“History doesn’t repeat itself, but it often rhymes.” And whether Mark Twain actually said this or not, the sentiment seems to fit the White House’s new AI Policy Framework rather aptly. For not only does the document resemble the Administration’s recent habit of issuing broad, directional policy blueprints (instead of, say, effective concrete changes), it also reads like the latest attempt to clear the field for AI with as little AI-specific regulation as possible – this time by leaning heavily on federal preemption.
In that regard, this document serves as another reflection of what this Administration wants Congress to prioritize (and, just as importantly, what it wants Congress not to do), and moves across seven broad areas of focus: protecting children and empowering parents; supporting communities through AI infrastructure, fraud prevention, and energy policy; respecting intellectual property without legislatively pre-judging the fair-use fight; preventing censorship and protecting speech; enabling innovation through sandboxes, datasets, and existing agencies rather than a new AI regulator; developing an AI-ready workforce; and, finally, building a federal framework that prevents a fragmented patchwork of state AI laws. So, before we even dive into the heat of the meat, it shouldn’t be understated that this “framework” is trying to marry child safety, anti-fraud enforcement, infrastructure buildout, copyright caution, speech protection, and industrial policy into a wish list – all of 4 pages long.
Looking at this section by section (because, why not – it’s 4 pages long), on children and families, the framework pushes Congress to require AI platforms likely to be accessed by minors to adopt “commercially reasonable” and privacy-protective age assurance, parental controls, and features aimed at reducing sexual exploitation and self-harm, while also building on the First Lady’s Take It Down Act (the backronym-titled law formally known as “The Tools to Address Known Exploitation by Immobilizing Technological Deepfakes on Websites and Networks,” which criminalizes the online publication of intimate images and deepfakes) and preserving state child-protection laws of “general applicability” (more on that later).
On infrastructure, it wants Congress to protect residential ratepayers from seeing electricity costs rise because of AI data centers, while simultaneously streamlining permitting so AI infrastructure can be built more quickly and, where possible, supported with on-site or behind-the-meter power. It also urges more law-enforcement support for AI-enabled impersonation scams (particularly those that target “vulnerable populations such as seniors”), more technical capacity within the national-security apparatus to understand frontier model risks, and grants, tax incentives, and technical assistance to help small businesses deploy AI tools.
The copyright and speech sections appear to tell a similar tale. The Administration says it believes training AI models on copyrighted material “does not violate copyright laws,” but also says Congress should let the courts sort that fight out rather than legislating around it now. At the same time, it leaves room for collective licensing or compensation frameworks and supports federal protections against unauthorized AI-generated digital replicas of a person’s voice or likeness, while insisting on First Amendment carveouts for parody, satire, news reporting, and similar expressive works. On speech more broadly, the framework says Congress should stop the federal government from coercing AI providers to alter or suppress content based on partisan or ideological agendas, and should create redress mechanisms for Americans who believe federal agencies pressured AI platforms to censor lawful expression.
The innovation section is essentially a plea to keep the runway clear – use regulatory sandboxes, open up federal datasets, and do not create a new federal AI super-regulator when existing agencies and industry standards can do the job. In that same vein, the workforce section outlines that rather than pairing AI growth with new employer obligations or worker-protection mandates, the framework prefers training, apprenticeships, youth development, technical assistance, and more federal study of how AI is reshaping work at the task level.
Look at everything to this point, and the picture becomes fairly clear – the administration is striving for light-touch federal oversight, strong anti-censorship rhetoric, no new AI super-regulator, and maximum room for domestic buildout and deployment.
But if the framework has a real center of gravity, it is preemption. The White House says Congress should establish a federal AI policy framework that avoids “a fragmented patchwork” of state regulation and should “preempt state AI laws that impose undue burdens” in favor of a “minimally burdensome national standard,” while still preserving some state powers – traditional police powers to enforce generally applicable laws, zoning authority, and rules governing a state’s own use of AI in procurement, education, or law enforcement. It then goes further, saying states “should not be permitted to regulate AI development itself,” should not unduly burden lawful AI use, and should not penalize developers for a third party’s unlawful use of their models. Consider this where the rubber truly hits the road.
As alluded to earlier, this “Policy Framework” also happens to look like the latest effort to keep the AI field as lightly regulated as possible, this time by way of federal preemption. Notably, earlier versions urged policymakers to build AI policy on “existing laws, rules, regulations and guidance,” and later said that “[e]xisting laws cover many risks associated with the use of AI.” The Computer & Communications Industry Association likewise emphasized that AI systems should operate within “existing” legal frameworks.
States, however, appear to have disagreed rather emphatically – to wit; as of March 2026, state lawmakers in 45 states have already introduced over 1,500 AI-related bills, a strong reflection of the judgment that existing law is not enough. It’s only logical, then, that the “next move” would be preemption and an attempt to block AI-specific state laws and preserve only “generally applicable” ones. This framework, in calling for a “minimally burdensome national standard,” rejecting a new federal AI rulemaking body, and favoring existing regulators and broad displacement of state AI-specific laws, still rests on much the same premise as the first: that AI can be governed on essentially the same terms as other digital technologies, even where its risks differ in kind, scale, and speed.
“Undue burden” is a phrase you’ll find in the Dormant Commerce Clause doctrine – however, that phrase’s use here lacks the balancing structure that normally gives that concept meaning (essentially, if the local benefit is real and the effect on interstate commerce is only incidental, the law usually survives unless the burden on interstate commerce is too great); “generally applicable,” meanwhile, sounds neat enough on paper, but may prove to be a litigation magnet because courts will necessarily have to give it meaning, and parties will inevitably fight over whether a law applying traditional legal norms to AI is truly “general” or instead singles out AI systems specifically (and, in turn, is therefore preempted).
Under the White House’s approach, states could possibly be blocked from regulating AI development or imposing AI-targeted safety obligations, even as the federal government declines to impose much in the way of substantive nationwide safeguards of its own. While the document starts out strong and provides relatively robust detail on child safety, it says decidedly less about several other consequential AI risks – including algorithmic discrimination, and particularly in lending, housing, employment, insurance, and healthcare, where AI tools increasingly drive or influence consequential decisions. In the banking world, these systems can affect underwriting, pricing, fraud detection, and other risk-based decision triggers that carry obvious fair-lending implications. More broadly, they can shape whether someone gets a loan, an apartment, insurance, medical care, or a job.
History might not repeat itself, but this certainly sounds like one of its more familiar rhymes. The full framework can be found here: [National Policy Framework Artificial Intelligence]
Written by:
Brett Goodnack, JD, CAMS
Compliance Advisor