In May 2025, New York State Governor Hochul signed Part X of New York’s annual budget, titled, “Personalized Pricing Transparency and Anti-Discrimination.” Part X, which took effect on July 8, 2025, sets disclosure requirements for the use of algorithmic pricing and prohibits the use of certain consumer data to set prices.
Key Requirements for Compliance with New York’s Pricing Law
As a result of this new legislation, companies that use “personalized algorithmic pricing” are required to disclose that prices were set by an algorithm using consumer data. Specifically, prices set using such algorithms must be accompanied by the following disclosure: “THIS PRICE WAS SET BY AN ALGORITHM USING YOUR PERSONAL DATA.” Part X defines personalized algorithmic pricing as “dynamic pricing derived from or set by an algorithm that uses consumer data … which may vary among individual consumers or consumer populations.” Consumer data includes any data that identifies or could reasonably be linked to a person or device, excluding location data.
Common examples of dynamic pricing include airline tickets, hotel reservations, ride-sharing apps, and concert tickets. To the extent companies engage in dynamic pricing using personal data, such as browsing patterns, shopping history, or consumer preferences, they must publish the disclosure near the price, in the same medium, and in a way that is visible and understandable to the average consumer. Notably, a company that relies only on location data to set prices is not required to include the disclosure.
Part X also prohibits companies from using certain data associated with protected characteristics to set prices or sell any good or service. The prohibition applies if it would result in certain groups missing out on “accommodations, advantages, and privileges,” or if the use of the data would yield differentiated prices. Notably, the law allows for targeted marketing using “protected class data,” as long as the marketing would not result in missed benefits (e.g., discount coupons) for groups differentiated according to variables that are part of New York’s definition of “protected class data.” “Protected class data” that may not be used in this way includes ethnicity, national origin, age, disability, sex, sexual orientation, gender identity and expression, pregnancy outcomes, and reproductive healthcare, as well as any other information that is a prohibited basis for discrimination under New York or federal law. Companies that collect protected class data may not combine these data with algorithmic pricing tools to create different prices for different people without the risk of violating New York law. A violation of this law subjects the company to civil fines and penalties, as well as private lawsuits to recover damages.
New York Law Challenged as a First Amendment Violation
On July 2, 2025, the National Retail Federation (NRF) sued to block the law, arguing that it violates the First Amendment rights of businesses by forcing them to use specific language. The NRF’s complaint sought to stay the implementation of the law, which took effect on July 8, 2025. As of the date of publication, a hearing date on NRF’s request for injunctive relief has not been set. The outstanding decision may result in a delay in the enforcement of the disclosure requirement, but the law remains in effect for the time being, and companies should implement its provisions for prices and sales efforts to New York consumers.
Personalized Pricing Tools Raise Consumer Protection and Antitrust Concerns
The New York law continues a recent trend of scrutiny on data-driven pricing practices. In January 2025, the FTC released its initial findings following a Rule 6(b) study on algorithmic pricing, which suggests that companies should expect increased scrutiny on the use of differential pricing tools. Consumer protection enforcers are focused on the risk of price discrimination based on protected characteristics, price gouging during emergencies or peak demand, and misuse of sensitive consumer data. Pricing tools that rely on private, nonpublic data are more likely to raise consumer privacy concerns than the use of publicly available data.
In addition to consumer privacy concerns, government enforcers have also sounded the alarm on antitrust risks from the use of third-party algorithmic pricing tools in particular. Notably, the New York disclosure requirement extends to companies using third-party pricing tools, which could speed up investigative efforts as antitrust enforcers and plaintiffs seek to find cases where competitors feed nonpublic data into a common pricing tool. Antitrust enforcers, including new leadership at the U.S. Department of Justice (DOJ), Antitrust Division, have recently highlighted that the improper use of pricing tools to engage in price-fixing or the anticompetitive exchange of information is a policy priority. Principal Deputy Assistant Attorney General Roger Alford recently remarked that “algorithmic sharing of confidential information on digital platforms should be challenged as a violation of the antitrust laws,” pointing to a statement of interest that the DOJ filed in an algorithmic pricing case in March 2025. He added, “If we do not take a strong stand now against algorithmic collusion, we will see this new form of price fixing destroying effective competition across a whole range of digital markets.”
Accordingly, companies using or designing third-party algorithmic pricing tools should seek legal counsel on the types of information they may include in data sets that train the model or dynamically update price. Companies should also take care to document the procompetitive benefits of using dynamic pricing tools, such as decreased prices for consumers. For an overview of risk factors to consider in using or designing an algorithmic pricing tool, see our checklist here.
Conclusion
Algorithmic pricing tools face increased scrutiny. As a result, New York’s Part X legislation marks a significant shift toward the regulation of algorithmic tools. Companies should assess the use of dynamic pricing schemes that rely on consumer data and issue disclosures for products and services in New York state. Companies should seek legal counsel for guidance on their use of third-party tools.
