New York Requires Disclosure of Personalized Algorithmic Pricing

Key Takeaways

• New York now requires businesses to disclose when they use personal data to generate individualized, algorithmically determined prices for consumers in New York.
• Several exceptions apply, including entities subject to insurance law, certain financial institutions, and certain subscription pricing practices.
• The New York attorney general has the power to enforce the requirement, with civil penalties of up to $1,000 per violation.
• Other states are considering similar or more aggressive legislation, suggesting a broader regulatory trend that is likely to resurface in 2026.

New York has enacted the Algorithmic Pricing Disclosure Act (NY General Business Law § 349-A), a first-of-its-kind statute requiring businesses to disclose when they use algorithms to set personalized prices for consumers based on the consumer’s personal data, often referred to as “surveillance pricing.” The law, which went into effect November 10, 2025, following the resolution of a First Amendment challenge, applies broadly to entities domiciled or doing business in New York and introduces new transparency obligations for companies that engage in dynamic, algorithmic pricing using personal data.

Overview of the Law’s Requirements

The statute applies to businesses that determine the price of a good or service using dynamic pricing (defined as “pricing that fluctuates dependent on conditions”) set by an algorithm that uses personal data. If such a business directly or indirectly states, offers, advertises, promotes, labels, or announces a price to a consumer in New York set by an algorithm using that consumer’s personal data, the business must include the following disclosure clearly and conspicuously along with the price:

THIS PRICE WAS SET BY AN ALGORITHM USING YOUR PERSONAL DATA

The Algorithmic Pricing Disclosure Act defines personal data broadly to include any information that identifies or could reasonably be linked, directly or indirectly, with a specific consumer or device. Examples of algorithmic inputs that could trigger the law’s disclosure requirement provided by the New York Attorney General’s Office include a consumer’s location, income, and previous shopping habits.

Exceptions and Limitations

Importantly, the Algorithmic Pricing Disclosure Act does not apply to all forms of dynamic, algorithmic pricing. Pricing models that vary based solely on nonpersonal data, such as supply and demand, time of day, or general market conditions, are not covered. Similarly, the use of aggregate data to train pricing models does not trigger the disclosure requirement unless the model also uses personal data of the specific consumer when setting the particular price displayed to them.

The act also includes several exceptions. Notably, businesses offering subscription-based pricing are exempt from the disclosure requirement when they provide a price that is lower than the price set in an existing subscription agreement. This may allow personalized subscription retention offers to be made without an accompanying disclosure. Certain regulated financial institutions and insurers are also excluded. In addition, the law does not apply to specific categories of transportation fares that are determined exclusively by standardized factors such as mileage and trip duration.

Enforcement

The Algorithmic Pricing Disclosure Act is enforced exclusively by the New York attorney general. Before bringing an action, the attorney general must first issue a written notice to the business identifying the alleged violation and provide the business an opportunity to cure. If the business fails to remedy the issue after receiving the notice, the attorney general may seek injunctive relief and civil penalties of up to $1,000 per violation. The act does not require proof that any consumer has been injured.

While the act does not create an express private right of action, it also does not “limit any other criminal or civil liability,” which leaves open the possibility of causes of action under other consumer protection laws.

Legislative Activity in Other States

Algorithmic pricing was a significant focus of state legislatures in 2025. On the antitrust front, both California and New York adopted laws related to the use of competitor data in algorithmic pricing. In California, AB 325 makes it unlawful under California’s Cartwright Act to collude using a pricing algorithm and to “coerce another person to set or adopt a recommended price or commercial term” using a “common pricing algorithm.” More narrowly, New York AB A1417B prohibits residential rental property landlords from colluding via the use of algorithmic rental pricing software and from using algorithmic software to set rental terms.

At the same time, a number of state legislatures considered bills that would regulate personalized algorithmic pricing, such as by prohibiting it outright (e.g., Colorado HB 1264) or requiring disclosures (e.g., Ohio SB 136). Other proposals target the use of biometric or other sensitive personal data (e.g., Massachusetts HB 99) or focus on specific sectors like grocery stores, restaurants, or ticket sales (e.g., New Mexico HB 285). Although these bills were not adopted in 2025, the profusion of legislative activity signals a growing focus on algorithmic pricing practices and the role of consumer data in price personalization that we expect to continue into 2026.