Algorithmic Pricing Bans Go Coast to Coast

Over the past three years, courts across the country have evaluated the use of pricing algorithms under the antitrust laws. In 2022, private plaintiffs filed the first of many civil cases involving algorithmic pricing against software provider RealPage and its customers (apartment property owners and managers), which have since been consolidated in a multi-district litigation in Tennessee.¹ RealPage has also faced lawsuits by multiple state attorneys general and a 2024 civil suit by the U.S. Department of Justice.² Private plaintiffs have brought additional suits alleging antitrust violations for use of algorithmic pricing software in other industries, including hotels and insurance.³

While courts have been grappling with the application of antitrust laws to algorithmic pricing tools, California and New York recently became the first states to amend their laws to directly prohibit certain uses of algorithms in pricing. As discussed in our February 2025 Advisory, these two states are in the process of amending their antitrust laws in ways that may increase risks for businesses.

California

The primary California antitrust law is the Cartwright Act, which is generally consistent with Section 1 of the federal Sherman Act. On October 6, 2025, Governor Gavin Newsom signed Assembly Bill 325, amending the Cartwright Act to make it unlawful:

• To use or distribute a common pricing algorithm as part of a contract, combination in the form of a trust, or conspiracy to restrain trade or commerce
• 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 algorithm⁴

The Cartwright Act 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 influence a price or commercial term.” Notably, the act does not distinguish between publicly available data (such as prices available on websites or through third-party publishers) and non-public data. The act applies to all industries that operate in California.

Nevertheless, as long as a company avoids coercion, the amendment does not materially change application of the Cartwright Act, since “a contract, combination in the form of a trust, or conspiracy to restrain trade or commerce” already is a violation of the law, including acts that facilitate the conspiracy. The amendment also clarifies the standard for motions to dismiss an antitrust complaint, which “shall not be required to allege facts tending to exclude the possibility of independent action.” Importantly, this change is not limited to cases involving the use of algorithms, but is applicable to all complaints under the Cartwright Act.

The same day, Governor Newsom signed an additional antitrust bill (SB 763) into law, increasing fines for violations of the Cartwright Act.⁵ The act now provides for a fine for corporate violators of the greater of $6 million (increased from $1 million) or twice the amount of pecuniary gain to the violator or pecuniary loss to the victim. This increase is significantly less than the $100 million corporate fine the bill’s sponsor originally proposed.⁶ The act also includes a new civil penalty of up to $1 million and increases the fine for individuals from $250,000 to $1 million, while maintaining potential imprisonment of up to three years.

New York

The primary New York antitrust law is the Donnelly Act, which also is generally consistent with Section 1 of the federal Sherman Act. On October 16, New York amended the Donnelly Act to become the second state to pass legislation concerning algorithmic pricing.⁷ The amendment is scheduled to take effect on December 15, 2025, 60 days after it was signed into law.

In contrast to California’s approach, New York’s law is specifically focused on the residential rental industry. The law prohibits the use of algorithms to set rental rates, making it unlawful to “set or adjust rental prices, lease renewal terms, occupancy levels, or other lease terms and conditions … based on recommendations from a software, data analytics service, or algorithmic device performing a coordinating function.”⁸ The law defines “coordinating function” to include “(i) collecting historical or contemporaneous prices, supply levels, or lease or rental contract termination and renewal dates … from two or more residential rental property owners or managers … (ii) analyzing or processing the information … including by using that information to train an algorithm; and (iii) recommending rental prices, lease renewal terms, ideal occupancy levels, or other lease terms and conditions to a residential rental property owner or manager.”⁹ Similar to California’s approach, the law does not appear to distinguish between public and non-public data.  What’s more, its prohibition expressly includes historical data, which generally is viewed as less competitively sensitive. 

The penalty for a violation of the Donnelly Act includes a maximum fine of $100,000 for individuals and a maximum of four years imprisonment. For corporations, the maximum fine is $1 million. But there may be additional risks down the road. As discussed in our February 2025 Advisory, New York legislators introduced a bill earlier this year that, among other things, would give private individuals the right to sue for violations of the act and provide for treble damages. The bill is still in committee.¹⁰

Other Jurisdictions

While California and New York are the first states to restrict the use of algorithmic pricing, multiple municipalities have acted to prohibit the use of algorithms in setting rents, including:

• San Francisco, Calif. (October 2024)¹¹
• Philadelphia, Pa. (October 2024)¹²
• Minneapolis, M.N. (April 2025)¹³
• Jersey City, N.J. (May 2025)¹⁴
• Providence, R.I. (May 2025)¹⁵
• San Diego, Calif. (May 2025)¹⁶
• Hoboken, N.J. (July 2025)¹⁷
• Seattle, Wash. (July 2025)¹⁸

Berkeley, California also passed a resolution banning pricing algorithms for rental properties in April 2025, but delayed implementation until March 2026 following a suit filed by RealPage. In May 2025, Colorado Governor Jared Polis vetoed a bill that would have imposed a similar ban on algorithmic rent pricing in that state.

Conclusion

The application of antitrust law to algorithmic pricing remains in flux, and cases have had varying outcomes: dismissed for failing to state an antitrust violation,¹⁹ allowed to proceed under the more permissive rule of reason,²⁰ and treated as a per se violation of the Sherman Act if competing defendants agreed to provide confidential data to an algorithm and to implement the prices recommended by the algorithm.²¹ Undeterred by this lack of clarity, the U.S. Department of Justice, as well as state attorneys general, continue to scrutinize algorithmic pricing across industries. Meanwhile, municipalities across the country continue to pass laws concerning the use of algorithmic pricing. Accordingly, companies should actively monitor developments in the regions where they do business to ensure they are not violating newly passed laws.

Despite the shifting sands in this area, there are measures companies can undertake to mitigate risk. First, companies should conduct due diligence on all software affecting pricing. Vendor agreements should adequately describe what inputs are used by the software to provide recommendations, as well as how the software uses the company’s data. Second, companies should retain the ability to modify or override any pricing recommendations provided by any software tool. Lastly, companies should consider seeking antitrust counsel to advise on ways to manage risk while allowing the business to use new technologies.

© Arnold & Porter Kaye Scholer LLP 2025 All Rights Reserved. This Advisory is intended to be a general summary of the law and does not constitute legal advice. You should consult with counsel to determine applicable legal requirements in a specific fact situation.