Third Circuit Revives Atlantic City Casino AI Price-Fixing Lawsuit, Setting Landmark Antitrust Precedent

Third Circuit Revives Atlantic City Casino AI Price-Fixing Lawsuit, Setting Landmark Antitrust Precedent

In a historic ruling on the intersection of antitrust law and algorithmic pricing, the U.S. Court of Appeals for the Third Circuit has revived a proposed class-action lawsuit accusing major Atlantic City casino-hotels and their software provider of conspiring to fix hotel room rates. On July 29, 2026, the Third Circuit reversed the District of New Jersey’s dismissal of the lawsuit, making it the first federal appellate court to allow algorithmic price-fixing claims to survive a motion to dismiss and establishing a monumental precedent for AI-driven pricing systems.

The Alleged Hub-and-Spoke Conspiracy

The plaintiffs, a group of consumers who rented guest rooms at five major Atlantic City casino-hotels—Caesars, Harrah's, Tropicana, MGM/Borgata, and Hard Rock—allege that the defendants engaged in a "hub-and-spoke" conspiracy in violation of Section 1 of the Sherman Act. The central "hub" of the conspiracy is Cendyn Group, LLC, which provides the "Rainmaker" dynamic pricing software, while the casino-hotels serve as the "spokes."

According to the complaint, the casino-hotels fed non-public, real-time room pricing and occupancy data into the Rainmaker algorithm. The software then pooled this confidential data across competing properties to generate coordinated room rate recommendations. The plaintiffs allege that the hotels followed these pricing recommendations approximately 90% of the time, allowing them to raise room rates in parallel even during periods of declining occupancy—conduct that would be contrary to each hotel's independent economic interest.

Why the Third Circuit Reversed the Dismissal

In September 2024, the U.S. District Court for the District of New Jersey dismissed the Consolidated Amended Complaint, ruling that the plaintiffs failed to allege a "rim" to the hub-and-spoke conspiracy—meaning they did not adequately plead a horizontal agreement among the competing hotels to coordinate their pricing.

The Third Circuit rejected this reasoning, finding that the plaintiffs’ allegations of parallel conduct and "plus factors" were more than sufficient to survive a Rule 12(b)(6) motion to dismiss. The court highlighted three critical elements:

1. Parallel Pricing and Declining Occupancy: The hotels contemporaneously used the same software to set prices, resulting in rising room rates during a period of falling occupancy, which strongly suggests coordinated pricing rather than independent competition.
2. Pooling of Non-Public Data: The algorithm did not merely rely on public market signals; it actively ingested and pooled each competitor's confidential, real-time pricing and occupancy data to generate recommendations for other competitors.
3. High Adherence and Limited Deviation: The hotels accepted Rainmaker’s recommendations roughly 90% of the time and could only override the suggested prices under "need and extreme circumstances," indicating a tacit agreement to delegate pricing authority to the shared algorithm.

Distinction from the Las Vegas Gibson Ruling

The Third Circuit’s decision represents a significant departure in outcome—though not necessarily in legal doctrine—from the U.S. Court of Appeals for the Ninth Circuit’s August 2025 decision in Gibson v. Cendyn Group, LLC, which affirmed the dismissal of a similar hotel pricing lawsuit in Las Vegas.

The key distinction lies in the specificity of the pleadings:

• In Gibson, the plaintiffs did not allege that the Cendyn software pooled or shared confidential competitor data to inform pricing, and the Ninth Circuit explicitly noted that its analysis might differ if such data-pooling were present.
• In Cornish-Adebiyi, the plaintiffs explicitly and detailedly pled that the Rainmaker algorithm relied on a pooled database of non-public, real-time data from competing hotels.

Legal and Compliance Implications

The Third Circuit's decision establishes that companies using third-party AI or algorithmic pricing tools face substantial antitrust exposure under Section 1 of the Sherman Act, particularly in highly concentrated markets.¹ For general counsels, the ruling underscores that outsourcing pricing to a third-party vendor does not shield a company from liability if the underlying algorithm pools competitor data to generate pricing recommendations.