AI Reality Check: What Retailers Must Do Before Scaling AI

Hey everybody, welcome to our webinar today, AI Reality Check: What Retailers Need to Get Right Before Scaling AI. My name's Greg Buzek from IHL Group, and joining us today we've got Cindy Carlson from Dell Technologies and Brian Gallagher from Connexion, and then as always, Lee Holman from our team. Say hi, guys. Hello, everyone. Good to have everybody. So we want to make this interactive, guys. Tell us where you're from and all that stuff.

Who's your team?

We'll talk about that. But once we— first of all, I want to thank Dell Technologies and Connection for sponsoring and making this content available to you. This research is— was independent research from IHL that we're distributing in a package here specifically on the infrastructure that's needed to scale properly for AI. So once again, tell us where you're from. Football starts tonight. College football starts tonight. Who's your team? Tell us where you're from. Please go ahead and mark that and let, let everybody know on that. So I'm a Buckeye. I've got my scarlet and gray going here. I even got my logo somewhere here. So excited about the year for sure. Hey, before we get started, I also wanted to invite all of you to Retail ROI Super Saturday. For those of you not familiar with Retail ROI, It is a charity of people in the industry to help orphans and vulnerable children. We have an event. It's free for retailers to attend. In fact, for every retailer that attends, and we're able to use your name and your title and company, at least through November, generally gets about $5,000 in donations, which is enough for clean water for 500 or education for 50 children. So information on the screen for that. And with that, guys, we're going to turn the cameras off and start jumping into the economy. So the inflation rate as the government shares the inflation, quite honestly, is disingenuous. So what we have here is Truflation, which is our preferred metric, which takes a Nielsen ratings approach to inflation. So today the PPI came out at 3.3%. We'll talk a little bit about that in a second, but 2.27 is what the real-time data is showing. The government data is at minimum 45 days late in most cases, in some cases up to 6 months late for some parts of the measure. So this is a much, much better view of the market and what's going on. And everything is related to fuel and the price of gas. So whether it's airfares at the bottom, you've got gasoline, electricity, gas service, there is the big numbers. And the only other things that are up there is vehicle repair and then fruits and vegetables because of the cyclospora kind of stuff that's out there. Everything else is much lower than what we're seeing in the top-end inflation gauge from the government. So gas prices have only gone up a penny in the last 2 weeks since we had our last webinar. Obviously they're up significantly here in the last year because of the war. Every penny sustained is $2 billion a year that can't be used for anything else. So over a year's period of time. So that does have a material effect on retail in a big way, certainly psychologically. The bigger number to bring up, though, is the hidden stuff, which is the diesel prices have jumped considerably in the last 2 weeks. Now, this flows into the PPI as we're seeing it, and it's going to make products and services more sticky. With that inflation going forward. So the CPI, where we are over the last, really since January of 2020, we're running about 13% above the 2% trend that we were prior to January of 2020. You've seen this chart before, but just shows that it's not getting any better. We've been running double the inflation rate since 2020 overall. Budget-wise, the reason it hits so hard for everybody is it's in the categories that everybody looks at and says, oh, bemoans when prices go up. We're going to complain about it. Gas, beef, coffee, eggs, and now lettuce. Those things have all are a big part of the actual food budget and our actual budgets, household budgets that is having an impact. So everybody's consumer perception is horrible as a result of that. As I've mentioned before, whenever Washington gives out money, buy oil stocks because honestly, the money always seems to find oil companies. As you can see, the last case here, oil prices up 58% from where we were when we had the COVID stimulus. We were up 169%. You can go all the way back to 9/11 is the last time that things didn't go up. And that reflects in the earnings because this shows the Q2 net income growth for your oil companies up over 100% for each one of those. But it's not just the oil companies overall. Public companies in the S&P 500 have seen a 50% year-on-year growth in their earnings going forward. So we get to blame tariffs for a lot of different things here, but you can't tell me that AI is not having an impact on companies when you start seeing earnings growth like this going forward. It's not just tariff side. So the question is, is it AI or tariffs? Even in retail, we literally saw EBITDA growth of 2.3 times for our top 12 public retailers through Q2, through Q1. Q2 just came out. Some of them are getting hammered. Dick's Sporting Goods yesterday just got absolutely destroyed based on their numbers with Foot Locker. We're seeing a hit or miss on the stocks here in Q2, but through Q1 with those tariffs, we saw really, really strong earnings growth and profit growth. Flip side of that is the headlines of the jobs. Is all real positive. The reality is 25% of the US workforce is functionally unemployed, which means people are literally unemployed or looking for a job, but they're also involuntarily working part-time and they're earning less than poverty. So that's $26,000 annually before taxes. 