October 12, 2026 — Artificial intelligence is reshaping how supermarkets manage stock, offer discounts and set prices, creating new opportunities to reduce food waste while raising questions about consumer privacy and fair competition.
Retailers are increasingly adopting automated pricing tools, electronic shelf labels and AI-based shopping assistants. These technologies can help businesses respond quickly to market conditions, but experts warn that using detailed customer data to determine prices could make grocery shopping less transparent.
The central question is how retailers will use these systems: to improve efficiency and make products more affordable, or to personalise prices in ways that consumers may struggle to understand.
How AI Is Transforming Grocery Retail
Artificial intelligence is becoming an important tool for retailers seeking to improve inventory management and reduce losses from unsold or perishable products.
One example cited in the report is Kroger’s Flashfood platform, which helps identify eligible food products approaching their expiry dates and makes discounted items available to shoppers through an app. Such systems can help retailers sell products before they become waste while offering customers lower prices.
Electronic shelf labels are another development. Retailers including Walmart, Whole Foods, Amazon Fresh, Tesco, Morrisons and Asda have been associated with the adoption of digital pricing technology in different markets.
These labels allow stores to update displayed prices electronically rather than replacing paper tags manually. When combined with suitable pricing software, the technology can make price adjustments faster and easier to manage.
However, the ability to change prices rapidly does not automatically mean that a retailer is using personalised pricing. The purpose and rules behind each pricing system matter.
AI Is Expanding Beyond Pricing
Retailers are also exploring AI-powered tools to simplify the shopping experience, manage payments and help customers plan purchases.
The report highlights Sainsbury’s SmartLists, an AI-based tool designed to turn meal ideas or photographs into organised shopping lists. Such features can help shoppers plan meals and identify the items they need.
Facial-recognition payment systems have also been tested in selected retail settings, according to the report. These applications could make transactions more convenient, although biometric information introduces additional privacy and data-protection considerations.
Together, these developments show that AI is moving beyond back-office operations into services that directly affect how customers shop and pay.
What Is Dynamic Pricing?
Dynamic pricing refers to changing prices in response to factors such as demand, inventory levels, timing, operating costs or competitors’ prices.
The practice is not new. Airlines, hotels and ride-hailing services have long adjusted prices as market conditions change. Digital systems now make similar adjustments possible in retail environments, potentially at a much faster pace.
Three concepts are important to distinguish:
Dynamic pricing: Prices change in response to market conditions, such as demand or available stock.
Markdown pricing: Retailers reduce the price of selected products, often to clear excess inventory or sell perishable goods before expiry.
Personalised pricing: A price or offer may be tailored to an individual customer using information about that person’s behaviour or profile.
These approaches can have different consequences for shoppers. A clearly displayed discount on food approaching expiry is not the same as charging two customers different prices for an identical item because a system estimates that one is willing to pay more.
Could AI Help Consumers Save Money?
AI-based pricing can benefit consumers when it helps retailers identify products that can be sold at a discount before they expire or become unsellable.
For households, lower prices on suitable products can provide meaningful savings. Retailers may also benefit by recovering some value from stock that might otherwise be discarded.
Automated inventory forecasting can further help stores anticipate demand and make better purchasing decisions. If these systems reduce overstocking and food waste, they may improve operational efficiency.
However, savings are not guaranteed. The effect on shoppers depends on how a retailer uses the technology, whether discounts are passed on to customers and how frequently prices change.
Consumers may benefit most when reductions are clearly labelled, pricing rules are understandable and comparable products can be evaluated easily.
Why Experts Are Raising Consumer-Fairness Concerns
The growing use of consumer data in retail pricing has prompted concerns among economists and legal experts.
Miroslava Marinova, a senior lecturer in commercial law at the University of East London, has discussed the legal and commercial implications of these practices, according to the source report.
Retailers may have access to information such as previous purchases, browsing activity, shopping patterns and, where collected, location-related data. Combining such information with pricing algorithms could allow businesses to estimate what different customers might be prepared to pay.
Critics argue that this could weaken consumers’ ability to compare prices if the offers they see are not the same as those presented to other shoppers.
It may also raise questions about transparency, data protection and whether certain consumers could face less favourable offers because of the profiles created about them.
These risks depend on the specific system and its implementation. The use of AI does not, by itself, establish that a retailer is discriminating against customers or charging unfair prices.
The McDonald’s Dispute Highlights the Debate
The source report also refers to an antitrust lawsuit that accused McDonald’s of using an AI-driven pricing system to determine menu prices and overcharge customers.
McDonald’s denied using AI to calculate individual customers’ willingness to spend, according to the report.
The distinction is important: allegations made in a lawsuit should not be treated as proven findings. The case illustrates the wider debate about automated pricing, but the precise claims and the status of the proceedings should be checked against court records before publication.
More broadly, pricing systems that rely on customer data may attract greater scrutiny when their decisions are difficult to explain or when customers cannot readily determine why they received a particular offer.
Could AI Pricing Make Inflation Harder to Measure?
The spread of frequently changing and personalised prices could also create challenges for economists measuring inflation.
Traditional inflation measures generally track changes in the prices of representative goods and services over time. When prices fluctuate frequently—or vary between customers for the same product—researchers may find it more difficult to determine which price best reflects what households actually pay.
The source report refers to work by economists at the Bank of England examining the potential implications of personalised pricing.
The issue is not simply that prices change more often. It is also that a single advertised price may not fully represent the different prices paid by consumers. Statistical agencies may need suitable methods and data to capture these differences accurately.
The scale of this challenge will depend on how widely personalised pricing is adopted, how much prices differ between customers and what information is available to researchers.
What Grocery Shoppers Should Watch For
As AI becomes more common in retail, consumers can take practical steps to make informed purchasing decisions:
Compare the final prices of the same products across retailers and shopping platforms.
Check the conditions attached to app-based discounts and personalised offers.
Review privacy settings and understand what information a shopping app requests.
Look for clear explanations of discounts, promotions and any eligibility requirements.
Keep receipts when a displayed price differs from the amount charged.
Retailers, meanwhile, can build consumer confidence by explaining pricing policies, protecting personal information and ensuring that automated decisions are subject to appropriate oversight.
The Future of AI-Powered Grocery Pricing
AI could help grocery retailers reduce waste, improve stock management and offer useful discounts. At the same time, pricing systems based on extensive personal data could create transparency and fairness concerns if consumers cannot understand how offers are determined.
The long-term impact will depend on the balance between commercial efficiency and consumer protection. Clear pricing practices, responsible data use and effective oversight will be essential if retailers want customers to trust increasingly automated shopping systems.