The Federal Trade Commission voted 2-0 on Aug. 19 to open a 30-day public comment window on a proposed enforcement policy statement warning that businesses using consumer data to set individualized prices without adequate disclosure may violate Section 5 of the FTC Act. The target isn’t personalized pricing itself, which the agency concedes it can’t ban outright. It’s the concealment.

Chairman Andrew Ferguson framed the consumer expectation plainly: shoppers should “expect it to be the same price that everyone else sees, not the retailer’s estimate of how much they are willing to pay.” That’s the willingness-to-pay modeling the statement puts in the crosshairs. Supply-and-demand shifts, regional cost differences, and rideshare surge pricing remain fine, per Paul, Weiss’s summary. Modeling what a specific customer will tolerate doesn’t.

The disclosure bar spelled out in Docket FTC-2026-1057 is exacting. Notices must be clear and conspicuous and cover the fact of personalization, its basis, and the data types used. “Specially selected” won’t clear it. The illustrative violations are pointed: a food-delivery app charging more when data suggests a customer can’t leave home; a grocer raising milk prices based on household children.

Holland & Knight reads the statement as flagging that AI pricing tools “heighten — not reduce — disclosure and governance obligations.” That inverts the pitch most surveillance-pricing vendors have been running. And the federal move doesn’t sit alone: Maryland and Connecticut surveillance-pricing laws take effect Oct. 1, 2026, arriving roughly two weeks after the comment window closes.

For small B2C sellers, uniform published pricing quietly becomes a marketable trust claim against platform incumbents whose margin models depend on the practice now under review. The FTC’s prior enforcement posture in the Cox Media–Mindsift settlement suggests the commission intends to build the record before it builds the case.

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