25% of US workers are in that bucket today. And this doesn't even include the underemployment with what's related to particularly the kids coming out of school. And out of college right now. We're also seeing a vast rise in delinquencies, most specifically credit card delinquencies, but most certainly student loans. Student loans have seen a huge spike here in the last year as things came off the payment pause of basically now in default when it comes to student loans. So the consumer there is hurting. I threw this chart in here because this isn't necessarily an immediate issue, but it is a longer-term issue when it comes to retail, the demographics. This, this has obviously, this chart has a lot more to do with society as a whole, but just the massive reduction in marriage, not just obviously of the women age 30, but also the men there since we've seen over the last 60, 70 years, a dramatic drop because married couples spend more on goods and services, particularly in the specialty hard goods. Area. And that is going to come back to bite us here soon when it comes to things. The good news is net worth is up generally overall. This is highly skewed to the top 10 to 20% of the US population, as we'll get into the data, and that's reflected in retail. Household debt is actually better than it's been in quite a few years. It's come down significantly. Once again, most people's largest purchase is their home. Most people bought at a low interest rate or have refinanced at a low interest rate. That has helped on the, that side of things. I do want to bring your attention to the bottom line there, which is China, which is just rapid growth in, in debt and household debt. This is, this has gone up significantly. And if you look at the companies, it's even worse than this in terms of the leverage, which brings me to the whole fact that we are literally in a K-shaped economy. I know Scott Bessen came out and shared that the K-shaped economy doesn't exist anymore. I beg to differ. While we have plumbers and electricians and those folks who are seeing rapid rises in their incomes, we're seeing no tax on tips, which is helping those that are in those industries. We are seeing a massive, massive delta between the haves and the have-nots for everybody that doesn't fit into those categories. And we truly are still in a very K-shaped economy when it comes to retail spending. The top 10% of households control two-thirds of the country's wealth today, and that's why retail sales continue to grow. We have inflation as a part of that, but the money that the top income households have and that wealth from the stock market is the thing that's been driving up the retail spend. We also got a bump from the World Cup being here that impacted the restaurants in particular, but also gas stations and some of the other folks that are in place there. What's striking is the sheer number of people that are living paycheck to paycheck. 2/3 of Americans are living paycheck to paycheck there. That's the upper left of the green arrow there. And then just different levels of that. What's interesting on the right, and the part that just kind of boggles my mind a little bit, is 37% of those people live paycheck to paycheck by choice, by their personal choice, not because they have to, not because it's necessity. But by choice, they're spending all that, all that money and not saving for a rainy day there. That's, that's a little scary, but just kind of gives you an idea of what's going on with consumers. I was going to put some charts in here about buy now, pay later. That has skyrocketed to a certain degree. You had the previous layaway that it takes the place of. However, so many things, including your phones, have a buy now, pay later component to them. Now, so there's a rapid rise of just people doing buy now, pay later, and just putting everything on a contract over time to pay things off. So those are, those are massive changes and things that are happening in terms of the economy. Retail sales are still up about 5.7%. It is in a deck that we'll share online. Retail sales, this is the CNBC and NRF Retail Monitor, which is 9 billion credit card transactions. It's a real-time. Credit card transactions. What happens with the government is the government puts out data month to month on retail. So when you have July coming out and you had Prime Day in June, as well as the World Cup happening in June, July compared to June is obviously going to be down. Well, that's how the