The new AI-powered grocery store
There’s a new store manager in grocery retail, but you won’t see them walking the floor, chatting with customers or putting up displays. Instead, this manager works behind the scenes, quietly analyzing data and optimizing operations. They can spot when bananas are running low before anyone else notices, adjust stock based on the weather and peak shopping times, and predict when a customer is likely to need coffee and eggs. This isn’t a person, though—it’s artificial intelligence (AI). And while this technology may be invisible, it’s becoming a central figure in grocery retailers’ operations.
As retail analyst Bruce Winder, president of Toronto-based Bruce Winder Retail says, AI is a “significant gamechanger” for the grocery sector—for two key reasons. “One is that the grocery industry is low margin, and one of the benefits that AI offers is operational efficiency,” he explains. “[Applications such as] supply chain forecasting and replenishment can save real money in an industry that’s low margin. The other reason is the ability [it gives retailers] to engage with customers at a deeper level, which increases sales and margins.”
Like the early days of e-commerce, this new AI-driven world promises exciting, transformative opportunities for the grocery sector. “It’s almost limitless in terms of the efficiency that AI can offer—if you have the time and resources to do it,” says Winder.
And not to worry—it won’t replace actual store managers. “AI, to me, is a human second brain,” says George Minakakis, founder and CEO of Inception Retail Group and author of Predictive Leadership: How Humans and AI Will Transform Organizations, Innovation and Competition. “For anyone in retail, it’s going to enhance our ability to do our jobs better. It’s not going to take over our jobs … I dismiss the idea that AI is dystopian and it’s going to take over the world. But the technology is going to enhance businesses, in general, and push us into a hypercompetitive marketplace.”
Here’s a closer look at how AI is reshaping key areas of the grocery industry, where challenges lie and what’s on the horizon.
Faster, smarter inventory management
Back to those bananas. AI is radically reshaping how grocers approach inventory management—making typically slow, manual tasks such as demand forecasting and replenishment faster and smarter. As IBM explains, AI technologies optimize and automate inventory management by combining real-time data, machine learning and predictive analytics. The result? Greater accuracy, cost savings, increased efficiency and improved customer satisfaction, as the right products are available at the right time.
Take demand forecasting, for example. AI-powered inventory management systems can analyze sales trends, customer behaviour, seasonality and even weather conditions to predict demand more accurately. At the same time, automated replenishment tools monitor stock levels in real time and automatically place orders when stock falls below a certain threshold. Together, these technologies help grocers anticipate demand spikes or shifts, avoid stockouts and reduce overstocking.
“That’s going to be the opportunity—to reduce waste and maximize assortment,” says Tara Conway, a Toronto-based retail and AI expert and speaker. “And if retailers can get close to perfect on their forecasting, it means they won’t have to mark down anything … So, the profitability impact is significant.”
Walmart is one retailer that’s tapping into AI to enhance inventory decisions. In the United States, the retail giant recently launched Wally, a generative AI-powered assistant. The tool streamlines time-consuming tasks such as data entry and analysis, forecasting and root cause identification—determining why certain products are over- or under-performing. Built on Walmart’s proprietary data, Wally processes large volumes of data through advanced algorithms and a robust computational infrastructure, according to the company.
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“And because usability matters, Wally is designed to be intuitive, requiring no technical training. Merchants can simply ask questions and receive actionable insights in seconds,” Walmart said in a blog post. “With AI removing the friction of manual reporting, our merchants can focus on what they do best: delivering the right products to customers, at the right time and with greater efficiency than ever before.”
This kind of real-time visibility is also a priority for digital players such as Instacart, which is applying AI to both the customer experience and behind the scenes. The company recently launched Store View, which combines AI and computer vision to power real-time inventory tracking for its retail partners. Instacart shoppers record videos of store shelves using their app. The Store View technology analyzes the videos for even more accurate insights into what’s in stock, running low or out of stock.
“This data powers smarter predictions, helping us know when items will likely be restocked based on store trends,” says Daniel Danker, chief product officer at Instacart. “Paired with tools like our Caper Carts, which combine AI and sensors for advanced inventory tracking, these innovations make shopping more efficient and reliable for customers and retailers alike.”
For retailers, technologies such as generative AI and computer vision could also unlock greater operational intelligence. Kantar refers to this as “operational AI.” As senior director Amar Singh explains, generative AI and computer vision can work in tandem to create greater efficiencies and help retailers make real-time decisions to optimize their layout, merchandising and assortment mix.
“GenAI can analyze inventory levels, shopping behaviour and [customer] demographics coming into the store, including age, gender and ethnic splits using facial recognition,” says Singh. “It also looks at how much time shoppers spend in different parts of the store. Using all these different inputs, AI can tell grocers, ‘This would be the right optimization mix for placing products in different areas of the store at certain times of the year.’”
Tackling theft with tech
As AI works to improve operational efficiency in various areas, it’s also tackling one of grocery’s most persistent problems: theft.
With the rise of self-checkout systems, customers are finding new ways to swipe some of their groceries. “When you place your product on a scanner, you could double up—for instance, putting two chocolate bars on top of each other. You just scan the lower bar and get away with the one on top,” explains Singh. “That’s shrink—and that’s been a pain point for many retailers for self-checkout.”
