On October 6, 2025, California Governor Gavin Newsom signed into law AB 325, marking a significant recalibration of California’s antitrust regime in response to algorithmic pricing practices. For companies operating in or targeting California, this development introduces new compliance risks as well as legal uncertainty.
Approved as part of a broader legislative package, AB 325 amends the Cartwright Act to impose new constraints on how companies may use, distribute, or coordinate pricing algorithms in California. In addition, the law, by modifying pleading standards for antitrust claims, lowers the bar for asserting an antitrust conspiracy.
At its core, AB 325 enacts two important changes to California’s existing Cartwright Act framework:
Pricing Algorithm Prohibition. The law imposes a new prohibition on the use of algorithms to coerce others to adopt pricing or other commercial terms:
It shall be unlawful for a person to use or distribute a common pricing algorithm if the 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 in the jurisdiction of this state.[1]
This new prohibition appears to create a new per se violation of the antitrust laws. However, whether this provision will ultimately affect the increasingly widespread use of pricing algorithms will likely depend on California courts’ interpretation and application of the term “coerces”: When does a user or provider of pricing recommendation software “coerce” another person to “set or adopt a recommended price”? What evidence will be required to show “coercion” in this context? Can a plaintiff rely solely on circumstantial evidence of coercion, and if so, what does that look like? Courts may look to prior decisions concerning other antitrust violations that make use of a coercion standard, such as tying claims, for help.
New Pleading Standards. AB 325 also adopts new revised pleading standards for antitrust conspiracies under the Cartwright Act. Under this provision, antitrust plaintiffs in California are no longer required to plead allegations that rule out the possibility of independent conduct, a requirement from the Supreme Court’s 1984 Monsanto decision and its later adoption by California courts. The new provision states that to allege a violation of the Cartwright Act, “it is sufficient to contain factual allegations demonstrating that the existence of a . . . conspiracy to restrain trade is plausible, and the complaint shall not be required to allege facts tending to exclude the possibility of independent action.”[2]
This provision appears to be, at least in part, a reaction to courts that have rejected claims of algorithmic collusion, which are often based on defendants’ parallel conduct combined with other indicia of conspiracy (or plus factors). By softening the requirements to plead a conspiracy, the law may result in more claims of algorithmic collusion proceeding to discovery. But the modification is not limited to pricing algorithms—it applies to all claims of agreement or conspiracy under the Cartwright Act.
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With AB 325 now law, companies that rely on or are considering pricing algorithms must re-evaluate their practices and controls to mitigate exposure. Many firms use vendor pricing platforms, SaaS tools, or AI models drawn from the same providers or datasets. Under AB 325, distributing or licensing a pricing algorithm to multiple clients may pose significant legal risks, even if the distributor is not orchestrating explicit collusion. Companies need to assess whether they or their vendors are “sharing” algorithmic logic or model parameters that could be deemed “common,” and whether the risk of others misusing those tools may pose too great of a risk.
In short: algorithmic pricing is no longer just a technical or business question — it is now squarely within statutory antitrust risk territory for companies operating in California.
[1] New § 16729 of the Business & Professions Code. The statute defines “common pricing algorithm” as any “technology, used by two or more persons, that uses competitor data to recommend . . . a price or commercial term.”
[2] New § 16756.1 (emphasis added).
