New York’s Algorithmic Pricing Disclosure Law: Compliance, Controversy, and What Businesses Need to Know

A groundbreaking new regulation in New York is poised to transform the way businesses approach online pricing and transparency. The recently enacted New York Algorithmic Pricing Disclosure Act requires businesses to notify consumers when prices are set by algorithms using personal data. In this article, we examine the law’s requirements, the rationale behind them, compliance tips, and the ongoing legal and industry debates.

What Does the Law Require?

Effective July 8, 2025, any business operating in New York that customizes prices using algorithms based on personal or device-identifiable data must provide consumers with a clear disclosure:

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

This disclosure must be positioned adjacent to the price and displayed in a manner that is easily understandable and conspicuous to an average consumer. One of the most common instances where consumers have started to see the notice is in food delivery apps, such as DoorDash and Uber Eats, as shown in the screenshot from Uber Eats to the right.

Who Is Covered?

• All businesses (not just retailers) that use computational processes (“algorithms”) to set individualized prices for New York consumers.
• “Personal data” includes any information that can be reasonably linked to a specific individual or device.

Policy Rationale and Key Provisions

The law aims to increase transparency in the growing and sometimes contentious practice of dynamic and personalized pricing online. Key aspects:

• Required Disclosure: Prevents consumers from being unknowingly subjected to algorithmic price customization.
• Applicability: Applies to all points of sale where personalized prices are shown, including online platforms and in-store displays.
• Enforcement: Grants the state Attorney General enforcement authority, who may seek penalties for non-compliance.

Removal of Explicit Anti-Discrimination Provisions

An earlier version of Senate Bill S7033 (available here: S7033 Senate Bill – earlier text) contained explicit language prohibiting the use of protected class data to set prices for goods or services if (i) such use caused the withholding or denial of accommodations, advantages, or privileges accorded to others, or (ii) resulted in a price difference for individuals or groups based on protected class data.

However, this anti-discrimination prohibition was removed during the legislative process. The final signed budget bill, which enacted the Algorithmic Pricing Disclosure Act as Part X of the 2025 budget (available here: A3008C Final Signed Bill), does not include an explicit bar on using protected class data in pricing decisions.

Therefore, while the final law mandates disclosure requirements, it does not itself prohibit discriminatory pricing based on protected class characteristics. Such discriminatory pricing could still be addressed under other laws, notably New York’s Human Rights Law, which broadly prohibits discrimination in public accommodations and business practices.

Industry Pushback and Legal Challenge

Not everyone is supportive of New York’s new requirements. The National Retail Federation (NRF) and a coalition of other industry groups are actively challenging the law in federal court. Significant points of contention include:

• Overbroad Language: Critics argue the law could apply to nearly all personalized deals, discounted pricing, or loyalty programs, even when data isn’t sensitive.
• Compelled Speech: The NRF contends the mandated warnings are misleading, risk confusing consumers, and violate the First Amendment’s speech protections for businesses.
• National Implications: With dynamic pricing being widespread across digital and brick-and-mortar retail, this law may create substantial compliance burdens and conflicts with other state and federal statutes.

Best Practices for Compliance

In addition to other pricing and subscription compliance requirements, if your business offers goods or services to New York consumers, prepare now:

• Audit All Dynamic Pricing Models: Determine which pricing strategies use consumer data and would trigger disclosure.
• Update Website and Point-of-Sale Systems: Implement conspicuous disclosures whenever algorithms are used to personalize prices.
• Data Mapping and Controls: Review your use of personal data, such as through data maps, to ensure that if personal data is used in price setting, either directly or by inference, then disclosures are displayed.
• Monitor Legal Developments: Stay updated on ongoing litigation, as final requirements could change pending court decisions.

Looking Ahead

New York’s Algorithmic Pricing Disclosure Act sets a national precedent for online pricing transparency and is already influencing legislative debates in other states. Successfully complying will require careful attention to disclosure and ongoing monitoring of legal updates.

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