NEW YORK'S SWEEPING ALGORITHMIC PRICING REFORMS – WHAT RETAILERS NEED TO KNOW

On May 9, 2025, New York signed into law the Algorithmic Pricing Disclosure Act – a first-of-its-kind law mandating businesses to disclose the use of algorithmic pricing based on personal data. The law, which was slated to take effect on July 8, requires any business using algorithmic pricing based on personal data to set a price to clearly and conspicuously disclose next to the price the following label:

“THIS PRICE WAS SET BY AN ALGORITHM USING YOUR PERSONAL DATA"

While the law does not provide for a private right of action, it authorizes the NY Attorney General to seek injunctive relief and impose civil penalties of $1,000 per violation. Notably, the law does not require proof of any actual individualized consumer harm.[1]

Without providing a rationale, the law exempts price disclosures for the following categories:

(i) certain local delivery, ride-share, and taxi services that rely solely on location data to determine trip pricing;

(ii) consumer insurance products;

(iii) consumer financial products and services offered by most banks, trust companies, credit unions, savings and loan associations, and industrial loan companies; and

(iv) goods sold under a subscription-based agreement, provided the displayed price is lower than the price specified in the subscription agreement.[2]

Legal challenge and enforcement stay

On July 2, 2025, the National Retail Federation (“NRF”) filed suit to halt enforcement of the law.[3] The NRF argues the disclosure requirement violates retailers’ First and Fourteenth Amendment rights, compelling speech that mischaracterizes pro-consumer pricing practices and requests the court declare the law unconstitutional and enjoin its enforcement.[4] The court is scheduled to hear cross motions for preliminary injunction and dismissal on September 4, 2025.[5] In the interim, the New York Office of the Attorney General has agreed to stay enforcement of the law (including any retroactive enforcement) until 30 days after a final order on the preliminary injunction.[6]

Understanding algorithmic pricing

Algorithmic pricing refers to the use of automated systems that analyze various data inputs—such as a consumer’s purchase history, items in their online shopping cart, geographic location (e.g., ZIP code), and other voluntarily provided information—to dynamically adjust or personalize the price of a product or service.  Retailers use these models to offer targeted discounts and promotions, and this can result in lower prices for consumers. While the practice is not new, the scale and precision enabled by modern algorithms have drawn increased regulatory scrutiny.  An important distinction is that not all algorithmic pricing models rely on the use of consumer data or individual consumer characteristics.  Many dynamic pricing models rely exclusively on non-personal data, such as time of day or seasonality, inventory levels, or geographic region (at a general level). While still subject to consumer protection laws, these models tend to be less controversial and are not within the scope of this law.

Emerging state legislation

New York’s law is part of a broader trend. Several states are considering or have proposed legislation targeting algorithmic and dynamic pricing:

• Texas has proposed legislation classifying failure to disclose the use of algorithmic pricing as a deceptive trade practice.[7]
• Vermont’s state house is considering a bill to prohibit the use of dynamic pricing in the point-of-sale display price.[8]
• California seeks to prohibit surveillance pricing—defined as “offering or setting a customized price for a good or service for a specific consumer or group of consumers, based, in whole or in part, on personally identifiable information collected through electronic surveillance technology”—and would allow a consumer to bring an action themselves for injunctive relief.[9]
• Minnesota has proposed an outright prohibition on algorithmic pricing.[10]
• Ohio would require disclosure to a customer of the use of a pricing algorithm.[11]

For a comprehensive overview of AI-related legislation, please see BCLP’s AI Legislation Map.

Action items for retailers

1. Review pricing algorithms and inputs

The New York law places particular emphasis on the use of consumer personal data. Retailers should carefully document all data inputs considered in their pricing models, distinguishing between inputs that qualify as “personal data” and those that do not.  Consider leveraging generalized data—such as certain location data—to offer competitive pricing without triggering the law’s requirements. Additionally, ensure that algorithmic pricing methods are well documented, including the data inputs and their sources, to support compliance with future reporting obligations.

2. Audit data collection and usage practices

Retailers should collect only the consumer data necessary for uses permitted under applicable statutes. With a growing number of state privacy laws now in effect, many of which may intersect with algorithmic pricing regulations, retailers must be mindful of how consumer information is used. These laws may restrict certain data practices or require additional disclosures and consumer consent.

Track the purpose behind each data collection activity to ensure that only the appropriate type and amount of consumer data is gathered—this will also help justify its use if challenged. As algorithmic pricing laws continue to expand across the US, it is essential for retailers to proactively review and adjust their pricing strategies and disclosure practices to remain compliant with evolving legal requirements.

3. Prepare for disclosure requirements

To enable compliance with New York’s law, and potentially similar initiatives across the US, retailers should develop internal systems to flag items that are priced using algorithmic methods, enabling them to easily identify which products may require disclosure under applicable laws. In tandem, businesses should design and implement labeling mechanisms that comply with jurisdiction-specific requirements. Finally, retailers should actively monitor legislative developments in other states, as the regulatory landscape surrounding algorithmic pricing continues to evolve rapidly.

[1] N.Y. Gen. Bus. law Ch. 20 Art. 22-A Section 349-A.

[2]  Id. §§ 349-a(1)(d), (3).

[3] NRF | NRF Asks Federal Court to Block New York Algorithmic Pricing Law

[4] National Retail Federation v. James, Docket No. 1:25-cv-05500 (S.D.N.Y. Jul 02, 2025) (ECF 1).

[5] Id. (ECF 13).

[6] Id. (ECF 16).

[7] Texas SB 2567 Section 2(b)(35) “failure to disclose information regarding use of artificial intelligence system, or algorithmic pricing systems for setting of price.”

[8] Vermont H.371 Section 3(b) “a retailer shall not use electronic shelf labels or dynamic pricing to display the retail price or unit price of a consumer commodity offered for sale at a point of sale.”

[9] California AB 446.

[10] Minnesota SF 3098.

[11] Ohio SB 328 Section 1331.50(B)(1) requiring disclosure “To a customer, before the customer purchases the relevant product or service, that the price or a commercial term is set or recommended by a pricing algorithm.”