According to retail technology company Wavetec, other ways shoppers can bypass payment at the self-checkout include the “banana trick,” where a shopper replaces the code of a higher-priced item with a cheaper one; the “pass around,” where they simply remove an item from their cart without scanning it; and the “switcheroo,” which involves peeling the sticker from an inexpensive item and placing it on the barcode of a more expensive one, while making sure both items weigh the same.
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With theft resulting in big financial losses, Singh says grocers are turning to advanced AI technologies such as computer vision and spatial analysis to make self-checkout systems more secure. “With this new iteration of technology, shoppers simply place an item on the scanner and it does all the analysis—it scans the item, identifies what it is and automatically weighs it,” he explains.
Spatial technology takes it a step further. “It scans everything in 3D, reading the number of products from different orientations, which means there’s a more accurate count of inventory that’s going out of the store,” Singh says. In the case of the “banana trick,” for example, AI can verify whether the items match in weight and appearance. And if a customer tries to “stack” two products in an attempt to just pay for one, spatial technology will detect both.
Personalization becomes even more personal
How is this achieved? According to global consulting firm Bain & Company, today’s leading retailers are pairing traditional AI with generative AI. This powerful combination not only recognizes patterns in unstructured data, but also analyzes complex data in real time to create personalized content—everything from targeted ads to product recommendations. As Bain puts it, this enables “scalable, adaptable personalization that gets smarter with each interaction.”
Armed with these capabilities, retailers can create more detailed and accurate customer segments, produce vast amounts of content at speed and identify customer preferences on an individual basis. The results speak for themselves: Bain reports that early trials have shown a 10% to 25% increase in return on ad spend for targeted campaigns. And consumers aren’t shying away from it. In a recent Bain survey, more than half of shoppers agreed that generative AI-powered personalized recommendations will be valuable when shopping online.
This kind of hyper-personalization is already in play for retailers such as Walmart. Last year, the company began testing a GenAI-powered shopping assistant in its mobile app, designed to guide customers from browsing to purchasing. The assistant is part of Walmart’s suite of GenAI-powered shopping capabilities, such as GenAI Search, which allows customers to make requests in their natural language—whether they’re planning a party or in need of newborn baby supplies—and Walmart quickly generates a list of relevant products.
Walmart is also using AI to personalize the online shopping experience, customizing each shopper ’s homepage based on their preferences. The company said a full U.S. rollout is expected by the end of this year, with plans to expand the technology to Canada and Mexico.
To further enhance personalized shopping, Instacart recently launched Smart Shop, an AI-powered tool that makes grocery shopping more intuitive and tailored to individual preferences. Smart Shop uses advanced machine learning to understand customers’ shopping habits and identify patterns in their preferences. It then combines that understanding with generative AI, enabling people to effortlessly discover products that meet their unique preferences. “For instance, if you’re focused on heart-healthy snacks, low-carb baking ingredients, or high-fibre options for meal prep, Smart Shop surfaces these products quickly and effortlessly,” explains Danker.
For retailers, Danker says these innovations foster stronger customer engagement and satisfaction. “AI-driven personalization ensures that consumers can quickly locate the right products at their favourite stores— turning first-time shoppers into loyal customers.”
Looking ahead, retail expert Conway says generative AI will handle even more “low-touch” interactions; for example, questions around product availability and pricing. “That’s going to start to elevate the customer experience because your team is going to be focused on higher-engagement experiences with customers versus being consumed with the low touch, low engagement [tasks] … I do see GenAI being far more focused on the customer side versus the back end or operational side.”
Barriers and best practices
As promising as AI may be, it’s not without challenges. “One of the key challenges retailers have is information overload—you can be overwhelmed,” says Winder. “If you have literally trillions and trillions of data, how do you use it? How do you create meaningful insights that are actionable?”
Winder advises grocers to start small. “Don’t bet the farm on it. Dip your toe into it and test AI in a few areas to see if it makes meaningful progress for your business and it delights your customers,” he says.
While cost may be another barrier, Winder notes that prices will likely fall as AI becomes more widespread. “Like most things in technology, the more innovation there is, and the more companies use it, the lower the cost for users.”
Grocers must also be mindful of consumer trust and transparency, especially when it comes to their data. “You have all this information about consumers from their search history, their previous purchase and even their personal life and social media,” explains Winder. “You have to be careful with your relationship with the consumer and not abuse it.”
READ: How GenAI can reshape the way grocers do business
That said, Winder believes consumers aren’t just OK with AI in retail—they expect it now. “If they start to see offers that aren’t relevant to them, they get frustrated. There’s not a lot of patience for that now.”
In fact, he envisions a future where grocers can use AI to predict what customers need to add to their shopping lists. “When you’re running low on something, you might get a reminder from AI saying, ‘don’t forget to get milk’ based on your previous consumption habits,” explains Winder. “AI is all about having a friend or an assistant who is always there to tell you what to do next and to make your life easier.”
Inception Retail Group’s Minakakis envisions a future where consumers can interact with grocers’ AI tools directly, for example, placing orders through simple conversations. “I think that’s the ultimate in personalization and convenience,” he says. “We’re not there yet, but we’re going there.”
This aligns with his prediction that in 10 years, consumers will be living a vastly different paradigm, much like the one brought on by smartphones. “[Smartphones] came out in 2007 and by 2010, we couldn’t put them down,” Minakakis says. “I believe the same thing is going to happen with personal AI systems. They’re going to become a part of our lives and we’ll be wondering how we ever lived without them.”
This article was first published in Canadian Grocer’s May 2025 issue.
