FTC Press Releases, read from an operations desk

Latest

FTC Signals Scrutiny of AI-Driven Personalized Pricing Tools

The FTC is seeking public comment on a draft enforcement policy statement about personalized pricing — the practice of setting different prices for different customers based on data, often via algorithms. It signals the agency's intent to scrutinize AI-driven pricing tools, even though no rule exists yet.

What changes for operators — If your sales stack includes an AI-assisted CPQ tool, dynamic quoting engine, or a pricing model that adjusts quotes based on customer firmographics, browsing behavior, or CRM data, this is the moment to document how those inputs are selected and whether any could be read as proxies for protected characteristics or opaque discrimination. Review your pricing logic now, log what data feeds it, and be ready to explain the rationale — not because a rule exists yet, but because comment periods like this typically precede guidance that regulators cite in later enforcement actions.

FTC Enforcement Action Targets False AI Marketing Capability Claims

If your company buys ad-targeting, lead-scoring, or customer-intelligence tools marketed as AI-powered, this case is a reminder to demand technical substantiation before signing contracts — vendors selling 'proprietary AI' features that sound too precise (like inferring intent from device audio) may be overselling capability, and you could be paying for a feature that does not function as described. It also applies in reverse: if your own sales or marketing team describes an AI feature in your product as doing more than it actually does — auto-qualifying leads, predicting churn with certainty, or analyzing customer sentiment from calls — you now have a live FTC enforcement example showing regulators will pursue deceptive AI marketing claims even without proof of consumer harm beyond the false claim itself. Any AI vendor evaluation should include a request for documentation on how the AI actually works, not just what it claims to output.

FTC Shuts Down $200M Credit Repair Scheme — What It Signals for B2B Lead Funnels

This case doesn't target B2B companies directly, and there's no direct regulatory obligation created here for a 10-200 person B2B firm. But it's a useful prompt to audit your own automated sales and billing workflows: if your outbound sequences, chatbots, or subscription-renewal flows make promises about outcomes, refund timelines, or guaranteed results, now is a reasonable time to confirm those claims are accurate and documented, since the FTC's enforcement posture on deceptive automated sales practices is visibly active. Operators running automated dunning, retention, or upsell sequences should also double-check that cancellation and refund paths are as frictionless as the sign-up flow — that asymmetry is a recurring theme in FTC actions against subscription and services businesses.

FTC Refunds Highlight Real Cost of Deceptive Automated Advertising Claims

If your company runs any automated pricing, promotional messaging, or fee disclosure through workflows — think auto-generated invoices, dynamic pricing rules, subscription upsells, or marketing copy pulled from templates — this case is a concrete reminder that "the system generated it" is not a defense against deceptive practices claims. B2B companies in the 10-200 person range increasingly automate quoting, billing, and customer communications precisely because it scales cheaply, but scale without a review layer scales liability too. The practical takeaway: any automation that touches pricing, fees, or claims about service (delivery times, discounts, "no cost" language, guarantees) needs a documented review step — even a lightweight one, like a monthly audit of auto-generated customer messages against actual terms. It's a cheap insurance policy against a very expensive correction later.