A rapidly expanding patchwork of state laws, proposed legislation, and attorney general investigations is reshaping the compliance landscape for companies that use consumer data and algorithms to inform pricing decisions. According to a recent overview by Kelley Drye, “surveillance pricing” remains loosely defined in policy debates, but regulators are converging on a set of legal theories and statutory tools that could materially affect how businesses deploy data-driven pricing strategies.
At the core of the current enforcement environment are three overlapping legal regimes: state consumer protection statutes, state data privacy laws, and state antitrust laws. Consumer protection laws, particularly prohibitions on unfair or deceptive acts or practices, are emerging as the most immediate source of risk. Many of these statutes already include pricing-specific provisions, such as bans on misleading price advertising or false representations about pricing, which regulators could apply to opaque or undisclosed personalized pricing practices.
State privacy laws add another layer of exposure by governing how companies collect and use personal data to inform pricing models. Antitrust enforcers are increasingly focused on the potential for algorithmic pricing systems to facilitate unlawful coordination among competitors, even absent explicit collusion, per Kelley Drye.
The most concrete legislative development to date comes from New York, which has enacted the first broad algorithmic pricing disclosure mandate. The state’s Algorithmic Pricing Disclosure Act requires businesses to clearly inform consumers when prices are set using personal data, mandating a conspicuous statement that the price was generated by an algorithm using that data.
The law has already faced a constitutional challenge from the National Retail Federation, which argued that the disclosure requirement violates the First Amendment. A federal judge rejected that claim, finding the requirement reasonably related to a legitimate government interest and not unduly burdensome. The case is now on appeal, setting up a potentially significant test of states’ authority to compel disclosures in algorithmic commerce.
Beyond New York, legislative activity is accelerating. Kelley Drye identifies more than 60 bills pending across over half of U.S. states, reflecting a broad push to regulate or restrict data-driven pricing. These proposals fall into two primary categories.
At one end of the spectrum are outright bans on personalized pricing practices, particularly where prices are individualized based on consumer data collected through automated systems or artificial intelligence. These bills often target specific sectors, particularly grocery and food retail, and may include carve-outs for cost-justified pricing differences, loyalty programs, or regulated industries such as insurance and financial services.
Related: New York Puts Businesses on Notice for Algorithmic Pricing
At the other end are transparency-focused measures that allow algorithmic pricing but impose disclosure requirements similar to New York’s law. Some proposals go further, requiring opt-out mechanisms or access to a non-personalized baseline price. Others incorporate additional restrictions, such as limits on the use of biometric or geolocation data, prohibitions on using minors’ or protected-class data, or even moratoria on enabling technologies like electronic shelf labels.
Enforcement is also ramping up. In January, California Attorney General Rob Bonta launched an investigative sweep targeting companies in retail, grocery, and hospitality sectors with significant online operations. The inquiry seeks detailed information on how businesses use consumer data in pricing, what disclosures they provide, and how they ensure compliance with competition and civil rights laws. No enforcement actions have been announced yet, but the inquiry signals heightened regulatory scrutiny.
For businesses, the practical implications are immediate. Regulators are not only scrutinizing pricing outputs but also the underlying data inputs and decision-making processes. Kelley Drye advises companies to conduct a comprehensive review of how prices are determined, including mapping data sources used in pricing models and assessing whether those inputs could raise discrimination or fairness concerns.
Equally important is evaluating disclosure practices and marketing claims around pricing. Companies should ensure that any representations about discounts, personalization, or price comparisons are accurate and not misleading under state consumer protection laws.
The firm also highlights the need to reassess discounting strategies to ensure they are structured in a way that aligns with evolving legal standards. Monitoring legislative developments at both the state and federal level is critical, given the scale at which new proposals are emerging.
For companies operating across multiple jurisdictions, the result is an increasingly fragmented compliance environment that demands proactive governance of pricing algorithms, data use, and consumer-facing disclosures.
