A recent decision from the Southern District of New York signals that personalized pricing (often called surveillance pricing) laws face First Amendment headwinds. The case is RealPage, Inc. v. James, Case No. 25-cv-09847.

On September 29, Judge Valerie Caproni preliminarily enjoined a provision of New York’s new rent-setting law. The provision made it unlawful for landlords to set rents based on recommendations from software performing a “coordinating function.” The plaintiff, a software vendor providing those recommendations, challenged the law.

While this case looks like it’s about a niche rent regulation dispute, it’s also about algorithmically driven pricing recommendations. The plaintiff’s software analyzes data and recommends rents, i.e., prices, to landlords setting those rents. The court held that these recommendations are commercial speech, even though software generates them, and that the plaintiff is likely to show the provision fails the intermediate scrutiny that applies to commercial speech. The court called its decision a “close call.”

Many pricing tools work the same way. Thus, the ripple effects of this decision could reach the personalized pricing laws and class actions we’ve covered extensively on our blog, for example a mid-year roundup of new laws, the emergence of class action theories, and the FTC’s surveillance pricing report. The laws most exposed, at least under this decision, are those that potentially restrict pricing recommendations, whether by regulating the vendors who supply them or the businesses that act on them, e.g., New York’s One Fair Price Act.

Although RealPage is a preliminary ruling involving an antitrust-style statute, its reasoning goes beyond allegedly collusive rent-setting. With courts treating an algorithm’s pricing recommendation as commercial speech, a law that restricts that recommendation must survive intermediate scrutiny, which requires a reasonable fit between the law and its goals. Whether personalized pricing laws hold up under that test remains to be seen.