Retailers’ AI pricing push faces consumer distrust, regulatory scrutiny

As retailers introduce digital shelf labels and software that helps determine prices, consumers are questioning how much information businesses collect, and whether it influences what individual shoppers pay. Those concerns are bringing greater scrutiny to pricing technology already spreading across stores, restaurants and online marketplaces, the Associated Press reported.

For investors, these tools offer potential gains through lower operating costs, more effective discounts and faster responses to demand. But those benefits come with risks: opaque pricing practices can damage customer loyalty, invite lawsuits and trigger restrictions on how companies use shopper data. Retailers’ ability to explain their systems could become as important as the financial returns the technology delivers.

Much of the debate combines practices that serve different purposes. Dynamic pricing adjusts charges as market conditions change, while personalized pricing uses customer information to tailor offers or prices. Algorithmic systems can support either approach. Digital shelf labels, meanwhile, simply allow stores to update displayed prices electronically; their presence alone does not establish that a retailer charges different shoppers different amounts.

Walmart (WMT) says its electronic labels reduce employees’ workload and keep shelf prices current, without adjusting charges according to individual customers, weather or time of day. Research at one unnamed grocery chain found virtually no surge pricing after digital labels were installed. Frequent price adjustments can also benefit shoppers: web data company Decodo reported that approximately half the US price changes it tracked across several product categories in 2025 were reductions.

Personalized pricing raises more direct questions about privacy and fairness. A Federal Trade Commission staff report published in January 2025 found that intermediaries offering tools capable of tailoring prices and promotions served at least 250 clients. However, different prices do not necessarily reflect the use of personal data. Instacart ended pricing experiments after an investigation found disparities among shoppers, but said the tests assigned customers randomly to groups.

Policymakers are responding. According to the National Conference of State Legislatures, lawmakers in at least 30 states considered pricing legislation this year. Maryland, New Jersey and Connecticut enacted restrictions on using personal information to determine retail prices, with the scope and exceptions varying by state. The FTC has also proposed an enforcement policy warning that undisclosed use of personal data to set individualized prices could violate consumer protection law.

Competition concerns present another challenge. In its antitrust case against Amazon (AMZN), the FTC alleged that a discontinued pricing tool helped the company raise prices when rivals were likely to follow. Amazon disputes that characterization. A separate consumer lawsuit alleges that McDonald’s (MCD) pricing system uses nonpublic information from competing locations to coordinate prices; the company rejects the allegations and says the tool helps franchisees make their own pricing decisions.

Business adoption nevertheless appears to be advancing. In a Simon-Kucher survey of more than 2,200 executives across 28 countries and 39 industries, 41% reported using AI to gather market intelligence, including competitors’ prices, and 28% used it for real-time price optimization. The investment question is whether companies can translate that capability into sustained profits while preserving shoppers’ confidence that prices are understandable and fair, the AP reported.