A shift in federal artificial intelligence (AI) policy redefines how regulators approach innovation and enforcement. In this episode of "Clearly Conspicuous," consumer protection attorney Anthony DiResta examines how the Trump Administration's executive order on artificial intelligence and "America's AI Action Plan" have influenced the Federal Trade Commission's (FTC) current approach to AI regulation. Mr. DiResta highlights the FTC's decision to set aside its order against Rytr LLC as a key example of the agency's move away from abstract theories that may burden AI innovation while continuing to pursue companies that allegedly make deceptive claims about AI products, performance and capabilities.

The best compliance strategy is not waiting for enforcement to arrive; it's preparing for it before regulators ask questions. In this episode of "Clearly Conspicuous," Anthony DiResta interviews his colleague Benjamin Genn of Holland & Knight's Consumer Protection Defense and Compliance Team about the Federal Trade Commission's (FTC) proposed personalized pricing policy statement and its potential impact on consumer-facing businesses. Mr. Genn explains the FTC's disclosure-based approach to personalized pricing (also known as surveillance pricing), outlines the deception and unfairness theories underlying the agency's enforcement framework, and distinguishes lawful dynamic pricing based on broader market conditions from the individualized pricing practices targeted by the government's proposed enforcement focus. He also highlights the practical steps companies should take now, including auditing pricing algorithms, evaluating data use disclosures and assessing risks tied to vulnerability-based pricing practices before the September 18, 2026, comment deadline.

The strongest defense when the government asks questions is knowing your answers beforehand. In this episode of "Clearly Conspicuous," Anthony DiResta interviews his colleague Benjamin Genn of the Firm's Consumer Protection Defense and Compliance Team about the increasing scrutiny of surveillance pricing and how it differs from lawful dynamic pricing. After explaining the distinction between these two pricing models, Mr. Genn highlights a major airline's response to a congressional inquiry regarding its use of artificial intelligence (AI) in flight pricing. When three senators demanded answers about the airline's plans to expand AI use in flight pricing, the airline addressed lawmakers' concerns by producing documentation showing its systems use aggregate demand signals rather than individualized personal data. This example underscores the importance of understanding and documenting pricing algorithms and loyalty program data flows before inquiries arise from Congress, the Federal Trade Commission (FTC) or state attorneys general.