New York's One Fair Price Act Decision Looms Over Algorithmic Pricing

By Dec. 31, New York Governor Kathy Hochul must decide whether to sign or veto the state's proposed One Fair Price Act, a sweeping ban on individualized pricing across most industries. Laura Brett, a partner at Simpson Thacher & Bartlett LLP, calls it the clearest sign yet that legal risk from algorithmic pricing is growing for a widening range of professionals.

The risks aren't theoretical. In December 2025, Consumer Reports contended that Instacart was charging some shoppers up to 23% more for identical items. Backlash followed. Instacart halted the practice, but New York Attorney General Letitia James still demanded the company turn over its pricing records.

Algorithmic pricing uses software to set prices automatically, drawing on data that ranges from demand and inventory to personal signals such as browsing history, location or loyalty status. For marketers, individualized pricing is, in Brett's words, "the holy grail of price-points" — the right number, at the exact moment, to convert a browser into a purchaser. For regulators, it raises concerns about privacy, transparency, fairness and pricing power.

What's the difference between dynamic and personalized pricing?

The legal analysis starts with a core distinction. Dynamic pricing is the airline or hotel model: prices change based on inventory, demand or time, but every customer sees the same price. Brett calls that generally safer ground for companies providing goods and services.

Surveillance pricing — what marketers call "personalized pricing" — is different. Prices change based on the customer. That poses greater risk, not just for failing to disclose the practice but for using it at all, depending on what's being sold.

The major fault line is charging different customers different amounts for the same product. For advertisers, the issue can be tricky. A promo code sent to one audience segment, a retargeted offer that undercuts the price everyone else sees, or a members-only price can each put different prices in front of different people for the same item.

How broad is the regulatory response?

Dozens of bills, with different legal rationales, are pending across more than 20 states. A House Oversight committee probe has requested records from companies including Lyft and Uber over concerns about opaque pricing. The FTC has examined the practice through consumer-protection and antitrust lenses and has published a draft policy statement outlining how personalized pricing can be misleading or unfair.

The state-level patchwork varies widely:

• Some states ban personalized pricing in certain industries — mostly grocery or retail, though New York's pending ban is more sweeping.
• Others require disclosure, and some do both.
• Mandated disclosure language differs by state. New Yorkers may have seen: "This price was set by an algorithm using your personal data."
• Enforcement rights vary too: New Jersey allows private rights of action and, in some instances, treble damages.

States can also regulate algorithmic pricing through antitrust law, and that approach, alongside consumer-protection scrutiny, is being applied at the federal level amid rising affordability concerns. Truth-in-advertising rules apply directly. If one customer sees an item at $15 and another at $20, a customer could be misled that the advertised price is widely offered, or that a sale price reflects a true discount. Even promotions that save consumers money — discounts or coupons targeted at specific audiences — could raise flags as regulators probe which price each user actually saw and why.

Where does the risk sit inside marketing teams?

Professional teams often set the rules that drive pricing, and adoption tends to outrun analysis: a new pricing tool gets rolled out because it works, before anyone asks whether it crosses legal tripwires. Brett notes that's already a familiar pattern in advertising law, where marketers find ways to drive revenue and legal finds out after the fact.

A few practical distinctions stand out:

• Loyalty and group discounts pose lower risk if they're transparent and criteria-based.
• Pricing by device or location raises flags.
• Third-party vendors can elevate risk: a tool shared across competitors may suggest coordination.
• Disclosure requirements are creating UX and creative constraints, and can lead to expensive — and sometimes clumsy — retrofits.

What can marketers do right now?

Brett recommends four immediate steps:

• Audit. Identify what personal data feeds your pricing and which campaigns show different prices for the same item. Review what vendors do with the data, and check DSP and ad-platform targeting criteria for anything that doubles as a pricing input.
• Map. Know how you're pricing, and where. What's permitted in one jurisdiction may not be acceptable in another — and it's easier than you think for marketing to reach a national audience. Involve legal counsel from the start, as a thought partner rather than a final check. An ounce of prevention beats a regulator's cure.
• Recognize distinctions. Know which campaigns rely on dynamic pricing versus personalized pricing, since the two carry different levels of risk. Be clear about whether a campaign varies offers by audience or uses targeting to set prices.
• Keep your antennae raised. Technology is advancing rapidly and uncertainty is increasing. Legal considerations mean you can't solve just for speed.

The technology is capable and improving fast — so why tap the brakes when it's running so well? Because pace accelerates risk, and legal threats are rising. Professionals shouldn't disdain the technology; competitors won't. But there's a better choice than standing still or racing into trouble. Advance with caution, because regulators are watching.