government puts out the numbers instead of year to year, which is a much better comparison of what's going on. So even with that, Year to year, the credit card receipts in July were up 5.8%. So regardless of what you say for inflation, whether or not you take the Truflation number or the government number of 3.3%, retail continued to expand and continued to grow across the board. The key sectors that grew strongly: sporting goods, obviously that has a direct component to the World Cup, as well as food and clothing. There is a major GLP-1 impact that is impacting clothing and grocery stores right now. People are buying less groceries, but they're actually buying new clothes that is tied to GLP-1s. As well, we had the people visiting for the World Cup that's going into food and drinking places. That is also up. So I apologize, the chart's not showing here, but 5.7%, I believe, is the number they had for July retail sales. So that leads us into our study today of what's going on. And I just really want to highlight some of the issues that we're going to be talking about that retailers are dealing with. Number one, we're— this is not your father's store anymore when it comes to the network. The average retailer now, particularly a large format store, has 6,700 network endpoints in a single store. Only 23% of retailers have a 5G type of approach in the stores. Just, we used to have just point of sale terminals and maybe CCTV cameras. Now we have RFID tags, we have RFID readers, we have ESLs, we have edge computing devices, we have robotics, we have roving robots through the store with their, their side of things. We've got Bluetooth devices, we've got all these different items that are hitting the network. And that's being a big problem. We're also seeing continually retailers and the staff losing time every day looking for merchandise within the store. Literally 30 minutes a day lost looking for information or looking for product that says, oh, it should be on the shelf. I need to check in the back. They're reporting 30 minutes a day per shift are lost just looking for stuff in the store. These are real problems that everybody is dealing with. And then we do annually, we do our inventory distortion study. Close to $1 trillion globally is related to either store operations issues or personnel-related distortion things with the retailers. And to put that in perspective, the personnel-related items alone is equivalent to the revenue of Costco. Just so we've got these massive issues where people are spending time looking for things, not being able to find things, people not being trained properly, the systems thinking they're accurate, but they're not really accurate generally. Most retailers think they're accurate 92% of the time, but because of theft, shrink, and other items, they're actually more likely in the consumer's mind to only be accurate 75% of the time. So when it comes to AI, it's really not just a technology. It's actually a formula of what you've got to do to deploy AI correctly. You know, it's not a secret. It's a sequence. You've got to do these things in order. And if you try to execute these things out of order, you're gonna have a disaster related to deploying AI. We have underspent for infrastructure for a long time and continue to underspend in infrastructure today. Only 14% of the spend when it comes to AI spend in retail is now being spent on the infrastructure side of the business. Which brings us to where does AI live? And there's really 4 levels when it comes to the store that matter. So on the device itself, we're seeing that more and more, particularly with handheld devices that are looking up inventory information or just information about pricing margins, et cetera, that lives in a small slim model on the device itself. Then we have store, in-store edge devices there that are aggregating things like computer vision, RFID, IoT streams. A lot of that is being processed at the store, and we're gonna talk a little bit about that going forward. Then you have near data center, which is outside the store itself, but through some of the communication players, you're in regional processing in that environment, and you're doing multi-store aggregation to make things very fast for your stores there. And then finally, you either have the cloud or you have an AI factory. We have Dell here today that is one of the only companies that are actually producing AI factories for privacy. For companies. And Cindy's going to talk about that going forward. So these are the 4 levels of usage there. And so this is just a different way of looking at it. So the managed pipelines of what you've got to do, there's less to manage when you're dealing with on-device. You just send it down and it's self-contained and it's private right there. And it's very, very fast. At the edge, it's a little more near the data center, a little more. And then at the AI and the cloud level, You're really doing heavy training, fine-tuning, the model governance and all that sort of thing that has to be done. That is our introduction, and I'm going to invite Brian back on to talk about connection.

