A Price to Pay: U.S. Lawmaker Efforts to Regulate Algorithmic Pricing is a report published by the Future of Privacy Forum (FPF) on August 18, 2025. It surveys state legislative activity on algorithmic and data-driven pricing during the first seven months of 2025, documenting a sharp rise in bill volume over the prior year.
Summary of findings
The report counts 51 bills in 24 states regulating algorithmic or data-driven pricing in the first seven months of 2025, up from 10 bills in all of 2024 — a roughly fivefold year-over-year increase. It groups the legislation into two main targets. Most bills address rent-setting software accused of facilitating collusion in housing. Others target surveillance-based pricing, meaning dynamic pricing set on the basis of personal data, location, or browsing history.
FPF frames the state-level activity against a federal backdrop in which the Federal Trade Commission's 6(b) surveillance-pricing investigation, opened under chair Lina Khan in 2024, released preliminary insights in early 2025 but was subsequently deprioritized under new FTC leadership. The report characterizes states as the primary venue for regulation as a result.
State examples
The report highlights several specific measures. New York's S 3008, signed July 8, 2025, imposes a disclosure mandate and prompted a First Amendment suit by the National Retail Federation (NRF). It also notes Delta Air Lines' announced plans for AI fare personalization, which the airline retracted under pressure from the Department of Transportation and members of Congress. Beyond New York, FPF identifies active algorithmic-pricing bills in California, Illinois, Massachusetts, Colorado, and Oregon.
Companion FPF research
The report is part of a series. The Price is Right: Responsible Uses of Personal Data in Pricing sets out an affirmative framework, and Data-Driven Pricing: Key Technologies, Business Practices, and Policy Implications (July 2025) provides a technical and business-practice survey.
The findings align with the federal-stall-plus-state-activity pattern described in Techno-Federalism: How Regulatory Fragmentation Shapes the U.S.-China AI Race and AI Compliance Industry / Regulatory Fragmentation. The report pairs with Premature Antitrust Standards in Algorithmic Pricing, which critiques emerging case law, and New York Algorithmic Pricing Regime and AG Enforcement, which documents the New York measure in detail.
Relationships
- supports: Algorithmic Pricing and Antitrust, New York Algorithmic Pricing Regime and AG Enforcement, Premature Antitrust Standards in Algorithmic Pricing.
- depends-on: Techno-Federalism: How Regulatory Fragmentation Shapes the U.S.-China AI Race, AI Compliance Industry / Regulatory Fragmentation.
- related: FTC 6(b) Study on AI Partnerships and Investments, Colorado AI Act (SB 24-205) and SB 25B-004 (Date Amendment), California SB 53 — Transparency in Frontier AI Act.