H.R. 8094: AI Foundation Model Transparency Act of 2026

Introduced Mar 26, 20263 cosponsors

Sponsor

Donald Beyer

Donald Beyer

Democrat · VA-8

Bill Progress

IntroducedMar 26
Committee 
Pass House 
Pass Senate 
Signed 
Law 

Latest Action · Mar 26, 2026

1/3

Referred to the House Committee on Energy and Commerce.

Force the biggest AI models to show their work

5 min readLast updated June 14, 2026

Why it matters

The AI tools you use every day reveal almost nothing about how they were built or where they fail. H.R. 8094 would force the largest models — those topping 10 million monthly users — to publicly disclose their training data sources, safety-test results, and known risks, with the FTC writing binding rules within a year of enactment.

H.R. 8094, the AI Foundation Model Transparency Act of 2026, would create a federal disclosure regime for the most powerful AI models. The Federal Trade Commission would have one year after enactment to write the rules.

The rules would only hit the biggest players. A company is covered if its model trips one of four triggers: it performs at levels that could pose serious risks; it has more than 10 million monthly users; it has more than 10 million monthly downloads; or it was trained on more than 10^26 computing operations. The bill also sets a floor for what counts as a "foundation model" in the first place — broadly trained, general-purpose, and built with at least 1 billion parameters.

H.R. 8094 Bill Summary

What H.R. 8094 actually does.

1

FTC writes binding transparency rules within a year

The Federal Trade Commission must issue the disclosure regulations no later than one year after enactment, working with NIST, the Commerce Department, the Office of Science and Technology Policy, standards bodies, academics, tech experts, and civil rights and consumer advocates.

2

Only the biggest models get covered

A company becomes a covered entity if its foundation model meets one of four triggers: high-risk performance, more than 10 million monthly users, more than 10 million monthly downloads, or training above 10^26 computing operations. A foundation model is defined as broadly trained, general-purpose, and built with at least 1 billion parameters.

3

Disclosures must be readable by people and machines

Covered companies must post the required information on their own sites in a plain, consumer-friendly format and feed a central FTC website in a machine-readable format. Personally identifiable and cybersecurity-sensitive material can go to the FTC without being publicly displayed.

4

Safety-test results, including for kids and seniors

Companies must disclose how their models perform on high-stakes questions — medical advice, weapons, national security, cybersecurity, critical infrastructure, elections, law enforcement, housing and loans, education, hiring, and public services — including effects on minors under 18 and seniors 65 and older.

5

Small and new firms get a three-month grace period

Small businesses and firms operating under a year get FTC guidance, machine-readable templates, and a one-time three-month grace period before penalties apply. During that window, a technically proficient FTC representative meets with the business to help it comply.

6

FTC must give 14 days' notice before enforcing

Violations are treated as unfair or deceptive practices under the FTC Act, but the agency must give a company at least 14 days' notice before taking enforcement action. The rules apply 90 days after they're finalized and must be reassessed every year.

Who benefits from H.R. 8094?

Anyone using major AI tools

You'd get clear, public information about what a model is for, where it falls short, when its knowledge stops, which languages it supports, and whether your inputs are collected or kept while you use it.

Researchers, auditors, and watchdogs

A central, machine-readable FTC database would put benchmark and risk-test results — across elections, cybersecurity, law enforcement, education, and hiring — in one searchable place instead of scattered across company blog posts.

Civil rights advocates and vulnerable groups

The bill requires test disclosures tied to loan and housing decisions, hiring, education, and public services, plus effects on minors under 18 and seniors 65 and older — evidence advocates could use to spot bias or harm.

Small AI firms and startups under a year old

Smaller companies get compliance templates, FTC guidance, a one-time three-month penalty grace period, and direct help from a technically proficient representative.

Who is affected by H.R. 8094?

Large AI model developers

Companies running models with more than 10 million monthly users, more than 10 million monthly downloads, or training runs above 10^26 operations would take on new disclosure and documentation duties.

Companies building on base models

Downstream developers can't point to a base model forever. They must link to that model's disclosure and comply themselves once they make significant changes, retrain, or adapt the system.

The FTC and technical regulators

The FTC would write the rules within a year, stand up a central disclosure site and a resources page, enforce violations, send Congress a report, and update the requirements annually.

