American retailers are adopting AI tools that help determine what shoppers will pay, drawing scrutiny over personal data, a lack of transparency in pricing, and the possibility that software could weaken competition.

Algorithms are increasingly used to recommend prices and predict demand, subsequently assessing customers’ responses. Personalized pricing can draw on information including location, income, and browsing habits, although its prevalence remains unclear.

The Federal Trade Commission has proposed warning businesses that undisclosed use of personal data to set individualized prices could violate consumer protection law. Legislators in at least 30 states have considered pricing measures this year.

Existing disputes illustrate the concerns. Target agreed to a $5 million settlement after California prosecutors alleged its app raised displayed prices when shoppers entered stores. The company denied personalizing prices through customer behavior. Amazon and McDonald’s separately dispute allegations that their pricing systems undermined competition.

Electronic shelf labels make price changes easier but do not establish that stores charge individuals differently. Walmart says its labels neither identify shoppers nor adjust prices based on weather or time of day.

A competitive market works best when shoppers can compare offers and take their business elsewhere. Personalized pricing makes that exponentially harder, as customers may see an apparently ordinary price without knowing someone else was offered less or that personal information drove the difference.

Retailers have always tried to estimate what customers will pay. That is nothing new. But AI could make these calculations more precise, subsequently leaving shoppers poorly equipped to challenge them. Information gathered for convenience or discounts may become a way to identify customers who are less likely to shop around.

Because these systems encourage competitors to follow price increases rather than undercut them, technology could weaken the pressure that normally restrains prices, raising another concern beyond privacy. The lawsuits described remain contested, though their allegations nevertheless concern whether retailers compete independently when setting prices.

Digital labels alone do not prove any of this, nor does every price adjustment disadvantage customers. The concern is that increasingly sophisticated pricing may leave consumers with less visibility into the bargain they are offered. Seller efficiency does not necessarily translate to a better deal for the buyer.

Grocery budgets become harder to manage when the price you see depends on information you cannot inspect. Comparing stores takes time, and comparing offers that may vary by account or shopping channel adds another burden. Loyalty programs also deserve closer scrutiny, since a discount may reward repeat business while giving the retailer a detailed record of your habits. The question is what else that information buys the company.

Shoppers should not have to become data analysts to understand a supermarket bill. Retailers introducing these tools should be able to explain when personal information affects an offer and make advertised prices easy to verify.

A market that expects consumers to exercise choice must let them see the terms on which that choice is being offered.