The food industry is learning to price with AI – consumers are still shopping with a calculator
Published Oct 03, 2026 • 4 minute read

Artificial intelligence is everywhere, including the food supply chain, where established habits and thin margins can make technological change difficult.
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Precision agriculture, machine learning and robotics are advancing, but adoption remains uneven. Investment capacity, data quality and access to skilled workers determine who moves ahead and who falls behind.
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The Wendy’s controversy illustrates how sensitive consumers are to these changes. In February 2024, its CEO discussed plans to test dynamic pricing. Following a public backlash, the company clarified that it would not raise prices during periods of peak demand.
The episode exposed a concern: consumers do not want buying lunch to become an exercise in guessing when prices might change.
More than two years later, the industry’s technological ambitions are growing. McDonald’s recently announced approximately US$8.5 billion in support for restaurant modernization through 2036. The program includes operational improvements and a system incorporating generative AI. This is a broad modernization package, rather than funding devoted exclusively to automation.
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McDonald’s also uses a pricing engine to recommend prices for individual restaurants. Restaurant-specific recommendations do not automatically mean that a burger’s price changes according to the time of day or the length of the lineup. Algorithms can inform pricing without making it fluctuate in real time.
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Businesses moving ahead with AI
For McDonald’s, the economic rationale is straightforward: improve productivity, understand demand and strengthen profitability. But what does the consumer get? Are Canadians equipped to deal with a food industry increasingly powered by AI?
Public anxiety is understandable.
Bill Gates recently warned that malicious uses of AI could lead to events causing as many as a billion deaths. That is an extreme risk scenario, rather than a forecast. For most shoppers, immediate concerns are more practical: prices, privacy and informed choice.
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Businesses are moving ahead. Over the past twelve months, Burger King announced its Patty assistant to support employees and improve operations. Walmart unveiled a partnership with OpenAI to enable shopping through ChatGPT. Loblaw announced a collaboration with Google to develop conversational shopping and expand its use of AI.
These initiatives demonstrate commercial interest. Consumer acceptance will depend on benefits shoppers can actually see.
ChatGPT became publicly available, free of charge, on Nov. 30, 2022. Next month marks its fourth anniversary. AI existed long before, but that launch made its capabilities tangible for millions. Adoption has since accelerated while governance tries to keep pace.
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Potential gains for food industry substantial
For the food industry, potential gains are substantial. Better demand forecasting can reduce surpluses, limit waste and improve availability. More precise inventory and transportation management can lower costs and help businesses respond faster to disruptions.
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The central economic question is who captures those gains.
Lower costs can improve margins, finance investment or support competitive prices. Their distribution will depend partly on competition and consumers’ ability to compare offers. Productivity gains are welcome. Whether they make food more affordable remains an open question.
Pricing will likely remain the most contentious application. An algorithm that estimates what customers are willing to pay can strengthen the seller’s position. When prices become harder to compare, shoppers must spend more time finding a deal.
That time has a cost. Consumers juggling work, family and transportation constraints cannot endlessly shop around to save a few dollars. A market can offer choices while making those choices expensive to exercise.
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Consumers could benefit from AI
Consumers could also benefit from AI. Imagine an application that compares an entire grocery basket, accounts for promotions, package sizes and dietary preferences, then recommends an efficient shopping route. Saving pennies makes little sense if collecting them requires several extra kilometres of driving.
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A game of cat and mouse may develop between retailers’ pricing tools and consumers’ shopping tools. A better balance is possible, but it will require accessible data, reliable comparisons and sufficient competition.
Buying local offers another opportunity. For food, “Product of Canada” and “Made in Canada” carry different requirements. The former refers to all or virtually all major ingredients, processing and labour being Canadian. The latter concerns the final substantial transformation in Canada and requires a qualifying statement about ingredient origins. AI could help consumers interpret these distinctions.
It could also improve traceability, allergen management and information sharing. But accurate records remain essential. An algorithm cannot establish an ingredient’s origin from incomplete evidence.
AI will change tasks and jobs throughout the food supply chain. Its value should be judged by concrete results: less waste, greater productivity, reliable information and more affordable food.
If AI makes the food system more efficient, Canadians should see the difference on their grocery bills.
– Sylvain Charlebois is director of the Agri-Food Analytics Lab at Dalhousie University, co-host of The Food Professor Podcast
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