The White House yesterday released a seven-pillar national AI policy framework urging Congress to preempt state AI laws, protect children online, and leave copyright questions to courts.
The White House yesterday released a comprehensive set of legislative recommendations titled A National Policy Framework for Artificial Intelligence, a seven-chapter document calling on Congress to establish a unified national standard for AI development and governance across the United States. The framework, published in March 2026, sets out specific policy objectives spanning child safety, intellectual property, free speech, workforce development, and federal preemption of state-level AI regulations - issues that cut directly across the digital advertising and marketing technology industries.
The document does not carry the force of law. It is, according to its own framing, a set of legislative recommendations from the executive branch to Congress, laying out priorities the Trump Administration wants enshrined in statute. Still, the breadth and specificity of the recommendations signal a significant shift in how Washington intends to approach AI governance, moving away from the fragmented, agency-by-agency enforcement model that characterized the previous administration.
The most structurally consequential recommendation concerns federal preemption of state AI laws. The framework calls on Congress to establish a single national standard and to override state-level AI regulations that it characterises as imposing "undue burdens" on innovation. According to the document, "States should not be permitted to regulate AI development, because it is an inherently interstate phenomenon with key foreign policy and national security implications."
This position is not a new one for the administration. As covered by PPC Land, a Tennessee bill proposing felony liability for certain AI training practices had already highlighted the collision course between state legislatures and federal AI policy preferences, with the White House's earlier executive order directing the Commerce Department to identify "onerous" state AI laws within 90 days. That evaluation deadline fell in approximately March 2026, roughly concurrent with today's framework release.
The document carves out explicit exceptions to preemption, which matter considerably for marketing professionals. States would retain authority to enforce their own general-purpose consumer protection laws, child protection statutes, fraud prohibitions, and zoning rules for AI infrastructure. States would also keep authority over their own internal use of AI in procurement and public services such as law enforcement and education. What they would lose is the ability to impose development-side restrictions on AI model training or deployment that go beyond what federal law permits.
For the advertising industry, the practical implication is significant. A patchwork of 50 state-level compliance regimes - each with different disclosure requirements, liability standards, and definitional frameworks for AI-generated content - creates operational risk that today's framework is designed to eliminate. The document explicitly states the goal is "not fifty discordant ones" but a single minimally burdensome national standard.
The first and most politically prominent chapter of the framework addresses child safety. Here, the recommendations are detailed and in some cases directly applicable to the data collection practices that underpin digital advertising.
According to the document, Congress should "affirm that existing child privacy protections apply to AI systems, including limits on data collection for model training and targeted advertising." That sentence directly implicates how AI-powered advertising systems process data about users who may be minors. It also references the recently enacted Take It Down Act - described as "a key initiative of First Lady Melania Trump" - which addresses the non-consensual distribution of intimate imagery including AI-generated deepfakes, and which the document presents as a foundation for further child protection legislation.
The framework also calls for age-assurance requirements, described as "commercially reasonable" and "privacy protective," for AI platforms likely to be accessed by minors. Mechanisms such as parental attestation are cited as examples. Platforms would additionally be required to implement features specifically designed to reduce risks of "sexual exploitation and self-harm to minors" - language that echoes enforcement language seen across multiple regulatory actions in 2025.
The child safety dimension has particular resonance in the context of AI advertising tools. PPC Land has previously documented the FTC's investigation into seven AI chatbot companies over child safety practices and covered the formal warning letter from 44 state attorneys general targeting major AI companies - including Anthropic, Google, Meta, OpenAI, and Microsoft - demanding protection of children from predatory AI products. The White House framework would anchor these concerns in federal statute rather than relying solely on FTC enforcement authority or state-level action.
The Children's Online Privacy Protection Act, whose revised rules took effect June 23, 2025, already requires separate parental consent for third-party data sharing and expanded definitions of child-directed services, with civil penalties of up to $43,792 per violation. Today's framework signals Congress may go further, specifically tying AI model training and targeted advertising to those existing protections.
The framework's position on copyright is notably restrained - almost conspicuously so, given the volume of litigation and legislative activity on the subject. According to the document, "Although the Administration believes that training of AI models on copyrighted material does not violate copyright laws, it acknowledges arguments to the contrary exist and therefore supports allowing the Courts to resolve this issue."
