Algorithmic Pricing Attracts Widespread Scrutiny as FTC Seeks Comment on Personalized Pricing Policy Statement
On August 19, 2026, the Federal Trade Commission announced that it is seeking comments on a proposed enforcement policy statement concerning personalized pricing, which is the use of a consumer’s personal data to estimate what they are willing to pay for a product or service. The FTC’s announcement follows recent increased scrutiny by state regulators, courts, and Congress of algorithmic and automated pricing technologies, including personalized pricing, that influence consumer pricing decisions. This heightened attention is driven by a concern that these pricing technologies are increasing costs for consumers, particularly in essential markets such as groceries and housing.
Below is a high-level overview of the FTC’s proposal, as well as recent state regulatory, litigation, and congressional developments. These developments will be of particular interest to any business that uses customer data to personalize prices, discounts, promotions, or offers, including those in retail and grocery, e-commerce and food delivery, airlines and travel, hospitality, rideshare, ticketing, and digital platforms.
The FTC: Proposed Enforcement Policy Statement
The FTC is requesting public comments on its proposed enforcement policy statement on “personalized pricing,” which uses consumer data to tailor prices to individual consumers. This proposal suggests the FTC is developing a framework to evaluate technology-driven pricing and personalization practices across a wide range of industries, using its relatively broad Section 5 power to address “unfair or deceptive” practices. In particular, the proposal notes that businesses that do not disclose these practices to consumers may be in violation of the FTC Act.
Interested parties may file comments on the proposed enforcement policy for 30 days following its publication in the Federal Register.
State Action: New Jersey Expands Restrictions on Algorithmic and Personalized Pricing
Building on the momentum of broader state privacy and consumer protection initiatives, New Jersey recently enacted two measures that directly target the use of algorithms and data analytics in pricing decisions.
- The Fair Price Protection Act
Enacted in July 2026, the Fair Price Protection Act was adopted to address concerns of grocery affordability by classifying certain pricing practices as unlawful under New Jersey's Consumer Fraud Act. The law prohibits retail food stores and third-party delivery platforms from using consumer data, such as browsing activity, real-time location information, purchase history, or inferred demographic characteristics, to engage in individualized "surveillance pricing" or to use an “electronic shelving label.” Although the law provides an exemption for the use of loyalty program discounts, those exemptions are complex and include detailed disclosure and consent requirements.
- The FAIR Act
Shortly before enactment of the Fair Price Protection Act, New Jersey also passed the Forbidding the Algorithmic Inflation of Rent (FAIR) Act. The law prohibits landlords and property managers from using certain third-party algorithmic pricing tools and coordinating software to set rental prices, lease terms, or occupancy levels based on shared competitively sensitive information.
Together, these measures demonstrate a growing willingness among state lawmakers to regulate technology-driven pricing tools not only as a data privacy issue, but also as a consumer protection and competition concern.
Litigation Risk: Courts Continue to Grapple with Algorithmic Collusion Claims
Against this legislative backdrop, two major federal appellate decisions have now considered antitrust challenges involving hotel pricing software and reached different outcomes. Although the decisions reflect competing approaches to algorithmic pricing allegations, the cases arrived at the appellate courts with materially different allegations concerning competitor data, adherence to pricing recommendations, and the horizontal agreements among competitors.
In late July, the Third Circuit revived a putative class action alleging that Atlantic City casino-hotels conspired to fix room rates through a common revenue management platform. In Cornish-Adebiyi v. Caesars Entertainment, Inc., the court held that the complaint plausibly alleged a horizontal agreement based on allegations that (1) the platform used participating hotels’ real-time, non-public pricing and occupancy data to generate recommendations; (2) the hotels followed those recommendations 90% of the time; and (3) rates rose as occupancy declined, despite alleged economic incentives to reduce room prices. The court emphasized that it was accepting those allegations as true at the pleading stage, not determining how the software actually operated.
Last August, though, the Ninth Circuit reached a different conclusion in Gibson v. Cendyn Group, LLC, when it affirmed dismissal of a putative class action challenge to hotels’ separate software-licensing agreements. The court held that those agreements did not restrain competition because the complaint did not allege (1) that one hotel’s confidential information was used to generate recommendations for its competitors; (2) that the hotels had agreed to follow the recommendations; or (3) that the agreements otherwise limited their ability or incentive to compete. While the two cases reached different ultimate conclusions, a key distinction is that Cornish-Adebiyi involved allegations of a horizontal agreement (among hotels) alongside competitor data-sharing allegations and other “plus factors,” while Gibson addressed independent vertical software purchases – which the court described as “ordinary sales contracts” – without a preserved horizontal-agreement claim.
As a result, companies using third-party software for benchmarking, revenue management, or price optimization should continue to assess whether the platform uses non-public competitor data, preserve demonstrably independent pricing decisions, and scrutinize features or practices that encourage automatic acceptance of recommended prices.
Congressional Action: Investigations Focus on Consumer Affordability
Scrutiny of algorithmic pricing has also expanded on Capitol Hill.
Driven by concerns regarding inflation and the cost of essential goods, the Ranking Member of the House Energy & Commerce Committee recently launched investigations into the use of “surveillance pricing” in the grocery, consumer products, and air travel industries. The investigative letters requested detailed information regarding the use of artificial intelligence, consumer data, and automated systems to support individualized pricing decisions.
These inquiries follow similar investigations conducted earlier this year by the House Oversight Committee and signal growing bipartisan interest in whether data-driven pricing models may contribute to higher prices for consumers.
While congressional investigations do not themselves create binding legal obligations, they often serve as precursors to future legislation, regulatory action, or enforcement initiatives.
Looking Ahead
While states and Congress have driven many of the most recent developments, the FTC’s proposed enforcement policy indicates that it is looking to play a greater role in the oversight of algorithmic pricing practices. Businesses that use algorithmic and automated pricing technologies should track these developments closely.
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Wiley’s Privacy, Cyber & Data Governance team has extensive experience advising clients on algorithmic pricing, automated decision-making technologies, and the evolving legal and regulatory landscape governing data-driven business practices. Our team regularly counsels companies on compliance, enforcement, investigations, and litigation matters involving FTC scrutiny, state regulatory initiatives, and emerging consumer protection risks. For questions about this alert or if your business is interested in filing comments in the FTC’s proceeding, please contact the authors.