Open-source AI projects

Fully open-source models are exempt from the disclosure rules — a carve-out that could sharpen debate over what counts as truly fully open-source.

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Tracking floor activity — no debate on H.R. 8094 yet. Updates when a legislator speaks on the record.

HR8094 Legislative Journey

1 actions

House: Committee Action

Mar 26, 2026

Referred to the House Committee on Energy and Commerce.

About the Sponsor

Donald Beyer

Donald Beyer

Democrat, Virginia's 8th congressional district · 11 years in Congress

Committees: Joint Economic Committee, Ways and Means

View full profile →

Cosponsors (3)

No new cosponsors in 81 days — momentum stalled

This bill has 3 cosponsors: 1 Democrat, 2 Republicans, reflecting bipartisan support. Cosponsors represent 3 states: California, New York, Pennsylvania.

1Democrat2Republicans·3 statesBipartisan

Committee Sponsors

Energy and Commerce Committee

24D30R
|0 signed54 not yet

0 of 54 committee members cosponsored

No committee members have cosponsored this bill

24 Democrats across this committee haven't cosponsored yet. Mobilize their constituents

H.R. 8094 Quick Facts

Cosponsors
3
Michael Lawler
Sara Jacobs
Brian Fitzpatrick
Committee
Energy and Commerce
Chamber
House
Policy
Commerce
Introduced
Mar 26, 2026

Referred to the House Committee on Energy and Commerce.

Mar 26, 2026

Constituent Resources

Get notified when this bill moves

Official Sources

H.R. 8094 on Congress.gov

The official bill page with full text, sponsors, and the Energy and Commerce Committee referral.

NIST AI Risk Management Framework

The voluntary framework covered companies would have to map their models against under the bill's disclosure rules.

NIST AI Resource Center

NIST's hub for AI RMF guidance, the companion playbook, and the generative AI profile referenced in trustworthy-AI disclosures.

FTC Artificial Intelligence

The Federal Trade Commission's AI page; the FTC would write and enforce the bill's transparency rules.

FTC Enforcement Authority

Overview of the FTC Act authority over unfair or deceptive practices that the bill uses to enforce violations.

White House Office of Science and Technology Policy

OSTP is named among the bodies the FTC must consult when writing the disclosure regulations.

H.R. 8094 Common Questions

Which AI models would H.R. 8094 actually cover?

Only the biggest. A company is covered if its foundation model has over 10 million monthly users, over 10 million monthly downloads, was trained on more than 10^26 computing operations, or performs at levels that could pose serious risks. The model must also have at least 1 billion parameters.

Would my AI chatbot have to tell me what data it was trained on?

If it's a covered model, yes. Companies would have to publish a plain-language summary of where their training data came from, how it was collected, and whether your inputs are retained while you use the model.

Are open-source AI models exempt from H.R. 8094?

Yes. Fully open-source models are exempt from the disclosure rules. The bill doesn't fully define "fully open-source," which is likely to be debated during the FTC's rulemaking.

What safety tests would AI companies have to disclose?

Companies would have to reveal how their models handle high-stakes questions: medical advice, weapons, national security, cybersecurity, critical infrastructure, elections, law enforcement, loan and housing decisions, education, hiring, public services, and effects on vulnerable groups.

Does H.R. 8094 specifically protect kids and seniors?

It singles them out for disclosure. Covered companies would have to report how their models affect vulnerable populations, defined in the bill as minors under 18 and seniors 65 and older.

Can AI companies redact sensitive details from public disclosures?

Yes, but with limits. Companies can redact material to protect cybersecurity, public safety, or national security, or to comply with federal law. Each redaction has to be briefly identified and justified.

Do small AI startups get a break under H.R. 8094?

Yes. Small businesses and firms operating under a year get FTC templates, hands-on help from a technical representative, and a one-time three-month grace period from penalties starting when they become covered.

Who would enforce H.R. 8094, and when would it take effect?

The FTC enforces it as an unfair or deceptive practice, but must give a company at least 14 days' notice before acting. The rules apply 90 days after the FTC finalizes them, and the agency must update them every year.

Based on H.R. 8094 bill text

H.R. 8094 Bill Text

PDF

To direct the Federal Trade Commission to establish requirements for making information available to the public about the training data and algorithms used in artificial intelligence foundation models, and for other purposes.

Source: U.S. Government Publishing Office

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