Congress is explicitly told not to take actions that would influence the judiciary's resolution of whether AI training on copyrighted content constitutes fair use. This is a direct instruction to stay out of pending and future litigation - a significant constraint given that the U.S. Copyright Office has already published three major reports on AI and copyright, and Congress has received the TRAIN Act (S.2455) and other proposals. PPC Land has tracked the copyright debate intensifying over AI training data since at least early 2025, when the Copyright Office's Part 2 report confirmed that AI-generated outputs can only be protected by copyright if a human author has determined "sufficient expressive elements."
At the same time, the framework does not entirely sidestep the issue. It recommends Congress consider enabling collective licensing frameworks that would allow rights holders to negotiate compensation from AI providers without triggering antitrust liability. However, any such legislation "should not address when or whether such licensing is required" - meaning Congress would create the mechanism but not mandate its use. This is a careful line, preserving AI developers' ability to argue fair use while giving rights holders a potential commercial pathway.
The framework also calls for a federal law protecting individuals against unauthorised commercial use of AI-generated replicas of their voice, likeness, or other identifiable attributes, with explicit carve-outs for parody, satire, news reporting, and First Amendment-protected expression. This provision has direct relevance for advertising - voice and likeness replication in AI-generated ad creative has become a live issue as generative tools have matured.
PPC Land reported in March 2026 on YouTube's expansion of likeness detection tools to government officials, journalists, and political candidates, illustrating how platforms have begun developing technical infrastructure for exactly the kind of protections the White House framework envisions at the statutory level. That expansion followed PPC Land's earlier coverage of YouTube's deepfake problem in the creator economy, where AI-generated scam videos using creators' likenesses persisted on the platform while legitimate journalistic content was demonetised.
The framework's second chapter covers what it calls "Safeguarding and Strengthening American Communities." Substantively, much of this section addresses the physical infrastructure of AI - data centres, power grids, and permitting. According to the document, Congress should ensure that "residential ratepayers do not experience increased electricity costs as a result of new AI data center construction and operation" - a provision tied to something called the Ratepayer Protection Pledge. At the same time, Congress is asked to streamline federal permitting for AI infrastructure construction, allowing developers to generate power on-site or behind the meter to accelerate buildout and "enhance grid reliability."
For small businesses specifically, the framework calls for grants, tax incentives, and technical assistance programs to support wider AI deployment across American industry. This provision mirrors growing attention to the gap between large technology companies - which have extensive internal AI resources - and smaller advertisers who rely on platform tools and third-party solutions. According to global ad spend data tracked by PPC Land, total global advertising is projected to reach $1.14 trillion in 2025, with AI infrastructure investment creating incremental advertising demand across platforms. The concentration of AI capability at the top of the market is a structural dynamic that the White House appears to be trying to address through direct support for smaller operators.
The framework also asks Congress to augment law enforcement efforts to combat AI-enabled impersonation scams targeting vulnerable populations such as seniors. For marketers, this intersects directly with brand safety - AI-generated impersonation content creates environments hostile to legitimate advertisers and erodes consumer trust in digital channels.
The framework's fourth chapter addresses censorship in notably pointed language. According to the document, "Congress should prevent the United States government from coercing technology providers, including AI providers, to ban, compel, or alter content based on partisan or ideological agendas." It further calls for an effective means for Americans to seek redress from the federal government for agency efforts to "censor expression on AI platforms or dictate the information provided by an AI platform."
This section reflects longstanding concerns from the current administration about government influence over platform moderation decisions, concerns that have become particularly acute as AI systems increasingly mediate content discovery, recommendation, and generation. For the advertising ecosystem, these provisions could affect content policies governing what AI systems can and cannot do in ad creative generation - a live area of concern as programmatic advertising integrates generative AI across campaign creation and optimisation workflows.
The sixth chapter establishes a workforce development agenda. According to the document, Congress should use "non-regulatory methods to ensure that existing education programs and workforce training and support programs, including apprenticeships, affirmatively incorporate AI training." Congress would also be asked to expand federal study of "task-level workforce realignment driven by AI" - a phrasing that suggests a relatively granular approach to understanding how AI affects specific job functions rather than employment in aggregate.
Land-grant institutions are specifically called out as vehicles for technical assistance, demonstration projects, and AI youth development programs. This is significant because land-grant universities have historically served as points of technology transfer between research institutions and industries including agriculture, manufacturing, and more recently digital technology. Incorporating them into AI workforce development creates potential pathways for regional capability-building outside major technology hubs.
