Two things are happening in Washington at the same time. AI policy is being written. And the money spent to influence it is setting records. Whether those two facts are related is left, as always, to the reader and the disclosures, both of which are public.
Last year, AI lobbying pulled in about $130 million, and one in four federal lobbyists now works the issue, up from one in nine in 2023. Those are filings, not accusations. What they describe is a policy field being shaped at the same moment the spending around it climbed to its highest point on record.
The money, by the numbers
In the first quarter of 2026 alone, eleven top tech firms spent $20 million, about $226,000 a day. Meta led at $7.1 million, with Amazon and Google behind it. The AI labs posted their biggest lobbying quarters ever, Anthropic at $1.6 million and OpenAI at $1 million, with Anthropic outspending the company it is racing. Across 2025, lobbyists filed more than 3,500 reports mentioning AI for 774 different organizations, up 400 to 500 percent since 2020. Industries tend to spend at that pace when something is being decided.
What the spending is near
The largest single item on the table is one provision in a 269-page draft. The Great American AI Act, released June 4 by Representatives Jay Obernolte and Lori Trahan, pairs new federal safety and transparency rules for AI developers with a three-year freeze on state laws that regulate how AI models are built. The freeze is not a new idea. The industry has sought a version of it since the Senate voted 99 to 1 to strip a ten-year moratorium out of last year’s budget bill. The Business Software Alliance supports the draft; Public Citizen and the AFL-CIO oppose it. The line between those two camps is worth reading slowly.
Whose problem it solves
The structure rewards a second look. Fifty state legislatures writing fifty different AI rules is the outcome the industry has spent years arguing against. One federal standard, shaped with its input and with state rules paused, is the outcome it has spent years arguing for. The safety obligations and the preemption arrive in the same bill. Which half of that bundle the spending was tracking is a question the disclosures let a reader work out without much help.
It is also the third entry in a sequence. The industry helped shape the text of the federal AI executive order, and the people who write AI policy keep moving into the labs. Money, text, and personnel have a way of pointing the same direction.
What sits closest to home
A freeze this narrow leaves most of what people deal with day to day untouched. State rules on AI in hiring, deepfakes, child chatbot safety, and algorithmic pricing govern how AI is deployed and used, and the draft leaves all of that with the states, alongside civil rights and consumer protection. What it pauses is the layer underneath, the state rules on how the models themselves are built. That layer is invisible to most readers and central to the companies, which is part of why the fight over it draws the spending it does.
The room where it happens
The people writing the rules face a quieter version of the same pressure. State legislators and attorneys general lose their lane the moment preemption passes. Federal staffers drafting the standards sit across the table from the best-funded lobby in the city, and often from former colleagues now on its payroll. Who remains in that room to argue the other side is a fair thing to ask, and an easy thing to overlook.
Where it stands as of late June
The Great American AI Act is a draft, not a law. It has not been introduced or voted on. The next AI lobbying disclosures land in the fall and will almost certainly run higher. Three things are worth watching: whether the Act is formally introduced, which members sign on after the money moves, and how the spending shifts around both.
None of this is illegal. Every dollar is reported, every meeting is logged, every bill is public. That is exactly why it rewards a close read. The record is sitting in the open, waiting for anyone willing to follow it from the check to the clause.
Correction, June 26, 2026: An earlier version of this piece said state protections on AI in hiring, deepfakes, child chatbot safety, and algorithmic pricing could be frozen by the three-year preemption. The Great American AI Act discussion draft preempts only state laws that regulate how AI models are developed, and it expressly preserves state authority over how AI is deployed and used, including those areas. The passage has been corrected.
FAQ
How much is spent on AI lobbying?
In 2025, lobbyists reported roughly $130 million for AI-related work, and one in four federal lobbyists now works on AI, up from one in nine in 2023. In Q1 2026, eleven top tech firms spent $20 million, about $226,000 a day.
What is the Great American AI Act?
A June 2026 bipartisan draft from Representatives Jay Obernolte and Lori Trahan that pairs federal AI safety rules with a three-year preemption of state laws governing how AI models are built. As of late June 2026 it is a draft, not law.
Who benefits from AI preemption?
