Key takeaways:
- Retailers will need to identify whether their stores serve a “convenience” or a “discovery” mission for shoppers as AI boosts customer product knowledge.
- The decision will affect everything from store design and layout to product assortment and workforce KPIs.
- More than two-thirds of consumers have used an AI-enabled shopping tool in the past three months.
People thinking about the impact of agentic AI in retail focus, quite naturally, on how the digital shopper journey is being affected. But the rise of AI also is having a profound effect on brick-and-mortar retail, according to a new ICSC report, Shopping in the Age of AI: Redefining Stores for a New Era, conducted by the association and McKinsey & Company.
According to the study, the changes taking place in search, discovery and shopping patterns will force retailers to operate their stores as either “convenience” or “discovery” destinations, differentiating locations based on their primary purpose. This convenience/discovery binary has implications for virtually every aspect of store operations, from location, design and store layout to assortment, inventory management and workforce.
The rapid ascent of AI has accelerated the need for retailers to rethink their traditional brick-and-mortar strategies. Agent-led discovery already is becoming embedded into consumers’ shopping processes: a recent McKinsey ConsumerWise survey on consumer sentiment revealed that 68% of respondents used at least one AI-enabled tool in the past three months.
AI use is concentrated in the early stages of the shopping journey, at least for now: 62% of respondents reported using the technology to compare brands, models, prices or reviews — the most common application — with 55% using it to learn about a category or product, and nearly half turning to AI for discovery and inspiration.
“As AI takes on more of the research and comparison process — and eventually, completes certain purchases itself — stores will no longer be the primary venue for search and evaluation,” wrote the report’s authors Colleen Baum, Molly Squire, and Tyler Rose with Joshua Reuben. “Instead, they’re more likely to serve as sites for order fulfillment, convenient returns, product validation, immediate product access or differentiated experiences.
“Meanwhile, the bar for in-store customer service and product expertise will be higher, since consumers may have a higher baseline understanding of the products and services they want to purchase before entering the store,” they added.
Where are Your Stores on the Convenience-Discovery Spectrum?
While it’s not truly possible to have store locations that are only about convenience or only about discovery, determining where stores sit on this spectrum provides a useful lens for longer-term planning.
“All stores need to do both, serve both convenience and discovery,” said Stephanie Cegielski, VP, Public Relations and Industry Education at ICSC in an interview with Retail TouchPoints. “What this data is showing is that as [retailers] plan for the future, they need to be looking at what younger consumers are doing, and what they want. You have to be thinking five and 10 years out.”
Those younger consumers are enamored of brick-and-mortar shopping: among both Gen Z and millennial consumers surveyed by McKinsey, 38% say they shop mostly in-store, with 48% shopping both online and in-store.
Chart courtesy ICSC and McKinsey & Company
For some retailers, different stores in their fleet will serve different missions. The report’s authors gave the example of a footwear retailer’s store located along a commuter corridor that might prioritize fast pickup, a focused assortment of high-demand styles and highly visible service counters. The same retailer’s store located in a lifestyle district, in contrast, might allocate more space for browsing and limited product releases.
“The inventory might overlap, but the layout, staffing model and operational tempo should reflect the store’s purpose,” the report’s authors noted.
Tecovas Stresses Discovery and Engagement but also Offers AI-Powered Convenience
In some cases, different elements within the same store can serve both convenience- and discovery-oriented shoppers. Western wear retailer Tecovas encourages discovery with what it calls “radical hospitality,” offering boot customization processes that include actual cattle irons heated with blowtorches to allow customers to “brand” their boots.
But the retailer also recognizes the importance of convenience. Its Boot Runner program uses AI to have a store associate request a specific boot be brought out onto the sales floor, with “deliveries” happening within 85 seconds of the request. This allows the associate to stay with the customer during the boot-buying process, which can be intimidating for a first-time buyer.
