Rep. Pramila Jayapal — National AI Charter Act Framework
National AI Charter
Released October 1, 2026 with the support of 18 organizations, including the American Federation of Teachers, Public Citizen, the Future of Life Institute, AI Now, and the American Economic Liberties Project, Jayapal's framework would require every AI company to hold a federal charter to operate in the United States, on the model of national bank charters. Companies valued at $1 billion or more would need congressional approval to be chartered, and smaller ones approval from a new National AI Charter Authority, a fee-funded prudential regulator with round-the-clock oversight, a federal testing function, and a bipartisan State Attorney General Advisory Council; charters would be renewed every ten years. The terms are non-negotiable. High-risk systems could not be released without federal approval after testing in isolated government facilities, and federal inspectors could trigger a mandated kill switch. Chartered companies would carry a duty of care, put public benefit ahead of profit, seat a safety specialist, a union representative, and a public-interest advocate on their boards, recognize unions, cap executive incentive pay, and could not participate in search or social media or own both AI infrastructure and AI systems. Training on surveillance data and on copyrighted work without authorization would be banned, along with systems capable of evading human control, systems posing catastrophic CBRN or infrastructure risk, and systems that replace licensed professionals or human care providers. A Monopoly Data Tax would fund AI Bonds paid to all Americans. Violators face strict liability, personal criminal liability for executives, charter suspension, and a 'corporate death penalty' that liquidates repeat offenders.
Key Provisions
Every AI company must hold a National AI Charter; companies valued at $1B or more need congressional approval, smaller ones approval from the Authority; renewal every 10 years
National AI Charter Authority: a fee-funded prudential regulator with a director, federal testing, inspectors with immediate access, and a bipartisan State Attorney General Advisory Council
Immediate shutdown of dangerous rogue models and of new training on surveillance data or stolen content
No release of high-risk systems without federal approval after testing in isolated government facilities; surprise red-teaming by government and certified nonprofits after launch
Mandated kill switch and emergency shutdown capability that federal safety inspectors can trigger directly
Duty of care on companies and executives; public benefit over profit; independent Chief Safety Officer; board seats for a safety specialist, a union representative, and a public-interest advocate
Mandatory union recognition, caps on executive incentive pay, no golden parachutes, and clawbacks after safety incidents
Structural separation: no participation in search or social media, no ownership of both AI infrastructure and AI systems, no ownership of non-AI companies
Bans on surveillance-based training, unauthorized use of copyrighted work and likeness, systems that evade human control, catastrophic CBRN and infrastructure risks, and AI replacement of licensed professionals and human care providers
Monopoly Data Tax and a tax on executive pay fund an AI Public Fund, paid out to all Americans as AI Bonds
Strict liability with mandatory insurance; joint liability with commercial clients; personal civil and criminal liability for executives who sign false quarterly certifications or recklessly deploy dangerous AI
Charter suspension, a 'corporate death penalty' for repeat offenders, a private right of action, and concurrent state enforcement with no preemption of stronger state law
Regulatory Philosophy
Make operating an AI company a privilege the public grants on its own terms. Where most proposals regulate a model, a risk, or a harm, Jayapal regulates the firm: its structure, its governance, its markets, and its right to exist. The bank-charter analogy is deliberate — prudential supervision, safety and soundness, and the separation of banking from commerce — and the framework layers onto it the pre-release approval used for nuclear materials and dangerous weapons. It treats safety, privacy, labor, and monopoly as one problem rooted in business models, and argues that addressing them one bill at a time is what has let the industry divide its opponents.
Every company operating in AI in the United States, chartered and supervised as a firm
Why it lands there
The only item on the map that falls on every layer by design. The charter requirement and conduct bans reach every AI company, from frontier labs to app developers. Structural separation hits the hyperscalers hardest: they could own AI infrastructure or AI systems, but not both, and could not stay in search or social media. Chipmakers are reached as infrastructure owners barred from controlling the models that depend on them.
Khanna and Jayapal both want a new federal agency, a tax on concentrated AI wealth, and a share of the gains for workers. Khanna models his agency on the NRC and the FAA — a technical safety regulator alongside a wealth tax and a workforce administration. Jayapal models hers on bank supervision and goes further on structure: every company needs a charter, the largest need Congress's approval, and the charter dictates board composition, union recognition, which markets a company may enter, and whether it may exist at all. Khanna's program regulates what AI companies do; Jayapal's regulates what they are.
+The most complete answer on the map to the question of who can stop a model: pre-release federal approval, government-run testing, surprise red-teaming, and a kill switch inspectors can pull
+Certifications signed by executives under penalty of perjury, with personal criminal liability and no indemnification, put individual accountability behind the safety claims
+Structural separation between AI infrastructure and AI systems is the only proposal on the map that addresses vertical integration across the industry's layers
+Treats labor, privacy, competition, and safety as one regime, closing the gaps that single-issue bills leave between them
+Preserves state enforcement and stronger state law, with a role for state attorneys general in the Authority itself
Weaknesses
From the perspective of political opposition
−A framework, not legislative text: the thresholds for 'high-risk' and 'dangerous capabilities', the testing standards, and the tax base are all undefined
−Congressional approval for every company valued at $1B or more would put chartering decisions for dozens of firms into the political process
−Several bans — on training with surveillance data, on unauthorized copyrighted content, on systems that replace licensed professionals — would, read literally, prohibit most existing frontier models and many existing products
−The ban on owning both infrastructure and systems would require the breakup of Google, Microsoft, Amazon, and Meta's AI businesses, which no coalition in Congress is close to supporting
−Its scope makes it a statement of a destination rather than a near-term vehicle
On the Podcasts
Verbatim from podcast transcripts; each links to the moment it was said
“What my bill does is it structurally separates these big tech companies. … And if you do that, if you structurally separate, you take away the profit incentive for these companies to prioritize engagement over safety on the social media side.”
Pramila Jayapal, U.S. Representative (D-WA), framework authorThe Hartmann Report · Will Democrats Enforce the Law? · Oct 13, 2026
“You have a proposal that the AI charter authority would be funded by charter fees from the companies themselves, and that makes me think of the patent office… Critics have said that that's part of why the patent office hands out too many low-quality patents because they are incentivized to issue patents.”
Matt Stoller, Research director, American Economic Liberties ProjectOrganized Money · Charting A New Course On AI Regulation (With Rep. Pramila Jayapal) · Oct 13, 2026
“I do think there's some sense in making it a federal AI charter. This is such a big part of our economy right now. It's propping up the whole economy, and there's so much anxiety about how this will transform things that, yeah, we should get in on the ground floor…”
David Dayen, Executive editor, The American ProspectOrganized Money · Charting A New Course On AI Regulation (With Rep. Pramila Jayapal) · Oct 13, 2026