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Law / United States

AI Labeling Act of 2026

S. 4915, 119th Congress

In committee, dated , as of .

An AI transparency rule binding private bodies.

Obligation class
Disclosure, Content labelling
Audit expectation
none
Setting the rule reaches
General

Where it has got to

The text described here is S. 4915 as introduced in the Senate. That print is S. 4915 IS, published .

Locally, this stage is referred to the Senate Committee on Commerce, Science, and Transportation.

The stage above is recorded at www.congress.gov.

More on this stage

Introduced and referred on , with no committee action recorded.

What it requires

  • Introduced and referred to committee with no vote taken, so this is a bill to watch rather than a duty to meet
  • As introduced it would require a visible disclosure on AI-generated image, video, and audio content
  • It would also require a machine-readable provenance record naming the system used and the time the content was created

These lines are LexLint's reading of the law's text.

In the frameworks

NIST AI RMF
  • MEASURE 2.8Risks associated with transparency and accountability – as identified in the MAP function – are examined and documented.
NIST AI 600-1
OWASP Agentic Top 10
  • ASI09Human-Agent Trust Exploitation
MIT mitigations Draft
  • 2.4Content Safety Controls
  • 4.1System Documentation
  • 4.2Risk Disclosure
  • 4.6User Rights & Recourse
FINOS AIGF
ETSI EN 304 223
  • 5.1.3-2Threats developers cannot resolve are passed to operators and on to end-users.
  • 5.3.1-1Users told where and how their data is used, accessed and stored, with developers informing operators.
  • 5.3.1-2.1That guidance covers proper use, limits and likely failure modes.

Our reading of where this law's duties sit in each framework. It never says that running a control meets the law. How we read a framework against the law

Identifiers refer to ETSI EN 304 223 V2.1.1 (2025-12), © ETSI 2025, all rights reserved. ETSI owns the standard; no ETSI text (titles or sentences) is reproduced here. The standard is free to download from ETSI.

If you get it wrong

Criminal exposureNo

Penalty structure

As introduced, Section 2(d)(1) treats a violation of the disclosure duty as a violation of an FTC Act rule defining an unfair or deceptive act or practice under 15 U.S.C. 57a(a)(1)(B), the same chain COPPA and the TAKE IT DOWN Act use, which would draw 15 U.S.C. 45(m)(1)(A)'s civil penalty: a nominal $10,000 per violation, currently adjusted for inflation to $53,088 per violation (2025 figure) by 16 CFR 1.98.

Rule
Per violation only
As of
Currency
USD
Per violation unit
Violation
Per violation amount
53,088

Who enforces it

Enforcement body

As introduced, Section 2(d) would have the Federal Trade Commission enforce the visible AI-content disclosure duty as an unfair or deceptive act or practice under 15 U.S.C. 57a(a)(1)(B); a separate anti-circumvention prohibition in Section 3(a) would be enforced by the Attorney General of the United States (Section 4), a State attorney general as parens patriae (Section 5), and, for platform-to-platform harm, private civil actions (Section 6).

Settledness

As of
Open questions
  • When does the use of a generative artificial intelligence system satisfy the test that it "materially alters, adds, or removes" the meaning or significance of content under section 8(4)(A) of S. 4915?
  • Which services "predominantly provides a forum for user-to-user sharing or searching of content" under section 8(5)(A) of S. 4915, for example a generative AI service that also lets users share its outputs?

What it makes you log

Logging duty

Sec. 2(a)(1) requires a visible label and a machine-readable disclosure embedded in the covered AI-generated content itself (the system and version, and the date and time of creation), with detection tools; Sec. 2(b) has platforms keep that disclosure intact, and Sec. 2(c) requires a chatbot disclosure. The disclosure travels with the content rather than being kept by the provider as a separate log, and no section states a duty to create, keep, or later produce a record of a disclosure. Enforcement is by the Federal Trade Commission under the Federal Trade Commission Act (Sec. 2(d)) and by civil action for tampering with a disclosure (Secs. 4 to 6), which turn on the content and not on a kept record. As introduced; the bill binds nobody yet.

Kind
None
As of

What this law does

Drafted with AI

Drafted with AI from the cited sources under the direction of UnGovr staff. UnGovr holds editorial responsibility for this page. How this site is made

Research summary

Legal information, not legal advice. This is LexLint's own research summary of a public legal source, and it creates no attorney-client relationship. For decisions that matter, consult qualified counsel in the relevant jurisdiction. About LexLint

As introduced, would require providers of generative AI systems to attach a visible disclosure to AI-generated image, video, and audio content, plus a machine-readable provenance record of the system used and the creation time, and would direct developers and major social media platforms to cooperate so users can identify content authenticity.

Introduced by a bipartisan group of senators and referred to the Senate Commerce Committee, with no committee vote or floor action found; it is the closest thing to a marquee federal AI-labeling proposal as of the date shown.

When LexLint raises it

When your app profile says your app generates audio with AI, generates images with AI or generates video with AI.

Back to the example  ·  Lint your app

Page updated .