“We’ve leveraged AI to make a better human connection based on what’s happening in the store,” said Kevin Harwood, Chief Technology Officer at Tecovas, speaking at the Shoptalk show in March 2026.
To find the right balance, customer demographic data is still a strong baseline for these types of analyses, Cegielski noted. “It will always come down to demographics like age and income, and each brand is different — I might not need an Abercrombie & Fitch store near me, but I would like if there was an Ann Taylor store.”
How Convenient is Your Store?
If a retailer determines that a store in its fleet should be a convenience-oriented destination, all aspects of the shopper journey should reflect this.
“Convenience is not just about speed at checkout — it’s also about daily-routine-friendly locations, predictable inventory, clear pricing and smooth transitions between digital and physical channels,” wrote the report’s authors. “Associates should be facilitators, helping shoppers locate items quickly, resolving issues efficiently and maintaining operational flows.”
These associates’ performance should be measured based on their ability to support the convenience mission, with possible associate performance KPIs such as reduced pickup wait times, transaction speed and issue resolution rates. In contrast, discovery-oriented sites’ workers could be measured on appointment conversion, average order value or repeat-visit rates.
Retailers also can make use of new AI-powered tools to determine just how convenient their store shopping experiences are. Digital twin capabilities allow retailers to simulate and optimize in-store operations before they make physical changes, creating digital replicas of store layouts, checkout lanes and replenishment flows. This allows retailers to model customer traffic patterns, test planogram configurations and align staffing with projected demand.
Home improvement retailer Lowe’s created 3D digital twins of each of its stores, giving its merchandisers a video game-style interface that allows them to virtually move products, fixtures and displays to help them determine optimal product placements as well as a host of other store-level decisions.
AI also is helping retailers manage and monitor operations, using recent advances in computer vision, edge sensors and AI-powered analytics platforms to capture and process in-store data in real time, according to the report.
New Shopping Patterns Demand More Frequent Merchandising Updates
For both discovery and convenience-oriented locations, the report’s authors believe in-store merchandising cycles need to speed up to match the pace of AI-assisted shopping. “Planning assortments once or twice a year is no longer sufficient in a world where search trends, social signals and AI-assisted discovery can shift demand in a matter of weeks,” they wrote. “Retailers need faster ways to adjust what they feature in store, how they allocate local inventory and which promotions they prioritize.”
These merchandising decisions need to be made based on a broad spectrum of information that can help determine consumer demand and optimal selling locations, even given the months-long lead times needed for many product categories. “It’s not just about the data you have about your consumers, but what’s being talked about,” said Cegielski. “If you’re trying to appeal to young consumers, what are the latest TikTok trends?”
These real-time demand signals, such as digital search trends and local sell-through data, also can be used to update replenishment, refine endcaps and continuously test new products.
Key Roles for Landlords and Shopping Center Operators
This type of heavily data-driven approach to retail also applies to mall and shopping center operators. “The success of any single tenant will increasingly depend on what surrounds it — elevating the need for landlords to curate a broader assortment of places where consumers can spend their time and money,” wrote the report’s authors.
They note that both landlords and retailers would benefit from the knowledge that, for example, an apparel store is drawing younger consumers who also frequently visit an adjacent yoga studio, or a grocery store is helping boost visits to nearly health and wellness tenants. Information on whether the mall’s entertainment options are helping to extend dwell times across the property also can be valuable.
This type of carefully curated, diversified tenant mix has been the goal for shopping center operators since at least 2008. They see it as a way of recession-proofing their properties, said Cegielski: “Malls were virtually just apparel retailers when I was growing up, but today people want to be able to go to a mall and check off four or five things on their to-do list at one stop.”
At both open-air centers and enclosed malls, ICSC has observed electric vehicle dealerships, an Apple store, plus food and restaurant options that go beyond typical mall food court offerings.
“It becomes this place that everyone wants to go to, and caters to everyone in a very simple and streamlined way,” said Cegielski.
