandate that permeates the entire health system.

The Core Philosophy: A "Living" Infrastructure

HHS’s central tenet is to create a "living" AI infrastructure. Rather than getting bogged down in theoretical frameworks, the agency is zeroing in on building a "practical layer" of AI to modernize operations and reduce administrative burden.

By explicitly labeling this "Version 1.0," HHS is acknowledging a harsh truth: The five-year strategic plans of the past are dead. AI moves too fast for static roadmaps.

The plan outlines five pillars for this next phase:

1. Governance and Risk Management

2. Infrastructure for User Needs

3. Workforce Development & Burden Reduction

4. Gold Standard Science & Reproducibility

5. Care & Public Health Delivery Modernization

What This Means for Industry Leaders

1.For Healthcare Operations: Efficiency is the Mandate

HHS’s stated goal to "automate tedious tasks" has already begun with the internal provision of tools like ChatGPT3. This signals to the private sector that using AI for operational efficiency isn't just allowed—it is the new standard. Expect interoperability with shared federal infrastructure to become a key procurement requirement.

2.For Life Sciences: The "Gold Standard" Shift

The NIH Mandate is centered on using AI to accelerate biomedical research. However, this comes with strings attached. The strategy’s focus on "rigorous scientific standards" implies that future grant funding and research validation will require clear proof that AI models are reproducible, not just novel. "Black box" discovery models must be explainable to pass regulatory checks.

3.For Public Health: Real-Time Intervention

HHS aims to drive measurable improvements in population health. The implications for the CDC are significant, signaling a switch to real-time, AI-driven surveillance. This lays the groundwork for the Administration's agenda to intervene in chronic disease trends faster than traditional methods allow.

4.For Medical Device Manufacturers: Data Liquidity

The "OneHHS" plan suggests that data generated by medical devices could eventually feed into broader public health AI models. Manufacturers should prepare for new interoperability requirements that insist device data be "AI-ready" for federal analysis.

5. For Market Access Teams: The strategy confirms that CMS will use AI for "claim adjudication" and coverage determinations. This signals a future where your evidence dossiers aren't just read by humans—they are processed by algorithms. To ensure reimbursement, your value proposition data needs to be structured and "machine-readable" to survive an AI-driven claims review.

A Call to Action for Medical Societies

The strategy explicitly calls for HHS to "co-create solutions" with private sector stakeholders. For Medical Societies and Advocacy Groups, this open invitation creates a new strategic imperative. You must move from monitoring AI to validating it.

• For Societies: The HHS focus on "Gold Standard Science" is your entry point. You have the opportunity to verify that the medical data feeding these new federal platforms is clinically sound for your specialty, ensuring that "efficiency" doesn't compromise clinical nuance.

• For Advocacy Groups: With the CDC prioritizing AI for public health, your role is no longer just policy advocacy—it is data advocacy. You must push to ensure that the training data used in these federal algorithms represents the diverse populations you serve, minimizing the risk of algorithmic bias scaling at a national level.

Conclusion

The HHS AI Strategy Version 1.0 is a declaration that the federal government intends to be a "Power User" of AI, not just a regulator. By committing to an iterative, unified approach, HHS is attempting to move at the speed of the market. For the industry, the message is clear: The regulator is upgrading its operating system. It is time we did the same.

References

1. HHS Unveils AI Strategy to Transform Agency Operations. U.S. Department of Health and Human Services. Published December 4, 2025. Accessed December 5, 2025. https://www.hhs.gov/press-room/hhs-unveils-ai-strategy-to-transform-agency-operations.html

2. HHS Artificial Intelligence Strategy. U.S. Department of Health and Human Services. Released December 2025. Accessed December 5, 2025. https://www.hhs.gov/sites/default/files/hhs-artificial-intelligence-strategy.pdf

3. McGee MK. HHS Outlines AI Road Map Amid Major Department Overhaul. HealthcareInfoSecurity. Published December 4, 2025. Accessed December 5, 2025. https://www.healthcareinfosecurity.com/hhs-outlines-ai-road-map-amid-major-department-overhaul-a-30196