New York Legislature Passes Ban on Personalized Pricing

2026-06-11 · Source: The Data Advisor · Field: Legal & Regulatory — Compliance & Risk Management, Regulatory Affairs & Government Relations · Depth: Intermediate, short

Summary

The New York State Legislature recently passed the One Fair Price Act (S.8623B/A.9349B), a bill that bans businesses from using personal data, such as purchase history, browsing history, real-time location, income, or inferred household size, to generate individual prices for consumers. This legislation, awaiting Governor Kathy Hochul's signature until December 31, 2026, explicitly prohibits "surveillance pricing" and the collection, use, retention, or sharing of personal data for this purpose. While the Act carves out bona fide discounts like loyalty programs and standard promotions, it requires companies employing "dynamic pricing" algorithms—which adjust prices based on non-personal factors—to "clearly and conspicuously" disclose their use, price change frequency, and influencing conditions. The Act empowers the New York Office of the Attorney General to enforce violations with civil penalties up to \$5,000 for the first offense and \$20,000 for subsequent violations, or the profits earned. This represents a significant shift from New York's prior disclosure-only regime, aligning with a growing national trend seen in states like Maryland and Connecticut.

Key takeaway

For AI Product Managers or Directors of AI/ML operating in New York, this Act mandates a critical reassessment of your algorithmic pricing strategies. You must ensure your systems no longer use personal data for individualized pricing, shifting to dynamic pricing models that rely solely on non-personal factors. Update your disclosure practices for dynamic pricing to clearly communicate price change frequency and conditions. Failure to comply risks significant civil penalties up to \$20,000 per violation.

Key insights

New York's One Fair Price Act prohibits data-driven personalized pricing, shifting from a disclosure-only regulatory approach to an outright ban.

Principles

• Personal data use for individual pricing is prohibited.
• Dynamic pricing is permissible if not based on personal data.
• Transparency is required for non-personal data-driven dynamic pricing.

In practice

• Evaluate current data-driven pricing algorithms.
• Seek legal counsel for compliance guidance.

Topics

• One Fair Price Act
• Personalized Pricing
• Dynamic Pricing
• Data Privacy
• Algorithmic Pricing
• New York Legislation

Best for: CTO, VP of Engineering/Data, Executive, Legal Professional, Director of AI/ML, AI Product Manager

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Editorial summary, takeaway, and curation by AIssential. Original article published by The Data Advisor.