Walmart, AI, and the future of shopping, with Walmart CTO Suresh Kumar

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The world's largest retailer, Walmart, has been in the news lately. Its longtime CEO Doug McMillan has called the company's next chapter an AI-driven transformation, deeply impacting everything from its workforce to the shopping experience. Plus, there's another big turn ahead because Walmart just announced that a new CEO will step in next year to oversee this AI evolution. And our guest today is the bridge between these eras of leadership and technology. Suresh Kumar is Walmart's Chief Technology Officer and Chief Development Officer, and he says AI is not an add-on for Walmart, it's core to the business.

It's an integral part of how we are transforming our customer experience, but delivering on that customer experience means that we are also changing the way in which we work internally as well. And it is very, very clear that with the capabilities that the systems can provide in the workplace, the nature of work will end up changing quite dramatically.

Suresh takes us inside Walmart's major push to integrate AI into every aspect of its business, online, in-store, and operations, all adding up to a completely new retail experience. This is the future of shopping. I'm Rana Elkalyouby, and this is Pioneers of AI, a podcast taking you behind the scenes of the AI revolution. Hi Suresh, welcome to Pioneers of AI. I'm so excited for our conversation.

Hi Rana, really good to be here.

So we're going to spend the bulk of today's conversation talking about how you're deploying AI at Walmart, but I'd love for our listeners to get a sense of your own journey. I believe you grew up in India and you immigrated to the U. S. So did I, so I think there's a lot of commonalities in our journeys.

You're absolutely right. I grew up in India, I did my undergrad work over there. I went to Indian Institute of Technology Madras. And then after I graduated, I came directly to the U. S. to do my PhD. Um, and first worked at IBM, IBM research in New York.

From his PhD at Princeton and then IBM, Suresh went on to roles at Amazon and Google, and he's been the Chief Technology Officer at Walmart for about six years. The tech community in India has closely watched his rise. So you're kind of a business celebrity in India, you you get a lot of coverage there. Do you still have strong connections?

I do. We have a very large office both in Bangalore and then, uh, in Chennai. We do a ton of software development over there, and I have personal connections too. My mom is, uh, still in, uh, Bangalore, where I grew up. I have family there, my my elder brother is there, my in-laws are in Chennai, so lots of reasons to go back.

You know, I spent I did an Eisenhower fellowship and I spent about um a month and a half there, like, basically exploring the AI ecosystem in India. And I was just both struck but also impressed by how the country's really leaning into AI. And of course, India is one of the few countries that already has a data infrastructure, so turning on the AI layer makes a lot of sense. All righty, so let's dig into all the ways Walmart is deploying AI, and I wanna start with the customer-facing use cases.

You guys recently announced a new partnership with OpenAI to create this, like, allowing people to shop from within ChatGPT. How did this partnership come about?

Oh, we are very excited about this. Look, um, uh, we want to be where our customers are, and we want to make it really, really easy for our customers, uh, to shop while they are still inside, uh, ChatGPT. So, what you will see very soon, uh, as a result of, uh, the partnership and the integration, is that if you are in ChatGPT and, uh, you know, you, uh, are continuing a conversation with ChatGPT, you can, uh uh, find all the Walmart products right, you know, right there.

And, uh, soon after that, you should be able to just, uh, select and complete a transaction right inside ChatGPT without, uh, without leaving it. The genesis of all of this, like I said, is we want to make it really, really easy for our customers, uh, as friction-free as possible when it comes to fulfilling their the shopping needs. Uh, we know that customers habits are changing, and, uh, it's no longer just about, uh, especially if you're online, it's no longer going to be just about uh, having a search bar where you can type in keywords and then get a list of millions of products.

It's actually about fulfilling a particular need, which is contextual and which is, uh, which is also based upon what your personal needs are as a as a customer. And wherever that need is felt, we want to be there.

The way people are shopping is really changing, right? As a point, you know, instead of, say, you know, Googling or whatever, you're now asking ChatGPT for an answer. How do you ensure that, you know, this AI bot basically recommends a Walmart product and points you in the right direction? I I think it's changing search engine optimization altogether, right?

it is. It is. It's, uh, less about search optimization, it's more about understanding intent and being able to fulfill the intent. We are basically building out our own, uh, you know, intelligent agent for for shopping as well. We call it Sparky, and there, I, instead of having to deal with a search bar and where you type in keywords, you'll you can have a natural conversation with Sparky. You can say that, hey, I've got six people coming over for a dinner tomorrow, and Sparky will actually help you prepare for the, uh, for the dinner, not just the ingredients.