The largest AI developers and platforms, who would face one federal standard instead of dozens of state laws. Civil-society and labor groups, from Public Citizen to the AFL-CIO, oppose it.
What does it mean for consumers?
The draft is narrower than it first sounds. State protections on how AI is used, including hiring, deepfakes, and child safety, stay with the states. The three-year freeze applies only to state laws that regulate how AI models are built, with a federal safety and transparency framework put in their place.
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Dean Ball helped write the federal government’s AI rulebook. In July, he starts work at OpenAI. That one sentence is the AI policy revolving door in miniature, and the door is spinning in a clear direction.
Ball served as senior policy adviser for AI and emerging technology at the White House Office of Science and Technology Policy, where he was a primary author of the administration’s AI Action Plan, the document that set federal expectations on chip exports, AI safety, and how Washington deals with the companies building frontier models. On July 6 he becomes head of a new OpenAI team called Strategic Futures, reporting to chief strategy officer Jason Kwon and working on catastrophic risk, recursive self-improvement, labor-market effects, and the relationship between frontier labs and governments. He keeps a non-resident fellowship at the Foundation for American Innovation. The same week, Noam Shazeer, who co-wrote the 2017 paper that made modern AI possible, left Google for OpenAI. One of those moves is talent. The other is governance.
OpenAI did not respond to a request for comment.
Here is the part worth sitting with: the AI policy revolving door is not new. The door between Washington and industry has been turning for decades, and it turns in both parties. During the Obama years, the Tech Transparency Project counted 258 revolving-door moves between Google and the federal government. The Pentagon version is older and larger, with hundreds of senior defense officials cycling into contractor boardrooms, a pattern the Project On Government Oversight has tracked for years. When Biden staffed his administration, advisers openly described technology firms as the new Goldman Sachs, the way that bank once seeded every Treasury. We covered the policy-text version of this in how the AI executive order got written, and the thinning line between state and company in Britain’s sovereign AI push. Ball is the AI era’s turn of a very old wheel.
That history is also Ball’s defense, and it is a fair one. Government needs people who actually understand the technology, and you do not get that understanding without moving talent in and out of the field. The door has always swung both ways. Someone who helped write a framework is not a regulator signing off on OpenAI’s compliance, and keeping a public fellowship is more transparency than most bother with. The distinctions are real.
The mistake is hunting for the villain. There isn’t one, and that is the whole problem. Power has stopped needing corruption now that it can simply hire the referee. The defense industry took generations to perfect this move, Wall Street took decades, and AI ran the same play in about three years, in the open, announced over press releases. What we are watching is a narrow class of people learning to write the rules and own the upside inside the same career, and calling the combination expertise. The public was never at that table. It only gets the bill.
For everyone outside this world, the takeaway is plain. The AI policy revolving door is why the rules about the AI in your bank, your hospital, and your benefits keep getting written by a circle of people who end up at the companies those rules cover. No one has to break anything for the public to lose its seat at the table, and that is a harder problem to fix than corruption, because nothing illegal ever happens.
Watch who moves next. The names leaving government for the labs are a better map of where AI policy is actually heading than anything published in the Federal Register.
FAQ
Who is Dean Ball?
Dean Ball was the senior policy adviser for AI and emerging technology at the White House Office of Science and Technology Policy and a primary author of the administration’s AI Action Plan. In July 2026 he joins OpenAI to lead a new team called Strategic Futures.
What is the AI policy revolving door?
The AI policy revolving door is the movement of people between the government roles that write AI rules and the companies those rules govern. The pattern is not unique to AI. It has long run between the Pentagon and defense contractors, and between the Treasury and Wall Street.
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The phone call came before the signing ceremony.
An earlier draft of Trump’s June 2 AI cybersecurity executive order would have given the federal government 90 days to review new frontier models before public release. David Sacks, Elon Musk, and Mark Zuckerberg called the White House to kill it. Sacks blessed a 30-day window, and the order moved forward on those terms. The signing went ahead Tuesday. Treasury Secretary Scott Bessent now has 30 days to stand up the AI cybersecurity clearinghouse the order created.
That was day one.
