The Federal Trade Commission announced on 28 October 2026 that it had launched an inquiry into personalized pricing and compensation, approving the orders by a 2-0 vote. This is a study rather than an enforcement matter: the authority relied on covers studies without a specific law enforcement purpose.
The orders are issued under Section 6(b) of the Federal Trade Commission Act, which allows the Commission to compel a company to file a special report without opening a law enforcement matter. Each recipient must provide information showing whether pricing for a product or service, or compensation for workers, varies by individual, and identify the factors behind any variation, including loyalty programme participation and the analysis of personal data by superintelligence algorithms. The orders also require recipients to document the inputs, tools and procedures used to set or adjust prices and compensation.
The nine recipients are Delta, United and JetBlue in air travel, Lyft and Uber in ride hailing, DoorDash and Instacart in delivery, and Target and Walmart in retail. Each must now assemble a record of how it sets prices and worker compensation, covering the data inputs and the algorithmic tools applied to them. Businesses outside the nine that price or pay individually can read the order topics as the Commission's current statement of the documentation it expects to find.
Recipients have 45 days from the date they receive the orders. The orders do not allege a violation, and the Commission has not said when or whether it will publish findings. The factors named in the inquiry, running from loyalty programme participation to the analysis of personal data by superintelligence algorithms, mark out the range of pricing inputs the Commission now treats as worth recording.
Licentium advises technology, marketplace and financial services businesses on algorithmic pricing, personalisation and consumer protection exposure in the United States, the United Kingdom and the European Union. Work we undertake includes reviewing pricing and personalisation logic against consumer protection rules, preparing responses to regulatory information demands, and documenting the data inputs and algorithmic tools behind individualised prices and pay.