At this year’s Shoptalk conference, everybody was talking artificial intelligence

Thanks to some misconception around the term, it has never exactly been clear what AI can do — particularly for retailers.

“The term has roots in the ’70s,” said Eric Colson, chief algorithms officer at Stitch Fix. “That was back when we had big ideas for what computers could do. Now that it’s here, the term has stuck.”

We asked brands and retailers to share what AI means for their strategies and how they’re using it, beyond the chatbot.

Kevin Mansell, CEO, Kohl’s
On a practical basis, we see the big win in AI is allowing machine learning to provide better solutions for fulfillment — literally, it’s the decision-making tree of where and how an online order gets fulfilled, whether that’s at a warehouse, in a store, at multiple stores or via multiple packages. That’s a practical application of AI, and that’s not a future thing; that’s a right-now thing. There is a lot of shiny stuff around artificial intelligence and analytics that’s longer term but may have a lot of benefit. But right now, that’s how we see it. It’s not customer-facing, yet.

Anthony Marino, CMO, ThredUp
We just think of AI as another way the customer could want to shop. There are lots of impulses that drive a purchase, and it ends up being a broad topic — but it could look like a structured query, with results delivered up. That’s not as exciting as Alexa, but a customer needs to see a dress before they order it; it won’t be ordered like their detergent. Instead, we think of AI as infrastructure that helps us do a better job. AI is a buzzy term, but it’s more machine learning and personalization, and predictive analytics. That’s mumbo jumbo, though.

Nadia Boujarwah, CEO and founder, Dia & CO
“We do a ton of machine learning and AI — TBD what the actual difference is. People ask about machine learning and AI separately when it’s the same thing. We believe in the power of machine learning to create a better experience and, from our perspective, the most powerful application of data science, or AI, is understanding the customer.”

“At the same time, we hear a lot about chatbots, and the question is: Why would anyone use that? What’s the actual outcome you’re trying to get out of that when you’re saying, “That’s cool, let’s apply it?” What are you actually trying to deliver, and what’s the customer experience payoff? At the heart of it, we’re talking about personalization a lot of times, and with personalization, the person gets forgotten. So what’s most powerful is not losing sight of the actual human experience.”

Philippe Pinatel, president and COO, Birchbox
“Everyone’s realizing that AI has a lot of potential. Today, it’s not necessarily disruptive, but in the future, when you have every touchpoint with the customer, how does it improve the experience? AI can help us, both in terms of insight and future predictions. Like every technology, a lot of times you don’t know where you’re going with it. You have to be engaging with the customer first; AI is not going to magically fix everything. What it does do is free up time for retailers to focus on things like entertainment and discovery, and it’s going to become much more critical as a result. When fulfillment is automated, you have to be better at engaging the customer.”

Eric Colson, chief algorithms officer, Stitch Fix
“Most of the industry is rightfully confused about what is actually AI. Most of what we do is machine learning, but we do use AI, which comes into play on Pinterest. Our customers are looking at images on Pinterest and saying, “I can’t put this into words, but here’s what I like.” We take that and use AI to find similarities and visual aspects, and that results in better recommendations. That’s really just deep learning. We can also use AI to understand written reviews. One top got more reviews than the written works of Shakespeare, and it’s really hard to parse that stuff. With AI, we can understand who should receive that top in the future and who shouldn’t.”