Comprehensive federal AI legislation remains elusive. In its absence, states have moved aggressively to fill the regulatory void, enacting laws governing AI transparency, algorithmic decision-making, and health care AI applications. That state-level activity is now squarely in the crosshairs of federal policymakers, evidenced recently by Senator Marsha Blackburn's proposed legislation entitled, The Republic Unifying Meritocratic Performance Advancing Machine intelligence by Eliminating Regulatory Interstate Chaos Across American Industry Act, or TRUMP AMERICA AI Act (Editorial Note: federal bills often invite debate regarding whether the acronym or the underlying title was conceived first; here, there is no ambiguity), and the Trump Administration's National AI Legislative Framework, released March 20.

Both the Blackburn bill and the Trump Administration have made federal preemption of state AI laws a clear priority but approach it differently.  The Senate bill would establish a federal floor, preempting state AI laws only where they conflict with its provisions while keeping the door open for stronger state protections, whereas the Administration's recent December 2025 executive order seeks more of a federal ceiling, directing DOJ to challenge state AI laws inconsistent with a national innovation-first policy and conditioning federal funding on state compliance.

This preemption tension is especially pronounced in health care, where AI tools are increasingly embedded in clinical decision support, prior authorization, utilization management, and diagnostics. State health care laws already impose significant transparency, disclosure, and oversight requirements on how those tools must function, which are requirements that a broad federal preemption regime could significantly curtail. The fate of these laws, many of which have already been enacted, with even more pending, depends on the route the federal government ultimately pursues on the preemption question.

In the meantime, even before Congress acts, the state and federal tension is playing out in real time. In a prior alert, we covered the California Attorney General's comment letter challenging HHS's proposed removal of the "model card" health IT certification requirement, for example, capturing the tension between state regulators pushing for AI oversight while the federal government deregulates in the name of AI adoption.

The outcome of this tension will shape the AI health care regulatory landscape for years to come. How much room will states have to require transparency? To mandate disclosures about algorithmic bias? To hold health care entities accountable under state law for AI-driven decisions? Those questions do not yet have answers, but these latest federal proposals are the most recent moves in an ongoing discussion between federal authority and state regulatory ambition. We will continue to monitor these developments closely and provide updates as the landscape evolves.