It can understand what, uh, dietary restrictions are going to be there. Most important, it can understand what is the best way for those products to be delivered in the most seamless way to your house, understanding what the ordering cutoff times are, the what the delivery times are. So shopping is much, much more than just having a list of products at great price. That's a very important part of it, but it's also the experience, right? And to understand what is the best experience that you need.

Uh, we need to understand Walmart needs to understand what the context is. The context if you are preparing dinner for six guests tomorrow is very different than you know if you, uh, are planning to go on vacation in two weeks. So, what is the best way to serve you depends upon what are you trying to do and what's the best way that that we can serve you further.

You know, I've been really thinking a lot about how companies can use AI kind of products can use memory as a moat. Cause now you're gonna have, like, especially with Sparky, right? You're gonna have all the history of the interactions and the conversations. How how do you think about memory to optimize the shopping experience?

Look, Rana, if you take a step back, the best way that we can serve our customers is to truly understand both what their preferences are and what are they trying to do. We so we talked about the context, what are they trying to do? The other very important part of this is really our ability to understand who you are as a customer. And I, if you think about it, Walmart has more information about our customers than just about anybody else that we can use to help serve our customers better.

Because we serve our customers online, inside the stores, through delivery, through pickup. We also have got all the services automotive, pharmacy, vision, our bakery, all of these things put together help us understand who our customers are at a very deep level. And that, in turn, allows us to be able to serve our customers in a much, much more personalized and contextual manner. And so, you know, when you talk about memory, the important thing for us is a true understanding of who the customer is, and therefore, what are the things that our customers really need?

And we believe that this is a huge competitive advantage for us. Um, just about everybody is going to end up having access to the latest large language model, but what differentiates us is the fact that we serve more customers in more ways than just about anybody else. And that allows us to combine the capabilities of this large language model with deep understanding of who our customers are. What do they want? What are their preferences and what are they trying to do in this particular uh interaction, whether it happens inside ChatGPT or whether it happens on our own site or somewhere else?

I love that marriage between kind of understanding, like, truly understanding a customer's profile and preferences, but marrying that with intent.

That's right.

That's very cool. So I read a statistic that 90% of people in the U. S. are within ten miles of a Walmart, which which is crazy actually. So how are you using AI at Walmart's brick and mortar stores?

Yeah, so first and foremost, you're absolutely right. There is a Walmart within, you know, ten miles of 90% of the U. S. population. Of course, we also have Walmart around the world as well. Um, what this allows us to do is many things. One, it allows us to curate sort of the the best and the highest value products that all of our customers want and place them as close to where they live as possible, right within a Walmart supercenter, within a Walmart neighborhood store.

So that's the first and foremost, and we are using AI to really understand what I talked about customer preferences. So if you aggregate that, then you get a really good idea about what our customers in a particular area are really, um, what is it that they really want? And we can therefore curate all of our products based on that. The second thing is that having a Walmart that close to all of our customers allows us to be able to then take our supply chain, which is a supply chain that we have been building over many, many years, combining the best of grocery and perishables with our general merchandise.

And now with third-party fulfillment that that we do for our on behalf of our sellers, and be able to optimize the flow of inventory all the way to the customers' homes, in many cases, through the stores itself. And what that allows us to do again is to deliver a seamless experience with Walmart Express Express delivery. We can uh have products that you really need right now delivered to you in less than an hour, uh, depending upon where you live and and you know what your preferences are.

If there is an immediate need, maybe you've run out of sugar or salt, we can have it to you uh before you complete making your dinner. So that is a huge advantage for us. And then the last thing that that it allows us to do is to really combine online shopping and in-store into a completely seamless experience. Um, what we call as truly omni uh experiences that can start online and may end up going inside the store.

It might be that you start online and you don't even go inside the store because we have pickup uh available for you. So all of these combinations, we want to be there where you are, but we also want to provide you with the products that you want in the way that you uh like to have them, right? And that might change today, tomorrow, and based upon whatever context you uh you're shopping on.

Yeah, you know, um, I, I grew up around the Middle East, and I suspect it's probably the same in India. My parents still to this day, if they wanted, like, run out of sugar or salt, they'll just call the closest grocery store, and literally within, you know, fifteen minutes, it's there. That's a little bit of a cultural difference in terms of how things work here, but I think there's an opportunity to create this instant kind of delivery, and it sounds like Walmart is leaning into that.

