We are past the point of conjecture about whether AI will upend the retail industry; it already has. In a recent study sponsored by Nvidia, 69% of retailers that used AI in 2023 reported that it increased revenues, and 72% said it reduced operating costs. With these kinds of results, it is no wonder 81% of retail leaders feel an urgent need to deploy AI this year, according to a Google report. But while AI is already delivering big changes to retailers’ bottom lines, it hasn’t yet truly transformed the way consumers shop. That will happen this year.
For the most part, retailers have deployed AI to tackle low-hanging fruit such as automated customer service chatbots, personalized content for one-to-one marketing campaigns and improved store and inventory analytics. Those early use cases make sense because they deliver immediate results. But what are the most forward-thinking retailers doing with AI this year?
As the CEO of an innovation agency that works with large retail brands such as Nike, Amazon and Best Buy to design new digital products, I am lucky to get a front-row seat to retailers’ “moon shot” ideas for AI deployments. Retailers come to us to brainstorm and create AI-enabled products and services that won’t just deliver new revenue and reduce costs, but instead will fully transform the customer experience. They don’t want to wait a few years; they want to deploy game-changing AI frameworks today.
Here are four predictions for some next-gen AI applications retailers will begin to roll out this year.
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AI agents will shop for you. First we drove to the mall and trawled through racks of clothes hoping to find something in our size and style. Then we turned to ecommerce, clicking through pages and pages of items in hopes of finding that rare pearl. Now, AI will find and buy items for us. Retailers are readying auto-shopping bots that allow consumers to enter very detailed preferences (styles, brands, materials, sizes, prices, etc.) and then authorize the bot to shop for them. Consumers can choose whether to pre-approve purchases or not, set budgets, inform the bot to shop only for certain items at certain times or only buy items when they go on sale, and many other parameters. All of the technology to make this happen exists today; it’s mostly a matter of tying AI search to checkout systems.
AI will personalize storefronts. We are all used to being stalked by ads for a pair of pants we clicked on many weeks prior and seeing personalized product recommendations on Amazon and other ecommerce sites. But we haven’t yet experienced 100% personalized storefronts. With AI, that is about to change. Retailers can use ML models to extrapolate and infer what specific customers would be interested in with far greater precision than current shopper analytics platforms. That means when a shopper visits a storefront, it will be tailored to their style, size, budget and preferences. And the storefront will keep getting more refined and personalized based on traffic and purchase data, dynamically changing in real time.
AI will summarize reviews. Looking for the perfect rain jacket, grout cleaner or perfume? It doesn’t matter what type of product you’re searching for, chances are there are thousands of customer reviews about it — so many that they become meaningless. Who has time to read 9,876 reviews on blackout blinds? Now, retailers are rolling out bots that scan thousands of reviews to deliver a high-level summary. Shoppers can query the findings to get information that matters to them, such as “drill down into reviews about fabric quality” or “do these blinds block out enough light to get a baby to sleep?”
AI will deliver precision-targeted offers. Retailers and CPG brands already are experts at leveraging shopper analytics and purchase data to present consumers with personalized offers and coupons. But AI will take this type of personalization up 10 notches. Using AI-generated synthetic data to create “digital twins” of customer personas, retailers will accurately predict with SKU-level precision which items a person is likely to buy, when and where. Using predictive synthetic data, a retailer could predict that a shopper who buys Starbucks ground coffee at Safeway on a Tuesday is also likely to buy Kerrygold butter in the same shopping trip — and could, for example, send them a mobile coupon while they’re in-store. And since synthetic data is anonymized, they could do this without compromising consumer privacy.
Retailers, facing stiff competition and operating on razor-thin margins, have always been early adopters of futuristic technologies. From ecommerce and mobile shopping to personalized product recommendations and BNPL, many retail innovations have transformed the consumer experience. This year, expect AI applications to become de facto at your favorite retailers.
Dan Kraemer is Co-founder and co-CEO of IA Collaborative, an innovation consultancy that has helped hundreds of brands including Nike, Airbnb, FedEx, Audi and Samsung ideate and create new products. He is also an adjunct professor at the Kellogg School of Management at Northwestern University, where he teaches innovation and growth strategy. He is a faculty coach at The University of Chicago Booth School of Business, training educators on new innovation concepts. Kraemer speaks regularly at events such as Shoptalk, Design Thinking Conference, World Forum Disrupt and the IDSA International Design Conference. His creative work has been recognized by Fast Company Innovation By Design, SXSW Business Design, Red Dot International and the International Design Excellence Awards. He writes for publications such as Fast Company, Crunchbase News and American Banker. Kraemer holds a BFA from Northern Illinois University and an MBA from the Kellogg School of Management at Northwestern University.
