Over the past few months, a Walmart Neighborhood Market in Levittown, New York, has been quietly transforming. With artificial intelligence-enabled cameras, interactive displays and a massive data center, this store suggests a retail future that seems like science fiction.
But this store isn’t just a shiny new object, equipped with tech for the sake of tech. It’s a unique real-world shopping environment designed to explore the possibilities artificial intelligence can contribute to the store experience. It’s Walmart’s new Intelligent Retail Lab – or “IRL” for short.
While the application of AI in e-commerce is now table stakes, there haven’t been many physical explorations of its potential. But IRL is designed to do just that.
Walmart’s tech incubator Store No 8 has positioned the store within one of the company’s busiest locations. Testing new, innovative ideas within a real store containing over 30,000 items is an opportunity that Mike Hanrahan, CEO of IRL, finds exhilarating. “We’ve got 50,000 square feet of real retail space. The scope of what we can do operationally is so exciting,” he said. “Technology enables us to understand so much more – in real time – about our business. When you combine all the information we’re gathering in IRL with Walmart’s 50-plus years of expertise in running stores, you can create really powerful experiences that improve the lives of both our customers and associates.”
IRL is set up to gather information about what’s happening inside the store through an impressive array of sensors, cameras and processors. All this hardware is connected by enough cabling to scale Mt. Everest five times and enough processing power to download three years’ worth of music (27,000 hours) each second. According to Hanrahan, the first thing this equipment will help the team focus on is product inventory and availability. In short, the team will use real-time information to explore efficiencies that will allow associates to know more precisely when to restock products, so items are available on shelves when they’re needed.
Here’s one example the team is working on for the near future: When you go shopping for the week, you want the products you buy to be in stock when you get to the store. In IRL, a combination of cameras and real-time analytics will automatically trigger out-of-stock notifications to internal apps that alert associates when to re-stock. This sounds simple, but it means the store has to automatically:
Detect the product on the shelf
Recognize the specific product (meaning, decipher the differences between 1 pound of ground beef and 2 pounds of ground beef)
Compare the quantities on the shelf to the upcoming sales demand
The result is that associates won’t have to continually comb the store to replace products running low on the shelves. They’ll know what to bring out of the back room before customers show up. With the technology in IRL, customers can trust that the products they need will be available during the times they shop.
Because there are many scenarios just like this to be tested, IRL will be in data-gathering mode in its early days. The focus will be on learning from the technology and not implementing changes to operations in haste.