Yes, so I think it's a huge desire for for many of our customers that there are many products where speed becomes very, very important. But that's not the only thing, right? So there are many cases where you want much more predictable delivery. You might want to make sure that that the delivery happens in a particular period of time. So we have got scheduled delivery, right? So you want to be there when the groceries get delivered. You can put it into into a refrigerator as soon as it comes.

So the nice thing about Walmart is that we can enable all of these things. So it's not just only quick commerce, it's not just only today delivery, or it's not just only about pickup. We can do everything.

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Last year, Stripe users processed $1.9 1 trillion combined. See how Stripe can power what's next for your business at stripe dot com. Welcome back to Pioneers of AI. You can also watch the show on our YouTube channel. Back to our interview with CEO of Walmart, Suresh Kumar. I wanted to ask Suresh about supply chain resilience. When Walmart delivers products all over the world, how do they use AI to help the company adapt to factors like bad weather?

When you talk about resiliency, there are several things, right? So, first of all, having a supply chain network that operates at scale allows us to plan ahead in terms of what is the optimal way to route inventory, but it also allows us to be able to react very, very quickly. So, uh, last year, when we had severe weather in parts of the East Coast, we were able to, on the fly, reconfigure our supply chain network. So that instead of delivering from one particular warehouse uh into a set of stores, we could reroute all of that uh to a different one.

Uh, same thing with our last mile delivery. If there are traffic incidents and and uh route closures, we are able to reroute our last mile delivery dynamically and keep the customer always updated in terms of what is going on, when are they going to receive the product. Through AI, we can connect all parts of our network to every other part. So it just allows us to be able to, uh, both plan in advance and be able to react in real time.

Do you also have digital twins of the stores? You do. I'd love to hear about, like, what technologies are you using to do that, and what are the use cases?

absolutely, yeah. So we have started building our digital twins at every level. All this optimization that I just talked about in terms of being able to plan ahead and to be able to reroute, that is possible because we have created a high fidelity model of the entire uh supply chain network. So we can then use that to not just plan several different scenarios and choose the most optimal one, but we can also test and see what happens if the one particular, let's say, warehouse or uh distribution center is closed.

We can run multiple scenarios kind of immediately to say this is the most optimal rerouting to to choose. Then inside what we call as our nodes, so you take a distribution center. We have rolled out a number of automated um systems inside our uh in inside our warehouses, inside our distribution centers. And we run simulation models upfront to make sure that these systems are processing inventory, whether they are receiving it, whether they are putting it uh on the shelves, whether they are pulling it out and creating what we call as the optimal pallet to be to be shipped.

All of those scenarios we can test out upfront. We can run simulations to figure out what is the best way to run different parts of our uh distribution center as an example. And then inside the store itself, right inside the store, we are starting to build out digital twins so that we can deeply understand things like what is the best way for us to be able to merchandise product? What are the best facings for merchandising our product?

Digital twins also allow us to optimize the pick path uh for our uh shoppers, our spark shoppers, or our own internal shoppers to be able to quickly go and pull product off the shelves to be able to deliver uh the order for you in the fastest time possible. So, um, ultimately, digital twins allows us to be able to quickly test out many, many different scenarios, sometimes in real time, so that we can choose the best one possible and the most optimal one possible.

And when things change, we can rerun it, and we can basically say, okay, now that something has changed, this is the best way for us to be able to react to it.

Are you also exploring robots within either the distribution centers or the stores? I mean, there's been a lot of investments in lots of robots in stores, but also humanoid robots, and I'm curious if that's an area you're exploring.

We are investing quite a bit in terms of automation inside our fulfillment centers and our distribution centers. These are purpose-built automation because these are industrial scale uh operations. And so there, we believe that the best way to automate a facility in such a way that we remove sort of the most dangerous type of work. We can do that with custom-built automation. So I'll give you an example distribution centers which handle groceries, working inside the cold chain, going into the freezer every single day for our associates used to be a very, very hard thing to do, right?

So it's sub-zero temperatures over there all the time, so you had to suit up, you had to go in hard working conditions. So there we, you know, we built in automation to be able to handle product in as much of an automated way as possible. And this is very custom-built, right? It is definitely AI-driven, but the hardware is custom-built. And so same thing with with our stores too. We have got automated storage, uh, management systems, and these are custom-built to operate within the store environment.

