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On October 6, 2025, Governor Gavin Newsom signed AB 325, amending California's primary antitrust law, the Cartwright Act, to make it unlawful for a business to use or distribute a common pricing algorithm in certain coordinated efforts. It also revises the pleading standard for Cartwright violations, likely raising litigation exposure.
Algorithmic pricing is an emerging legal frontier that businesses must handle with care. The line between optimization and collusion has never been thinner: what once may have been regarded as a sophisticated pricing strategy may now be unlawful if it aligns competitors' prices.
Modernizing State Antitrust Law
AB 325 updates California's antitrust regime in response to legislators' growing concerns that AI-driven and algorithmic pricing tools can facilitate tacit collusion between competitors without explicit agreements. Essentially, it prohibits competitors from using shared pricing software to align prices or terms based on competitor data, or from pressuring others to adopt recommended prices or terms.
First, AB 325 makes unlawful a business's use or distribution of a common pricing algorithm as part of a contract, combination, or conspiracy in restraint of trade. It defines "common pricing algorithm" as "any methodology, including a computer, software, or other technology, used by two or more persons, that uses competitor data to recommend, align, stabilize, set, or otherwise include a price or commercial term." "Price" includes not only consumer-facing pricing, but also employee or independent contractor compensation. "Commercial term" includes, without limitation, level of service, availability, or output.
Separately, the law imposes liability "if a person coerces another person to set or adopt a recommended price or commercial term recommended by the common pricing algorithm for the same or similar products or services." This provision aims to address situations where a dominant firm or platform uses its influence or contractual leverage to push others into adopting algorithmic recommendations.
Lower Pleading Bar for Alleged Cartwright Act Violations
AB 325 also amends the pleading threshold for private plaintiffs in Cartwright cases. A complaint now need only to allege plausible facts showing the existence of a contract, combination, or conspiracy to restrain trade.
Previously, plaintiffs alleging price-fixing or collusion faced a high pleading threshold, akin to the federal Twombly standard, under which they were required to plead facts excluding the possibility of independent action. Now, a plaintiff no longer needs to show at the outset how companies communicated or coordinated; parallel conduct plus a plausible link, such a shared algorithm or data source, may be enough to proceed to discovery.
This shift may significantly increase litigation exposure for businesses that rely on shared data, pricing vendors, or third-party technology to set prices.
Algorithmic Pricing Is Now A Highly Regulated Practice
Regulators and lawmakers have closely scrutinized algorithmic pricing in recent years. In July, New York's Algorithmic Pricing Disclosure Act began requiring businesses to prominently disclose when a price was algorithmically set using personal data. The law is temporarily enjoined pending a constitutional challenge by the National Retail Federation. Federally, the United States Department of Justice has filed Statements of Interest in algorithmic pricing cases and brought suit against RealPage, a property management software provider accused of providing unlawful apartment pricing algorithms.
Clearly, algorithmic pricing is, and will remain, a regulatory priority. Accordingly, businesses must take particular care when deploying or using pricing technologies.
Key Takeaways for Businesses
- Audit and monitor pricing tools. Businesses using third-party pricing tools, especially those that use competitor or market data, should ensure that outputs do not unlawfully recommend or align prices among competitors. Vendors distributing algorithmic pricing solutions may also face liability if their software facilitates coordination among competitors.
- Review vendor contracts and marketing. Ensure algorithmic recommendations are framed as nonbinding and optional to avoid the perception of coercion.
- Evaluate HR and compensation systems. "Price" includes employee or contractor pay, HR systems that recommend or align compensation levels may also create exposure.
The new frontier is algorithmic price-fixing, which can attain uncompetitive ends with greater efficiency and scale and yet is even more difficult to detect, let alone prove in court.
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