How States Are Taking on Algorithmic Pricing

2026-03-20 · Source: Tech Policy Press · Field: Legal & Regulatory — Legal Technology (LegalTech), Compliance & Risk Management, Regulatory Affairs & Government Relations · Depth: Intermediate, medium

Summary

Algorithmic pricing tools, which include both algorithmic price-fixing and surveillance pricing, are increasingly influencing consumer costs across various sectors like rental housing and groceries. In 2022, ProPublica exposed RealPage's role in coordinating rent increases, leading to a 2026 DOJ settlement. Consumer Reports documented in 2025 how Instacart's Eversight software inflated grocery bills by up to 23% for some users. While federal scrutiny has begun, with the DOJ suing RealPage and the FTC initiating a Section 6(b) study in 2024, federal regulatory commitment remains uncertain. Consequently, state legislatures have significantly increased activity, with 24 states introducing 51 bills in early 2025. New York enacted the first law targeting algorithmic price-fixing in rental housing (S.7882) and amended General Business Law 349-a for surveillance pricing disclosure, setting a precedent for state-level regulation.

Key takeaway

For CTOs and VPs of Engineering overseeing product development or compliance, you should proactively assess your company's algorithmic pricing practices against emerging state regulations. Understand the distinction between algorithmic price-fixing and surveillance pricing, and identify which data inputs feed your pricing algorithms. Prepare for potential re-architecture of systems to eliminate prohibited data uses, as compliance with new state laws, like New York's S.7882 and S.8623, will demand significant technical and institutional changes and may face legal challenges.

Key insights

States are leading regulatory efforts against algorithmic price-fixing and surveillance pricing amidst federal uncertainty.

Principles

• Algorithmic price-fixing reduces market competition.
• Surveillance pricing raises individual discrimination concerns.

Method

Detecting algorithmic price-fixing requires analyzing intermediary data sharing and market impact. Identifying surveillance pricing involves controlled participant studies or large observational datasets like the National Internet Observatory.

In practice

• New York's S.7882 prohibits coordinated rental housing pricing.
• New York's S.8623 establishes a private right of action for surveillance pricing.

Topics

• Algorithmic Pricing
• Algorithmic Price-Fixing
• Surveillance Pricing
• State Regulation
• Consumer Protection

Best for: CTO, VP of Engineering/Data, Director of AI/ML, Policy Maker, Legal Professional, Business Analyst

Related on AIssential

• Pricing Changes in Small Commercial Without Governance Debt - with Barbara Stacer of Utica National Insurance Group — Operational friction, not actuarial modeling, is the primary bottleneck in small commercial pricing deployment.
• The US state apparatus acting less like a neutral referee of markets and more like a growth function for a particular sector. “Take our stack, because our diplomats will fight your sovereignty rules.” — US statecraft increasingly functions as an industrial policy, promoting American AI and cloud services globally through diplomatic and development channels.
• The AI Subsidy Era is Over — The AI industry is ending its subsidy era, shifting to usage-based pricing due to rising agentic compute demands.
• How State Utility Regulators Are Shaping AI Infrastructure Deployment — State utility regulators are critical in determining the economic viability and deployment pace of AI infrastructure.
• Artificial intelligence will transform Brand Protection more decisively than any technology since the notice-and-takedown regime itself. — AI-driven clarity in brand protection will expose widespread infringement, creating a paradox for platforms balancing enforcement with revenue.
• Yes to California's Bill to Ban Surveillance Pricing — Surveillance pricing, customizing product costs based on personal data, harms privacy, equity, and transparency, necessitating legislative bans.

Open in AIssential →

Editorial summary, takeaway, and curation by AIssential. Original article published by Tech Policy Press.