AI Rewrites the Retail Playbook

Live from the Morgan Stanley Global Consumer & Retail Conference, our analysts discuss how AI is reshaping the future of shopping in the U.S.

Read more insights from Morgan Stanley.

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Michelle Weaver: Welcome to Thoughts on the Market. We're coming to you live from Morgan Stanley's Global Consumer and Retail Conference in New York City, where we have more than 120 leading companies in attendance. 

Today's episode is the second part of our live discussion of the U.S. consumer and how AI is changing consumer companies. With me on stage, we have Arunima Sinha from the Global and U.S. Economics team, Simeon Guttman, our U.S. Hardlines, Broad Lines, and Food Retail Analyst, and Megan Clap, U.S. Food Producers and Leisure Analyst. 

It's Friday, December 5th at 10am in New York. 

So, Simeon, I want to start with you. You recently put out a piece assessing the AI race. Can you take us through how you're assessing current AI implementation? And can you give us some real-world examples of what it looks like when a company significantly integrates AI into their business? 

Simeon Gutman: Sure. So, the Consumer Discretionary and Staples teams went to each of their covered companies, and we started searching for what those companies have disclosed and communicated regarding their AI. In some cases, we used AI to do this search. But we created a search and created this universe of factors and different ways AI is being implemented. We didn't have a framework until we had the entire universe of all of these AI use cases. 

Once we did, then we were able to compartmentalize them. And the different groups; we came up with six groups that we were able to cluster. First, personalization and refined search; second, customer acquisition; third product innovation; fourth, labor productivity; fifth, supply chain and logistics. And lastly, inventory management. And using that framework, we were able to rank companies on a 1 to 10 scale. 

Across – that was the implementation part – across three different dimensions: breadth, how widely the AI is deployed across those categories; the depth, the quality, which we did our best to be able to interpret. And then the last one was proprietary initiatives. So, that's partnerships, could be with leading AI firms. 

So that helped us differentiate the leaders with others, not necessarily laggards, but those who were ahead of in the race. In some cases, companies that have communicated more would naturally scream more, so there is some potential bias in that. But otherwise, the fact pattern was objective. 

Walmart has full scale AI deployment. They're integrated across their business. They've introduced GenAI tools. That's like their Sparky shopping assistant. As well as integrated to in-store features. They talked about it. It's been driving a 25 percent increase in average shopper spend. They've recently partnered with OpenAI to enable ChatGPT powered Search and Checkout, positioning where the company, where the customer is shopping. 

They're also layering on augmented reality for holiday shopping, computer vision for shelf monitoring. LLMs for inventory replenishment. Autonomous lifts, the list goes on and on. But it covers all the functional categories in our framework. 

Michelle Weaver: And how about a couple examples of the ways companies are using these? Any interesting real world use cases you've seen so far? 

Simeon Gutman: So, one of them was in marketing personalization, as well as in product cataloging. That was one of the more sided themes at this conference. So, it was good timing. So, the idea is when product is staged on a company's website; I don't think we all appreciate how much time and many hours and people and resources it takes to get the correct information, to get the right pictures and to show all the assortment – those type of functions AI is helping enable. 

And it sounds like we're on the cusp of a step change in personalization. It sounds like AI, machine learning or algorithm driven suggestions to consumers. We didn't get practical use cases, but a lot of companies talked about the deployment of this into 2026, which sounds like it's something to look forward to. 

Michelle Weaver: And Megan, how would you describe AI adoption in your space in terms of innings and what kind of criteria are you using to assess the future for AI opportunity and potential? 

Megan Clapp: Yeah, I would say; I'd characterize adoption in the Food and broader Staples space today is still relatively ear