So that's that's the approach that that we have been following.

Given Walmart's scale, any subtle bias in any of these AI algorithms or models could affect millions of people. So I guess what concrete safeguards are in place to catch and then also correct some of these unintended consequences before they affect, you know, I don't know, pricing decisions to millions of people or whatever.

This is a great question. Look, one of the cornerstones of what we are doing with our AI program is trust and safety, whether it is trust of our customers, our own associates, by the way, our sellers, uh, the suppliers that that we work with. And so, generally speaking, what we have done is to make sure that we build in evaluation testing safeguards at all aspects of the pipeline. Let's start with uh uh with the LLMs themselves.

We don't build our own foundational models. We make use of the best foundational models that are out there, whether it is by OpenAI or Gemini or, um, you know, uh, by Google or, uh, the open source models or any of these things. But we don't just bring those models in-house just like that. We have built out a program where we extensively test each one of these to make sure that things like biases, uh, hallucinations and all of these things, they don't occur within the environment where we operate, right?

So it it's a very specific environment where we want these models to to operate in. So first is model testing, uh, before models are let into our production. Second is around data, right? Uh, the models are only as good as the data that they operate on. So there is a lot of uh effort that is put in around building guardrails so that the mod the models ingest data that has been vetted, trusted, and uh scanned for things like uh accuracy, coverage, completeness, and and so on.

So because we don't want models to operate on data that has been tainted or is incomplete, because then you can't trust the answers that that it that it gives out. And then the last part of it is on the output itself. So we have human in the loop where we take, you know, um, a statistical uh sample during operational time and during build time. We take a significant amount of the output that that comes out, starting with all the output uh when we start out something brand new, pass it through human evaluation to see whether the combination of data and models is actually producing the right results or not.

And then we go back and tune. And once we get it right, we still have a small fraction of the outputs that these models generate to always go in front of a human evaluator, because these models can drift, the data can drift over a period of time. So that's how we make sure that across the entire pipeline, data model output that we have safeguards everywhere.

Coming up, more on how Walmart sees its AI edge in a steeply competitive retail space. Stay with us. So Amazon is still the leader when it comes to e-commerce, but Walmart is showing impressive growth in this space. What would you say is Walmart's competitive advantage?

There are two bigger advantages. I think the first advantage, clearly, um, is that customers care about having access to great quality products. They care about trust, they care about convenience, and they care about the experience overall. So that is one big advantage that Walmart has because we serve customers no matter how they like to shop and how they want their products, right? Whether it is online, offline, inside the store, delivery, pickup, all of these things. So that's a huge advantage.

The other big advantage that that we have is that serving our customers in all of these different ways means that we have a much deeper understanding of what our customer needs are, what their preferences are, and I talked about the contextual piece. Translating that context into action requires not just an online presence, but it also requires us to have the the inventory in the right place, where, which is where our thousands of stores, uh, having a Walmart within ten miles of 90% of the the U.

S. population, that's where the advantage comes in. So ultimately, it is not about e-commerce or or stores, it's about how you deliver the entire experience.

Kind of marrying the physical with the digital and making that a seamless experience. AI is a vital part of Walmart's future, and Suresh is the person shaping that for the global giant with $680 billion in annual revenue. After our interview, longtime Walmart CEO Doug McMillon announced he'll retire from the company in January. Just a few weeks before that, McMillan made a major announcement about AI and Walmart's workforce at the company's Arkansas headquarters.

He said he couldn't imagine any job that wouldn't be impacted by AI, and that Walmart's plans to grow as a company did not necessarily include adding more people to its workforce. With more than 2.1 million workers worldwide, most of them in the U. S. It was big news. I asked Suresh to unpack Walmart's AI vision for its workforce in more detail.

It's an integral part of how we are transforming everything. We talked a lot about our customer experience, but delivering on that customer experience means that we are also changing the way in which we work internally as well. Um, and obviously, uh, AI, the tools that that we are developing will have a huge impact on the way in which we work. Um, and it is very, very clear that with the kind of advancements that that we are seeing in terms of the capabilities that these systems can provide in the workplace, the nature of work will end up changing quite dramatically.