The 90-day version that died
The 90-day review was the headline restraint in the original draft. Three phone calls killed it. The replacement is voluntary and runs 30 days, and the class of “covered frontier models” subject to even that review will be defined through a classified benchmarking process at NSA and CISA. Companies will not know in advance whose models trigger it. The voluntary structure matters because there is no enforcement mechanism if a company decides its next release falls outside the covered class.
The order also instructs Treasury, Homeland Security, Defense, and the NSC to consult on the clearinghouse design. The Q1 federal lobbying record shows the companies were already inside that conversation. Six firms (Alphabet, Meta, Microsoft, Nvidia, Anthropic, and OpenAI) collectively employed 307 federal lobbyists in the first three months of the year. They reported $20 million in combined federal lobbying spend.
Altman went to the Hill the next day
Wednesday, Sam Altman flew to Washington. He met with White House staff, House Speaker Mike Johnson, Minority Leader Hakeem Jeffries, Senate Minority Leader Chuck Schumer, and Senator Bernie Sanders, whose draft plan would take half the equity of every frontier AI lab and channel it into a sovereign wealth fund. OpenAI used the trip to release what the company calls a blueprint for a durable federal AI framework. The single line in the blueprint that mattered to Altman was the call for a larger OpenAI role in the Commerce Department’s Center for AI Standards and Innovation. CAISI is the office that will write the safety standards every frontier developer has to publish.
Twenty-four hours after Altman asked for a seat in CAISI, Congress moved.
The bipartisan draft
Thursday, Representatives Jay Obernolte and Lori Trahan introduced “The Great American Artificial Intelligence Act.” Their co-sponsors include two more Republicans and two more Democrats. The draft preempts state laws regulating AI model development for three years. It requires any frontier developer with more than $500 million in annual revenue to publish a safety framework and submit to semi-annual third-party audits. And it codifies CAISI into statute, with $100 million in annual funding from 2027 through 2029. Exactly the office Altman lobbied to expand the day before.
The state-preemption clause is the part that travels furthest. As of this spring, 45 states had AI bills in motion. Arizona’s 2025 AI consumer-protection laws were already on a federal preemption track under Trump’s spring framework, as Laterstack reported in April. The 1,500 state-level AI bills the country has watched accumulate since 2024 now sit on a three-year clock, assuming the draft becomes law.
Anthropic, the other major frontier lab, spent $1.6 million on federal lobbying in Q1, up from $360,000 in the same quarter last year. OpenAI spent $1 million. Both record their largest-ever quarterly outlays in the disclosures.
Inside the room
Look past the 30-day window. The room where it got drafted is where AI policy actually gets made. Access to that room is measured in millions of dollars per quarter and in the willingness of senior executives to phone a White House on a Sunday. The companies in the room change administration to administration. The Biden White House’s October 2023 AI executive order routed industry consultations through NIST and OSTP. This one routes them through Treasury, NSA, and CISA. Different agencies. Same companies. Same room. The faces and the company logos rotate. The mechanism does not.
This is what makes the EO and the Obernolte-Trahan draft worth reading together. The order created a clearinghouse. The bill, twenty-four hours later, codifies the office that will write the rules the clearinghouse depends on. Twenty-four hours after the executive who would benefit most asked for a seat at the same office, in person, with the Speaker and the Minority Leader in his calendar.
That is how AI policy gets made in 2026. Three artifacts, three days, one channel.
What this means for the people not in the room
Policy staff already know the channel exists. The Q1 lobbying numbers are public and the meeting schedules get leaked. The people who do not know are the readers and constituents who experience AI policy as a finished product. Federal frameworks descend, state protections get preempted, and the design of the safety regime gets treated as a technical question rather than a political one.
The next visible artifact will arrive in 30 days, when Bessent’s clearinghouse stands up. Watch who staffs it. The names will tell you whether the channel grew or held steady.
Requests for comment
Representative Obernolte’s office did not respond to a request for comment about whether OpenAI or Anthropic provided input on the draft bill’s CAISI language. OpenAI did not respond to a request for comment on whether the company advocated for the 30-day window over the 90-day version. Laterstack will update this story if either responds.