Thank you, Greg. Yeah, always love to hear you walk through the economics. Anybody who's on the line from my team knows that's how I like to start every conversation around what we're thinking this world looks like. At the end of the day, right, we're driven by what the consumer votes on. And a couple of things for the retailers out there and that I would highlight from what Greg walked through on the economic side. One is that 2/3 of households in this country are living paycheck to paycheck. Granted, that's becoming more the norm to choose to do that. But it also talks to the second piece to me, which is important for retailers to understand, which is we've got the number of households skyrocketing with increased household income. And then we've got the opposite side, that gap in the middle. And so for so many retailers, figuring out where we're going to fit in our business and how we're going to meet the consumers that we're trying to drive in the doors or to our website. That's the important thing as retailers, which I was a VP of Sales, VP of Stores for a number of years. We spent a lot of time talking about how we straddled that. And that's just one of those things that just does not exist any longer. And it's very interesting to hear you walk through that, Greg. I appreciate that insight. If you can go to the next slide, Greg. For those who maybe don't know me or don't know Connection, just a little bit of an overview of who we are. I'm Brian Gallagher, our Retail Strategy Director here at Connection. I've been here for about 10 years after about 25 years leading store organization. I was with, back at the time, Signet, Crabtree Evelyn, Lindt Chocolate, and spent my last 9+ years with Brookstone. And so that's always sort of my lens. And now I get the pleasure in these last 10 years here at Connection of simply thinking about how does technology and the investments in technology create better store execution, better store outcomes. It's a pleasure of mine to get to work with all you as retailers and restaurateurs in figuring out what are those magic buttons for your business. So we're going to spend some time going through that, but I won't bore you with this whole slide other than to know sort of the way Connection looks at our our business in general is whatever you need in the technology space, from consultation to design, we're certainly available on the procurement side, as many resellers have always been, but Connection will support you all the way through that lifecycle journey. So whatever it is that your organization needs, we'll build that around you, including services through like the Helix Center for Applied AI and Robotics, a really forward-thinking group. I'm on the council there as well, leading around what do retailers and what do businesses in general really need to do in preparation for not just what's happening in AI today, but what is coming and when it's coming. And so those services and solution groups being available for you, but The main thing that I would point out here, and this is going to tie into what I think is the single biggest message I'd like you to walk away with today, which is going to be something we'll talk about here in the next slide, which is partnership, is at Connection, we're really proud of our Net Promoter Score of 82. I will just say that is really, really good for those who aren't familiar with that Net Promoter Score, it's simply going to our customers who work with us and go, would you recommend us to somebody else? Yes, no. I can tell you the Amazons of the world are historically in the mid-70s. So to be in the 80s, we're really proud that— and then to be an employer of choice. So as we talk about on the next slide, you can go ahead and go there, Greg. that the benefit of partnership, that to me, I hope is what sticks for everybody about who Connection is if you aren't familiar with us already. All right, we put this study together with Greg and we pulled in our partners at Dell because I think they're a great example of how we overcome what I truly believe is one of the biggest issues keeping us in retail from moving fast enough to meet our consumers where they're at and for what they're demanding from us in terms of solutions and services and support, whether it be from having the right product in the right place at the right time— traditional thing, right? Yeah. Or understanding how they want to interact with our brand on different platforms and engage with a physical store. We're having a really hard problem on the technology side of implementing that technology. Greg, He made mention, right, the investment in the infrastructure to make that happen is abysmally low. I think it was 14%. And, and we'll talk in a little bit about just how out of line or how that's sort of not in step with how you want to actually launch a good program. But for me, we're in a position where we need to start thinking about who are our partners. Who do we trust to go to battle with us? In the technology world over the last 15 to 20 years, we've created this web. And many of us have thought about it as the web that's in the back office of our retail store. And that sort of is true as well, but more in this case, that same web of cords and plugs and Which is, it's the same with our partnerships with our solution providers, and with organizations and resellers, connections and others, with our OEM partnerships. And we've, we've done it over the last 15 years for good reason, right? When we were launching a new solution, new POS system, we went and we bought who's got the best POS system right now from print to maybe we needed touchscreen, maybe we needed the interaction on the payment side. And we deployed that. Then we looked at our network and said, well, we've got the latest and greatest network and they can help us secure it and optimize it and maybe help us control for guest versus business. And, and we put all these things in place. Then we added, to Greg's point, hundreds, if not thousands of touchpoints, IoT and others, and we now have this web out there. One of the things, and we've also done some studies, some of this data you're seeing in here is from that, but the one