X.AI LLC v. Bonta
Issue
In *X.AI LLC v. Bonta*, X.AI argues that California AB 2013 — which requires generative AI developers to publicly post summaries of their training datasets across twelve enumerated categories — unconstitutionally compels disclosure of proprietary trade secrets and commercially sensitive technical information. The case presents the hard question of whether a state-mandated AI training-data disclosure regime triggers demanding First Amendment scrutiny as compelled speech, or whether it qualifies as ordinary commercial-speech regulation subject to the more permissive *Central Hudson* intermediate-scrutiny standard. The answer is not obvious because AI training-data summaries arguably occupy contested ground between the corrective-disclosure context in which courts are most tolerant of compelled speech and the forced revelation of proprietary editorial and technical judgments in which courts are least tolerant.
What Happened
X.AI filed these Excerpts of Record in the Ninth Circuit on May 14, 2026, as the mandatory record compilation accompanying its Opening Brief on appeal under Ninth Circuit Rule 30-1. The filing assembles the trial-court record — including the March 4, 2026 district court order denying X.AI's motion for a preliminary injunction, the hearing transcript, supporting declarations, and the State's opposition — that will frame the appellate court's review. The district court, applying the *Winter* preliminary injunction standard, denied relief on all three constitutional theories X.AI advanced: a Takings Clause claim failed for lack of particularized identification of X.AI's own trade secrets; a First Amendment compelled-speech claim failed because AB 2013 likely survives *Central Hudson* intermediate scrutiny at this early stage; and a vagueness challenge failed in part because X.AI's own pleadings used the statute's contested terms fluently. The Excerpts of Record preserve those rulings and the underlying evidentiary record for de novo legal review at the Ninth Circuit.
Why It Matters
This is the first appellate test of a state-level generative AI training-data disclosure mandate, and the Ninth Circuit's resolution of the *Zauderer*-versus-*Central Hudson* boundary in this context will carry significant weight as other jurisdictions consider similar AI transparency legislation. X.AI's most viable appellate argument centers on First Amendment proportionality: the district court itself signaled that the "limited utility of high-level dataset summaries for important consumer decisionmaking" is a genuinely open question that a fuller evidentiary record could resolve differently. If X.AI can persuade the Ninth Circuit that AI training-data disclosures are more analogous to compelled revelation of proprietary judgments than to corrective commercial disclosures — distinguishing the pharmaceutical pricing precedent the State relies on — the case could constrain how California and other states may structure AI transparency requirements going forward.
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