Technology experts and researchers are reporting that retailers are testing artificial intelligence to move beyond fixed pricing toward individualized costs for shoppers. Lindsay Owens, CEO of the nonprofit think tank Groundwork Collaborative, stated that AI allows companies to analyze personal data to determine the maximum amount a specific consumer is willing to pay. This shift would depart from the fixed-price model that has been a retail standard since the 1860s.
The technology builds on dynamic pricing, a method used for decades by travel and ride-share industries to adjust costs based on supply, demand, or weather. However, analysts with Cornerstone Research noted in a 2025 report that AI now empowers firms to process data with greater granularity, potentially leading to pricing based on specific shopper profiles rather than just market conditions.
In a trial reported by Groundwork Collaborative and Consumer Reports, the grocery platform Instacart used AI software to show different customers varying prices for identical items from the same store. The investigation found that grocery baskets containing the same products cost up to 23% more for some shoppers than others. Instacart disputed the findings, stating the calculated price gap reflected an \"atypical\" basket and that it does not use protected characteristics like race or gender to set prices.
Further research from Groundwork Collaborative claimed that Walmart has applied for patents on technology that could adjust prices based on a shopper's profile or the items currently in their cart. One example provided suggested a customer might see a different price for mayonnaise based on whether they already had tuna fish in their basket. Walmart's executive vice president of corporate affairs, Dan Bartlett, denied these claims in a public letter, stating the company does not and will not use personal information, income, or shopping history to set individualized prices.
The day-to-day impact involves a move toward what Owens describes as \"AI-enabled haggling,\" where the cost of a routine grocery or retail trip is no longer fixed but dictated by invisible data points. This could influence how shoppers interact with digital platforms and physical stores equipped with electronic shelf labels. For a household, this means the cost of a weekly grocery bill could change significantly based on their perceived willingness to pay, rather than a universal store price.
The knock-on effects include a potential loss of consumer trust and a shift in how regulatory bodies view consumer protection and price transparency. Jay Zagorsky of Boston University’s Questrom School of Business noted that merchants are unlikely to disclose these practices due to potential backlash. While Instacart announced in December that it would stop using AI to charge different prices for identical items, other retailers continue to develop similar tools. Future developments depend on whether these patented technologies are implemented in physical stores or remain limited to digital experimentation.