thing that we know is that there's a priority, 80% of your CIOs, or if you're a CIO on the line, then maybe you can chime in and agree even in the chat, but we're disagree if you have a different viewpoint, but 80% of CIOs out there are asking their IT organizations to simplify their technology portfolio and specifically the number of strategic suppliers they're working with. All of this makes sense when you think about how much time we spend simply coordinating meetings, right? Like, let's just take that. Yeah, if you're working with 10 different OEMs in one retail location and you've got 3 to 5 different suppliers building those solutions, even if it's just on a replenishment side, right, the break-fix side, you're having to manage all of those relationships. All of those meetings, right? We all need your time to make sure that we're doing the best job we can and delivering the best solutions at the best price, the right time for your business. But we need your time to do that. What CIOs we know are asking for is to consolidate that to your most trusted partners. If you can eliminate 50% of those meetings, You actually gain 10 to 20% of time back right off of the bat, and it starts immediately translating into bottom line profits. You can see some of the numbers on the screen and all of the reference material is there as well. But yeah, one of the things we know is when it comes to the pure nuts and bolts of a piece of technology, it's becoming more and more about the partnership and the trust and understanding in what that will provide for your business short-term and long-term. And so developing deeper relationships, more meaningful relationships that truly understand what's happening in your business and what your long-term or midterm to long-term goals are is becoming more and more important within the organization. And so For all of you out there, hopefully you'll take some time and really think about who those trusted partners are or should be. But understand that the benefit is sitting there, and this is one of those where it's really easy. And I challenge everyone to look for those, at least even the first few opportunities to sort of shake that tree and go, why are we only buying something from somebody because we always have? That's typically not a good reason to do it. Could be, yeah, but typically not. I would say most of you can probably name a bunch of technology in your environment today, but you all speak with us about how it— how tough it is to tie those technologies together in a view of what's actually happening in the stores, right? You're creating dashboards, your help desks are monitoring all these things. We're actually buying software solutions to tie in and understand how one thing is affecting the other, or we're developing AI agents maybe today to go out and do that. But what if it was all built together to work together in the first place? So that's the main thing that I'll challenge everyone to think about. And I think you'll see in the study that Greg and the team have put together, you know, from a data perspective, there's some Real truth to that that's pretty easy to latch onto as you go back to your organizations and try and put that into practice. The second, and really the, my last priority for retail businesses is this idea of thinking about, to Greg's point earlier, how do you start building out your AI infrastructure? And I'm talking the infrastructure from all the way from the cloud or the factory to the employee's endpoint device. Everywhere in between, we know that AI is going to touch it. Again, consumers have voted for every one of our businesses. Whether you're a QSR, you're a specialty retailer, you're a big box retailer, high-end goods, discount goods, it sort of doesn't matter that The consumer has spoken, but we know that only 13% of retailers are actually prepared in the way that they would like to be at the edge to deploy AI that they believe is going to take their business forward. So think about that, 13%, 13.6%. Yet only 14% of the investment is being put into AI infrastructure. One of the things that we are working really hard with our customers on at Connection is trying to better align what your line of business leaders are desiring with what the reality is that's going to be required to deliver that Not just in the short term, but in the long term. Like, I get it's really easy to get caught up in what can AI do from a pure solution standpoint? What can it do from a marketing standpoint to drive consumer behavior? But what happens when the consumer complies? He actually does. what you've asked him or her to do. But you're not prepared for that, where they're going to meet the actual product. And one of the things that still always gets me, and I'll keep saying this, because I'm a believer in stores. Stores are different than they were 20 years ago. But we know 80-90% of all transactions, all commerce transactions, still touch the store in some way in the fulfillment path, right? Some of that might be because you're using stores as sort of the spoke and hub for an inventory model that's fulfilling e-commerce. Products still got to be in the right place at the right time. Or it might be that your stores are a showcase and a pickup point for some of the requirements of especially Gen Z who wants to touch and feel it before they actually walk out. Right. Especially depending on what segment of product they're looking at. But at the end of the day, we know stores are still important. So how do we make sure that we're putting the investment there? Yeah, you can see where some of this is. And I won't steal all of this because I am going to hand this over to Cindy here in a minute. But the idea that We've got to start investing in the right path matters. Sequencing matters. We as retailers need to think about what's the beginning of the technology journey. And it's not just the exciting application and working backwards. We've got to figure out how we lay that foundation. And something that, as a Helix connection, we love to jump in and start thinking about what that looks like and making sure we don't end up with that huge gap in the middle. And, and lay that out together.

