April 25, 2019
By Matt Smith, Walmart
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.”
What’s Inside IRL
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.
“Customers can be confident about products being there, about the freshness of produce and meat. Those are the types of things that AI can really help with,” Hanrahan said.
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.
“You can’t be overly enamored with the shiny object element of AI,” Hanrahan cautioned. “There are a lot of shiny objects out there that are doing things we think are unrealistic to scale and probably, long-term, not beneficial for the consumer.”
So, before jumping to more futuristic concepts, the IRL team is starting with real, practical solutions like the meat inventory example as well as others like making sure shopping carts are available and registers are open.
The IRL Experience
Walking into IRL for the first time is both familiar and unique. There are a lot of the staples you’d expect in a Walmart Neighborhood Market: associates, cash registers and shelves with thousands of products. There are also features that stick out right away, such as a glass-encased data center bathed in blue glow.
The idea of a live shopping environment infused with AI is exciting, but it also raises questions about all the visible technology. This was a key consideration for the team while designing IRL, and the store includes multiple information stations for customers to visit to understand exactly how AI makes the store tick.
“We chose right from the very start to not hide the technology,” Hanrahan explained.
As customers shop, they can interact with a number of educational displays. Small educational kiosks are interspersed throughout the store. A Welcome Center at the front end allows customers to dive deeper into technical specifications and common questions.
But, the real fun is just outside the Data Center where the servers are housed. Flanking the plexiglass windows are two large displays – one of which encourages participants to move around and learn how technology reacts to body positioning.
The interactive wall is a fun demonstration of how AI can estimate body positioning.The interactive wall is a fun demonstration of how AI can estimate body positioning.
This display outside the Data Center shares facts about IRL’s information processing ability.This display outside the Data Center shares facts about IRL’s information processing ability.Harlan Erskine
Small “Haven” displays are spaced throughout the store for customers to learn as they shop.Small “Haven” displays are spaced throughout the store for customers to learn as they shop.Harlan Erskine
At the front, the Welcome Center has commonly asked questions.At the front, the Welcome Center has commonly asked questions.Harlan Erskine
Working in IRL
Among the customers who’ll be absorbing knowledge, IRL’s more than 100 associates will be undertaking these retail experiments every day, getting a firsthand view of what’s possible for the future. With technology performing mundane tasks like evaluating if shopping carts need to be corralled, associates will be able to spend more time on tasks humans can do best, such as helping customers or adding creative touches to merchandise displays.
“We think it’s something our associates will be excited about,” Hanrahan said. “The technology has been built to improve associates’ jobs, to make their jobs more interesting, to help them alleviate some of the mundane tasks. AI can enhance their skillset in a very rapidly changing world.”
One day, the efficiencies being explored in IRL could lead to enhancements that help associates all over the country in the future. That part isn’t science fiction. It’s a journey that’s beginning now in Levittown, New York … in real life.