Third Circuit Revives Algorithmic Price-Fixing Suit, Deepening Circuit Split on Sherman Act Liability

The collision between modern artificial intelligence and century-old antitrust law has reached a critical juncture in the federal courts. For decades, the legal standard has been clear: if a human being cannot legally collect confidential pricing data from competitors and tell them what to charge, that conduct is a per se violation of antitrust law. The emerging question is whether replacing that human with a sophisticated software algorithm changes the legal calculus. The U.S. Court of Appeals for the Third Circuit answered that question on July 29, 2026, reviving a proposed class-action lawsuit against several Atlantic City casino-hotels. The unanimous ruling establishes that the shared use of algorithmic pricing tools can indeed constitute a horizontal price-fixing conspiracy under the Sherman Act, provided certain conditions regarding data sharing and adherence are met.[1][2][3][4]

The plaintiffs in Cornish-Adebiyi v. Caesars Entertainment allege that major hospitality operators, including Caesars, Harrah's, Tropicana, and MGM's Borgata, violated Section 1 of the Sherman Act by using Cendyn Group's "Rainmaker" software. The core allegation centers on a classic "hub-and-spoke" conspiracy adapted for the digital age. According to the complaint, the hotels (acting as the spokes) fed their non-public, real-time pricing and occupancy data into the Rainmaker algorithm (the hub). The software then allegedly pooled this sensitive commercial data to generate coordinated room rate recommendations, which the competing hotels accepted approximately 90 percent of the time. The plaintiffs argue this arrangement allowed the hotels to maintain artificially inflated room rates during periods of declining occupancy, confident that their competitors would not undercut them.[1][3][4][6][8]

A federal district court in New Jersey had previously dismissed the case, ruling that the plaintiffs failed to prove a "rim" connecting the spokes—meaning there was no evidence of a direct horizontal agreement among the competing hotels to fix prices. The lower court reasoned that parallel use of the same commercially available software was insufficient to prove collusion without direct communication between the competitors. However, the Third Circuit reversed that dismissal, finding that the plaintiffs had plausibly alleged a conspiracy. The appellate panel determined that the combination of parallel conduct, the exchange of non-public data through a shared agent, and the high rate of adherence to the algorithm's recommendations provided sufficient circumstantial evidence to infer collusion at the pleading stage.[1][3][5][8]

Crucially, the Third Circuit rejected the defense's argument that the hotels could not be fixing prices because they retained the ability to override the software. The court noted that prices can be considered "fixed" even if the conspirators retain final pricing authority and do not adhere to the recommendations entirely. The alleged 90 percent compliance rate, the court found, was enough to support an inference of an agreement to avoid competing on price. This ruling creates a direct and stark conflict with the Ninth Circuit's August 2025 decision in Gibson v. Cendyn Group. In that case, which involved the exact same software and similar allegations against Las Vegas hotels, the Ninth Circuit affirmed the dismissal of the suit, finding no plausible antitrust violation.[2][4][5][8]

Legal analysts point to a critical factual distinction that may explain the divergent outcomes between the two appellate courts. The Cornish-Adebiyi plaintiffs specifically alleged that the software pooled non-public competitor data to generate its recommendations, whereas the Gibson plaintiffs did not clearly make that allegation and ultimately abandoned their hub-and-spoke theory on appeal. Regardless of the nuances, the Third Circuit's decision is the first federal appellate ruling to allow an algorithmic price-fixing claim to survive a motion to dismiss. This significantly lowers the pleading bar for plaintiffs in jurisdictions that follow its reasoning, providing a clear roadmap for future antitrust challenges against AI pricing tools across various sectors.[2][4][5][6]

To understand the court's reasoning, one must look at how dynamic pricing algorithms actually function in practice. As described by the Third Circuit, these AI-reliant software systems automate pricing by ingesting vast amounts of data related to past, present, and future supply and demand conditions. The algorithms learn through iterative processes and pattern recognition, allowing vendors to adjust prices frequently and at lower transaction costs. While the court acknowledged there is nothing inherently wrong with using algorithms to engage more effectively in commercial activity, the legal danger arises when the software's training data includes non-public, competitively sensitive information sourced directly from horizontal competitors within the same market.[4][8]

In antitrust law, when plaintiffs rely on circumstantial evidence rather than a written agreement, they must demonstrate "plus factors" that elevate parallel conduct to the level of an illegal conspiracy. The Third Circuit identified several such plus factors in the Atlantic City case. Beyond the high adherence rate to the software's recommendations, the court pointed to the economic circumstances of the market. Specifically, the plaintiffs alleged that room rates rose while overall occupancy fell during the class period—an outcome that contradicts basic supply-and-demand economics and suggests that the hotels were acting against their independent self-interest in favor of a coordinated pricing strategy.[1][8]

The implications of the Third Circuit's ruling extend far beyond the hospitality industry. Algorithmic pricing tools have become ubiquitous across the modern economy, utilized in sectors ranging from residential real estate and commercial airlines to health insurance and retail. The legal boundary between competitive software use and illegal price-fixing will determine how much consumers pay for everyday goods and services. If courts broadly adopt the Third Circuit's reasoning, companies that rely on third-party pricing algorithms will need to rigorously audit their software vendors to ensure that their non-public data is not being pooled with competitors' data to generate market-wide pricing floors.[2][5]

The Cornish-Adebiyi decision does not exist in a vacuum; it is part of a rapidly expanding wave of litigation targeting algorithmic collusion. The most prominent parallel involves RealPage, a revenue-management software vendor for residential landlords. In 2024, the Department of Justice and multiple state attorneys general sued RealPage, alleging its software pooled non-public lease data to artificially inflate rents across the country. The legal theories tested in the casino-hotel litigation will directly impact the trajectory of the RealPage cases and similar lawsuits pending against health insurance clearinghouses and meat processing companies.[2][7]

The ruling arrives amid a broader crackdown on algorithmic pricing by federal enforcers, who view the practice as a major threat to competitive markets. The Department of Justice and the Federal Trade Commission have filed statements of interest in multiple cases, consistently arguing that software cannot be used to launder collusion and that the antitrust laws must adapt to new technologies. These agencies have emphasized that the absence of direct competitor-to-competitor communication—the traditional "smoke-filled room"—does not immunize companies from liability when they knowingly delegate pricing decisions to a shared algorithm trained on confidential market data.[2][7]

Following the Third Circuit's reversal, the Atlantic City case will now return to the federal district court in New Jersey for the discovery phase. This critical next step will allow the plaintiffs to demand internal documents, emails, and technical specifications from both the casino-hotels and Cendyn Group. Antitrust experts anticipate that the discovery process will focus heavily on the specific architecture of the Rainmaker software, seeking to uncover exactly how competitor data was segregated or pooled, and whether hotel executives explicitly understood that their participation in the platform would result in coordinated, market-wide price increases.[1][2][5][6]

With a clear circuit split now established between the Third and Ninth Circuits, the question of whether algorithmic pricing constitutes a per se antitrust violation is increasingly likely to head to the Supreme Court. Until the high court intervenes to resolve the conflicting appellate standards, businesses utilizing dynamic pricing software face a heightened risk of litigation, particularly if their tools rely on pooled, non-public competitor data to generate market recommendations. For consumers and antitrust advocates, the ruling represents a vital first step in ensuring that the digital economy remains subject to the same competitive safeguards that have governed American commerce for over a century.[2][5][6][7]