On October 28, 2026, the Federal Trade Commission (FTC) issued Section 6(b) orders to nine companies requiring detailed reports on how they use personal data to set prices for consumers and compensation for workers. The orders follow Chairman Ferguson's earlier announcement of a planned study, which we previously covered, and the Commission's August 2026 proposed enforcement policy statement on personalized pricing. The Commission vote was 2-0 (Chairman Ferguson and Commissioner Meador).
The orders are compulsory process and must be answered within 45 days of service, with a mandatory meet-and-confer trigger at 14 days. Their scope is broad and cover companies’ methodologies for pricing, job assignments and compensation for gig workers. Almost all requests seek information and documents dating back to January 1, 2023 (and research projects back to January 1, 2021).
The Full Story:
The FTC's press release pointedly criticized the prior administration's approach, stating that the 2024 surveillance pricing study "examined only middlemen consultancies rather than the businesses that actually set prices" and that the agency "learned nothing about actual pricing decisions." The new orders go directly to operating companies setting prices for goods and services provided to consumers in the airline, ride share, food delivery, and retail industries. As Chairman Ferguson framed it, the Commission intends "to scrutinize the opaque methodology that some companies in these industries may be using to determine how much consumers pay or how much gig workers are paid for the same product or service."
The most significant expansion is the focus on labor. The press release notes that while airlines typically pay transparent wages, ride-share and food-delivery firms "may pay their workers shifting compensation offers based on opaque formulas," potentially driven by the use of driver personal data such as "phone usage or acceptance history for past offers." The order accordingly defines "Worker" to include gig workers and independent contractors—but expressly excludes salaried employees and hourly employees with fixed schedules—and reaches a third concept beyond price and pay: "Offer Assignment," meaning which workers are offered which jobs, in what order, and which jobs are hidden from an individual worker entirely.
Several definitions in the orders are noteworthy:
- "Personal Information" spans 24 enumerated categories, including geolocation, persistent identifiers, biometrics, household and family status, reactions to offered pricing or job offers, willingness to pay for a product or service, willingness to accept a job, and anything inferred or derived from those categories.
- "Pricing" and "Compensation" are defined to reach far past list price and base pay: coupons, discounts, promotions, loyalty offers, and, on the labor side, surge and boost multipliers, quests and streak bonuses, earnings guarantees, tips, reimbursements, deductions, and referral bonuses.
- "Super Intelligence" ("SI") is the order's term for what is commonly understood to mean artificial intelligence systems, and "Document" sweeps in chats, texts, direct messages, employee-owned devices, and content in collaborative work environments—expressly including generative SI platforms such as ChatGPT, Copilot, Grok and Claude.
What Companies Should Do Now:
- Recipients should immediately calendar the 14-day and 45-day deadlines, issue a litigation-style preservation notice covering chat, collaborative platforms and generative SI tool logs, and assemble a cross-functional team spanning legal, pricing, data science, HR/operations and privacy. Begin scoping discussions with Commission counsel early and evaluate any grounds to petition to limit or quash.
- Non-recipients in similar or adjacent industries should treat the orders as a diagnostic. Could your company clearly articulate a response as to which personal data inputs are used for pricing or compensation, who built the models, how they were validated, and what your company has told consumers and workers? Those are the questions the FTC’s orders are now asking under oath.
- All companies using personal information or SI in pricing goods or services should test their existing disclosures against the Commission’s proposed August 2026 enforcement policy statement, which focuses on consumers' reasonable expectations and on clear and conspicuous disclosure of the fact of personalization, its basis, and the personal information used. These companies should also be focused on compliance with the disclosure provisions of new state laws enacted in New York, Maryland, Connecticut, and New Jersey (as well as a new law awaiting the governor’s signature in New York) regarding “surveillance pricing” practices, defined differently than the FTC’s “personalized pricing.”
- All consumer-serving companies should anticipate further Congressional hearings and legislation focusing on personalized or surveillance pricing in the next Congress and whether and how such legislation could potentially impact their business’s pricing practices.
A 6(b) study is a fact-finding exercise and receipt of an order does not imply wrongdoing. But the Commission has paired this inquiry with a pending enforcement policy statement and an active Labor Task Force, and the record built here may inform both future policy and future enforcement.
To explore these issues further, we invite you to join us tomorrow for our upcoming webinar, “Surveillance Pricing Regulation: What's Pending, What's Next, and How Retailers Should Prepare.”
Click here to register and gain timely insights into navigating the evolving regulatory landscape.
- Partner
Paul Martino is a highly regarded public policy advocate and government relations partner with over 25 years of experience in Washington, DC specializing in privacy, data security, artificial intelligence (AI), ecommerce, and ...
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Kevin focuses on antitrust merger review, including pre-transaction counseling, merger investigations and merger litigations. He previously served as head of the FTC’s Mergers IV Division, where he led investigations in ...
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