May 2026 Health Policy Update — AI: The Washington Report

Health Policy Takeaways

• Federal AI policy remains unsettled. The White House’s delay of a proposed AI cybersecurity order highlights ongoing debate over federal oversight of advanced AI, with implications for health care organizations navigating evolving compliance and risk expectations.
• HHS is moving AI into core oversight functions. The AERO initiative signals growing use of AI in federally funded health program audits, enforcement, and program integrity activities.
• AI infrastructure policy is becoming more relevant to the health sector. Congressional focus on data centers, grid reliability, and energy costs may affect health systems, life sciences companies, and other organizations with significant digital infrastructure needs.
• FDA continues to shape sector-specific AI governance. The agency’s proposed clinical trial pilot suggests AI oversight in life sciences will continue to develop through targeted, use-case-specific frameworks.
• Energy affordability may emerge as a secondary health policy concern. As AI infrastructure expands, related debates over electricity costs and permitting could have downstream effects on health care providers, research institutions, and other large energy users. 
   

 
1. White House Delays Proposed AI Cybersecurity Order

President Trump postponed a planned executive order on AI and cybersecurity on May 21, hours before a White House ceremony with major technology executives. Reports indicate the order would have created a voluntary framework for leading AI developers to share advanced models with the federal government for cybersecurity and safety review before public release. Trump said he objected to parts of the proposal and warned additional oversight could weaken US competitiveness, especially relative to China.

The delay highlights ongoing disagreements within the administration and industry over how far the federal government should go in overseeing AI. Technology companies have warned that new requirements could slow innovation, while some officials favor stronger safeguards for advanced models and critical infrastructure.

Draft language reported on May 22 suggests the order would also have created an AI cybersecurity clearinghouse, launched benchmarking for advanced cyber capabilities, expanded federal AI-enabled defensive tools, and accelerated cybersecurity hiring. It also reportedly emphasized enforcement of existing criminal laws against malicious AI use while making clear it would not impose mandatory licensing or preclearance for AI models.

Why it matters: For health sector stakeholders, the delay underscores that federal AI policy remains fluid even as expectations around cybersecurity, safety, and governance continue to evolve.

2. HHS Launches AI-Enabled Oversight for Federally Funded Health Programs

On May 21, HHS announced AERO, a new initiative that will use AI to review annual audits for federally funded health programs. HHS said the effort is intended to address persistent audit noncompliance by analyzing at least five years of audit history across all 50 states to identify waste, fraud, and abuse.

The announcement fits the administration’s broader push to expand AI adoption across the federal government, with HHS positioning itself as an early user of generative AI.

In recent months, HHS has expanded employee access to generative AI tools, released an agencywide AI modernization strategy, and promoted AI for administrative and oversight functions. AERO shows how the department is moving from strategy to operational use at scale.

The initiative also aligns with the administration’s broader anti-fraud agenda in Medicaid and Medicare, including the March executive order creating the Task Force to Eliminate Fraud.

Why it matters: Providers, plans, grantees, and state partners should expect increased attention to audit readiness, documentation, and governance as HHS begins incorporating AI into compliance and program integrity functions.

3. Congress Signals Increased Focus on AI Infrastructure

The House Appropriations Committee’s advancement of the FY2027 Energy and Water bill on May 20 shows how Congress is increasingly addressing AI through the infrastructure that supports it. The bill treats data centers as a key intersection of AI development, energy policy, consumer protection, and grid resilience.

Lawmakers also focused on the effect of data centers on utility costs. The bill includes funding for research on reusing thermal energy from data centers and directs FERC to work with DOE’s PermitAI initiative to accelerate permitting, highlighting the tension between limiting infrastructure impacts and speeding deployment.

The bill also underscores that AI infrastructure governance will require coordination across federal agencies, states, and utility regulators.

Why it matters: For health systems, research institutions, and life sciences organizations with growing compute demands, AI infrastructure policy may increasingly intersect with energy costs, permitting, and resilience planning.

4. FDA Advances AI Oversight in Clinical Development

On April 29, 2026, the FDA issued a Request for Information (RFI) on a proposed pilot to assess whether AI-enabled tools can improve decision-making in early-phase clinical trials. The agency is seeking input on both program design and evaluation metrics.

The RFI emphasizes “trustworthiness” and aligns the pilot with NIST’s AI Risk Management Framework, signaling that the FDA is approaching AI in clinical trials through both innovation and governance lenses.

The agency highlights familiar regulatory concerns, including data governance, transparency, privacy, security, reliability, and bias in AI-assisted decision-making.

Why it matters: Drug sponsors, device developers, and other regulated health companies should anticipate that FDA expectations for AI may continue to develop through targeted frameworks tied to specific clinical and regulatory contexts.

5. Energy and Consumer-Cost Concerns Gain Traction in AI Policy Debates

Alongside broader AI governance debates, policymakers are increasingly focused on the physical infrastructure needed to support large-scale AI deployment.

Lawmakers and regulators are paying closer attention to the energy, water, permitting, and consumer-cost effects of AI data centers. As a result, data centers are becoming a central part of the broader AI policy debate.

A House Energy and Commerce Committee hearing in April 2025 highlighted growing congressional concern about the affordability and environmental effects of AI-driven data centers.

Lawmakers have emphasized that the rapid growth of AI infrastructure is increasing pressure on the electric grid and consumer utility bills.

Developments to monitor:

House Energy and Commerce Hearing on “AI and the Grid.” The April 29 hearing examined how rising AI and data center electricity demand could affect grid reliability and ratepayers, reflecting bipartisan concern about affordability as well as innovation.

The Protecting Families from AI Data Center Energy Costs Act. Introduced on May 18, H.R. 6529 would require large-load customers such as AI data centers, rather than residential consumers, to bear the cost of grid upgrades tied to their power demand.

A December 2025 executive order also left states with authority over zoning, permitting, and utility regulation for AI compute and data center infrastructure.

Why it matters: While not unique to health care, AI infrastructure debates could affect hospitals, research institutions, and other health sector organizations through energy affordability, siting decisions, and local infrastructure constraints.

We will continue to monitor, analyze, and issue reports on these developments. Please feel free to contact us if you have questions about current practices or how to proceed.

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