The fifth chapter on innovation contains several technically significant proposals. Congress is asked to establish regulatory sandboxes for AI applications - controlled testing environments where companies can develop and deploy AI systems without immediately triggering full regulatory compliance requirements. The framework is explicit that Congress should not create "any new federal rulemaking body to regulate AI," directing AI governance instead toward existing sector-specific regulators with subject matter expertise.
This approach would mean that AI in healthcare continues to fall under FDA oversight frameworks, AI in financial services under SEC or CFTC jurisdiction, and AI in advertising under the FTC - rather than a new dedicated AI regulator modelled on, say, the European Union's AI Act, which came into force in August 2024. For the digital advertising industry, the bipartisan AMERICA Act introduced in March 2025 - which targets structural conflicts of interest in the programmatic advertising supply chain - illustrates the kind of sector-specific legislation the White House framework would channel AI governance through, rather than a general-purpose AI oversight body.
Congress is also asked to make federal datasets available "in AI-ready formats" for use in training AI models - a provision that would give industry and academia access to government data holdings that are currently difficult to use for machine learning purposes due to format and access constraints.
The framework's direct relevance to marketing professionals is concentrated in several areas. The copyright provisionsaffect publishers and content creators whose material may be used in AI training datasets - a concern documented extensively by Mediavine, which launched a petition in August 2025 demanding immediate Copyright Office action on behalf of over 17,000 independent digital publishers. The administration's position - that training on copyrighted content does not violate copyright law - aligns with arguments made by AI developers, but the collective licensing mechanism proposed could create new commercial structures for creator compensation.
The child privacy provisions extend existing COPPA frameworks into AI systems, with explicit mention of "targeted advertising" as a data use subject to limits when minors are involved. This builds on enforcement momentum from the FTC and multiple state attorneys general that was already reshaping how advertising platforms handle data from users who may be under 18.
The preemption provisions would, if enacted, consolidate compliance requirements for AI-powered advertising tools into a single federal standard. Companies operating programmatic advertising campaigns across multiple states currently face potentially divergent obligations under state privacy and AI laws. A federal floor with targeted exceptions for consumer protection, fraud, and child safety could reduce operational complexity while preserving meaningful protections.
The impersonation provisions - covering AI-generated voice and likeness replicas - would create a federal legal basis for advertising restrictions on synthetic representations of real individuals, with carve-outs for expression protected by the First Amendment.
None of these recommendations are law. They require congressional action. The document itself acknowledges as much. But the administration's willingness to engage in this level of specificity - seven chapters, dozens of discrete recommendations, explicit positions on contested legal questions including copyright fair use - signals that AI governance will be a significant legislative priority in the 118th Congress.
Who: The White House, under the Trump Administration, released the document. It is directed at the United States Congress and addresses AI developers, platform operators, content creators, small businesses, and the American public. Luis Alberto Montezuma, an International Data Spaces Facilitator, shared commentary on LinkedIn the same day, characterising the framework as a "legislative outline to establish a consistent national standard for AI development."
What: A seven-chapter set of legislative recommendations spanning child safety, community safeguarding, intellectual property, free speech, innovation policy, workforce development, and federal preemption of state AI laws. The document includes dozens of specific congressional directives, including maintaining that training AI on copyrighted material should remain a question for courts rather than Congress, establishing regulatory sandboxes, creating age-assurance requirements for minors, and building mechanisms for collective licensing negotiation between rights holders and AI developers.
When: The framework was published in March 2026 and released today, March 22, 2026.
Where: Issued from the White House as a formal set of legislative recommendations. Its scope is explicitly national - aimed at creating a single federal standard rather than allowing the current state-by-state variation to persist. The document explicitly frames AI development as "an inherently interstate phenomenon with key foreign policy and national security implications."
Why: The administration frames the framework as essential to maintaining United States leadership in AI globally. The core concern is regulatory fragmentation - the emergence of differing state AI laws that create compliance burdens and competitive disadvantages for American companies relative to international rivals. The framework also responds to documented harms including AI-enabled deepfake abuse, child exploitation risks in AI chatbot environments, impersonation scams targeting seniors, and data collection practices that may conflict with existing child privacy law.