Retail AI tools sharpen focus on grocery pricing risks in the U.S. and UK

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Retail AI and grocery pricing

Highlights

McDonald’s faces a federal antitrust lawsuit alleging it uses AI-based pricing to overcharge U.S. customers, though the company denies personalized pricing practices.
Kroger, Amazon Fresh, Walmart, Whole Foods, Tesco, Morrisons, and Asda are expanding AI-driven pricing tools and electronic shelf labels, with Kroger also using FlashFood AI for perishable discounts.
Regulatory pressures intensify as New York, Maryland, New Jersey, and Connecticut impose restrictions on personalized, data-driven pricing, raising concerns about inflation measurement due to individualized consumer pricing.

AI adoption expands across food retail

As reported by CNBC, supermarkets, fast-food chains and payments platforms are introducing AI-based systems that affect pricing, promotions and customer transactions across the U.S. and UK.

A federal antitrust lawsuit filed this week against McDonald’s alleges the company uses an AI-powered pricing engine to set menu prices across U.S. locations and overcharge customers for items including Big Macs and fries. McDonald’s denies it uses AI to determine what individual customers are willing to pay, saying it gives franchisees tools, research and recommendations to support their decisions.

Elsewhere, Kroger said earlier this year that it uses the FlashFood AI platform to mark down perishable goods nearing the end of shelf life and market them through an app. Electronic shelf labels are also spreading at chains including Kroger, Amazon Fresh, Walmart and Whole Foods, while UK grocers such as Tesco, Morrisons and Asda are also adopting the technology.

Retail experimentation is widening beyond shelf pricing. Revolut recently trials facial recognition checkout in selected coffee shops, and Sainsbury’s this week launches SmartLists, an AI feature that helps customers build shopping lists and find products from uploaded images or typed meal ideas.

Regulatory pressure and inflation concerns build

Experts say the broader issue is not dynamic pricing itself, which has long been used in sectors such as airlines, hotels and ride-hailing, but the growing volume of customer data that retailers can collect and combine with market information.

Miroslava Marinova, senior lecturer of commercial law at the University of East London, says dynamic pricing responds mainly to market conditions, while personalized pricing uses consumer-specific information to estimate willingness to pay. As those systems increasingly overlap, she warns shoppers may find it harder to know whether a price reflects wider market conditions or their own behavior.

Bank of England economists Clare Lombardelli and Rupal Patel say more sophisticated technology is making prices change more frequently and become more individualized, potentially pushing firms closer to charging the maximum a consumer is willing to pay. They also warn that this trend could make inflation harder to measure because consumer price data relies on representative price samples, while increasingly personalized prices may mean households experience different inflation rates.

Several U.S. states are already moving to limit data-driven pricing. New York requires most businesses that use personal data to set prices to disclose it clearly, while Maryland restricts food retailers and delivery services from using personalized, data-driven pricing to charge higher prices for certain food; New Jersey and Connecticut have also enacted measures targeting surveillance pricing.

AI’s growing impact on academic publishing has been driving a surge in manuscript submissions and intensifying concerns about quality control and rising screening costs across the industry. Our earlier article noted that major publishers are expanding human and technical review capacity while consolidation and licensing deals gain momentum as firms look to protect margins and defend the value of trusted research content.

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