And so that's what Doug meant by saying that he can't think of a single role that is not going to be impacted by AI. Just, uh, you know, think back to before, let's say, spreadsheets, um, uh, or word processors were there. People would still type out documents, they would still do financial analysts, but the way in which they started doing that, after the word processor became generally available and after spreadsheets became a thing, the nature of work changed quite dramatically.

It's not that we had fewer analysts, financial analysts being done after spreadsheets started showing up in. In fact, we now have far more analysis being done. Why? Because it's become a lot easier. So AI is going to do the exact same thing. Uh, the nature of work will will change, but that would mean that it would open up far more possibilities. So many things that only human beings can do to understand taste and preferences of our customers and translate them into merchandise that we want to sell.

These kinds of things we can do it much more efficiently with a lot more, uh, intentionality. Human beings are are great at understanding, you know, things like, uh, customer, uh, preferences for for new, uh, products and and things of that sort. But where the systems and especially AI is great at is to be able to sort through huge amounts of data. And we just talked about how Walmart has got the advantage of having all of this, this information.

How do you translate that into something meaningful? That's where the tools become important.

I'm really intrigued, like your best practices in terms of how do you bring the largest employer in the world, Walmart, right? How do you bring the team on board with this, you know, becoming AI first? How? What are some of your best advice for companies that are looking to become AI driven?

Well, few things. First and foremost, is to be intentional about it, right? So I took all of our leaders to go visit a number of companies in uh the Bay Area. We also went to some of the universities over there, and one of the quotes that one of the professors there said is that, you know, this AI transformation is a design problem, and it is not a prediction problem. What he meant by that is that, you know, you don't want to sit on the sidelines to wait and see how AI is going to actually manifest itself.

You want to play an active role in designing it such that it's going to be useful for what you are trying to do. And that's how we approach it, right? So every part of the organization, we look at what is the work that's being done today, and how can it be done better, faster, more accurately, in a way where the human element is amplified through technology and especially AI, that that's now being available. Um, so we look at not just today's work, but also starting to imagine what the future of the work is going to to look like.

A lot of the the the emphasis is on you're not able to do certain things today. So, for example, when we uh think about uh how we create and curate our catalog of millions of items, right? Today, it's very, very time consuming to go and look at each and every uh item and every attribute of an item. But this is where AI can help, and we have already deployed AI. So there are many things that you could not do before, you can do now, and that's how we're reimagining every part of the workplace.

I love that Suresh, we're gonna have to bring you back for part two to talk about some of this, like, what is what kind of new jobs AI is creating? But I wanna end with this question, which I ask of all my guests. What do you think it means to be human in the age of AI?

I think that being human, especially in the retail industry, really the the key part of what we are trying to do. And we describe ourselves as being people led and tech powered, and it's very deliberate, right? People led comes first and then tech powered. The retail industry fundamentally is about humans. After all, all the products that we are selling are for consumption by humans. So the human element runs all the way from our manufacturers and suppliers, our sellers, to our associates who are involved in every aspect of serving our customers, to the customers themselves.

You may still have an agent, but that agent is actually working on behalf of a human, right? The uh, latest iPhone case that you're going to be buying, even if you delegated that to somebody to a to an agent, it's really meant for you, right? So, to be a human in the age of AI, ultimately, is about using AI to make your own life better. And that also ties back to what our purpose is, right? So we help people save money so they can live better.

And I firmly believe that having AI is going to help people live better.

I love that. That's a wonderful way to end our conversation. Thank you, Suresh, for joining us today.

Thank you, Rana. It's been my pleasure.

I would love to have Suresh back as Walmart continues to implement more AI across the organization. He says he's game, so it would be great to hear from you to tee up a second conversation. With the holiday season upon us, how are you using AI to find and buy gifts? What features would be most helpful? I would personally love to have an AI shopping agent that I could put in charge of making a list and checking it twice.

But how would you feel about sharing personal information with an AI shopping agent? Or generally, the impact of AI on the shopping experience? Leave us a voicemail anytime at six zero one six three three two four two four. That number is also in our show notes. We'd love to know your thoughts. Pioneers of AI is a Wait What Original. Our executive producer is Eve Tro. Our producer is Rachel Ishikawa, and our associate producer is Jordan Smart.

Our senior talent executive is Stephanie Stern. Mixing and mastering by Brian Pugh. Original music by Brian Holliday, and our head of podcasts is Lital Molad. You can join the conversation on LinkedIn, Instagram, TikTok, YouTube, and X. Just search for at Pioneers of AI. Thanks so much for listening.