Algorithmic collusion suit hits gas market after 2 DOJ settlements

For antitrust and regtech counsel, this case represents a pivotal moment: a direct challenge to algorithmic coordination armed with a new California statute that explicitly extends liability to pricing AI. The Kalibrate lawsuit will pressure courts to define the line between lawful price optimization and illegal conspiracy — a question left open after the DOJ’s settlements with RealPage and Agri Stats. As class actions multiply, law firms and compliance officers must reassess all third-party pricing tools.

A proposed federal class-action lawsuit filed in California on June 22, 2026, alleges that gas station operators — including major chains like Marathon and Circle K — unlawfully colluded through Kalibrate, an AI-powered fuel-pricing software platform, to artificially inflate retail gasoline prices statewide. The suit, brought under California antitrust law, describes Kalibrate as the “central nervous system for a conspiracy to extinguish retail price competition among gas stations.” The case is the latest in a series of high-profile algorithmic price-fixing actions, following DOJ settlements with RealPage (rental-housing software) and Agri Stats (meatpacking data-sharing) over the past year, signaling a dramatic escalation in how enforcers view AI-driven coordination.

“

The Kalibrate lawsuit will pressure courts to define the line between lawful price optimization and illegal conspiracy — a question left open after the DOJ’s settlements with RealPage and Agri Stats.

Kalibrate’s software, used by fuel retailers in more than 70 countries, ingests station-level cost, volume, and competitor data to generate “suggested” prices. Plaintiffs claim the platform discourages any price deviation warning that lowering prices would trigger a “downward spiral,” thereby systematically suppressing competition. The lawsuit maintains that by outsourcing pricing autonomy to a common algorithm, defendants engaged in a hub-and-spoke conspiracy that violates both California and federal antitrust principles, even if no explicit agreement to fix prices existed. The case leverages a 2025 California statute that explicitly extends antitrust liability to pricing algorithms, providing a direct legal hook that earlier federal cases had to construct through broader Sherman Act theories.

The timing is critical: California consumers already face some of the highest gasoline prices in the United States, exacerbated by global supply disruptions stemming from the Iran war. Average pump prices in the state hovered near $6 per gallon in mid-2026, placing added scrutiny on any mechanism that might be amplifying costs. The lawsuit seeks damages for a proposed class of all California gasoline purchasers since mid-2022, potentially encompassing tens of millions of drivers and billions of dollars in alleged overcharges.

The implications extend well beyond gasoline. The case crystallizes a regulatory inflection point: software platforms that set “recommended” prices across competing firms can effectively replace smoke-filled-room conspiracies with automated optimization. If courts accept the plaintiffs’ theory, any third-party algorithmic pricing service used by multiple market participants could face treble-damage exposure, reshaping how industries from hospitality to freight adopt dynamic pricing. For climate and energy policy, the allegation that AI is being used to prop up fossil fuel prices at the consumer level could galvanize public sentiment for aggressive electrification and oversight of algorithmic systems that retard the transition to renewables.