Right.

And then finally, right, if we put this together, like if I was speaking with your line of business leaders and thinking about how we sort of frame this and steal this if it helps.

Yeah.

If you're an IT leader out there, I get the challenges, right? I'm meeting with you guys every single day and you're being asked to do more and more with less and less, or in some cases the same. It's maybe evened out a little bit. But you're being asked to do more with the same. That's still not easy. Yeah. And you're not seeing a roadmap and you've got layers, right? All the way from the cloud to the endpoint that you have to consider along that journey. Yeah. Is to start thinking about what this equation looks like. And this to me is what every single business needs to be thinking about. And if you've conquered this, man, I'd love to chat with you about how you've put this together. How your line of business leaders are working with you as IT leaders and then with your partners to do this. Hopefully that's with Connection. It's with somebody else that they love to learn. But right, this idea that we started with of consolidating a partner ecosystem, and that's on the OEM side, that's on the solution side and the support side with people like Connection. But then the second piece and. How do we make sure that we're modernizing our stores to be able to handle what we see coming in AI and what we can't see yet? Like, we all have to have some realization that there are things coming in AI that the consumer is going to adopt and require that we maybe have a feeling about today, but we have no certainty, and we're going to need to be in a position where we adapt. So when you're thinking about endpoint devices, edge computing, networking, storage, right, all of that's going to move to your store location where 89% of those fulfillment touch. And are we prepared to carry those AI loads as we get there? So I'll leave you with, you know, think about it this way. If you can have fewer strategic partners, What's that do for your business? How much time do you pick up? How much more trust and flexibility and speed to action do you pick up? And if you could then secondly have your networks and your edge layers and your endpoints ready to go with partners who you know are flexible for what may or may not be there, What would that give you? And then lastly, if you put those 2 things together, how much more accountability do you have on both sides? Right. We're working with you every single day, whoever those partners are, and you're not piecemealing conversations together. You're not having those famous conversations of, well, yeah, we're thinking about updating this, but that agreement's not up till next year. So we're going to have to do what we have to do this year. Right? We've all sort of had those conversations. Let us come in. Yeah, we know this is important. If we can help sort of build out what that roadmap looks like, we'd love to do that with you guys. And our role really is kind of simple. And if we can help you develop a strategy for deployment all the way through lifecycle, and wherever you need us to plug in, we're happy to do that. And let's To have great partners, top-tier partners like Dell to do that alongside of us. And yeah, I'm going to invite Cindy to come on now and she can jump on camera. Yeah, I'm going to have her walk through like, how does Dell deliver some of these same things we've talked about and maybe share a few other things at the same time?

Thank you, Brian. It's great to be here with Greg and Brian. So just to give a little bit of background on myself, my name is Cindy Carlson and I am one of the leaders in our retail industries group. So I come out of industries. I spent time at Target Corporation and before that with other retailers. So I love— it's great to be here with the retail community. We also have a very strong partnership with Connection and Brain. It's great to be here with one of our valued partners. So just a quick overview of Dell. Our purpose is to create technologies that drive human progress. We want to be the most essential technology partner, and we leverage our strengths to extend our leadership and capture new growth. Couple of important categories. We have the broadest end-to-end portfolio and are number one across client peripherals, server, and storage. We have the largest go-to-market engine with our direct sales force plus our large partners ecosystem, which Brian is part of that ecosystem, Brian and the connection team. And then we have the industry-leading supply chain. Everything is automated, AI-driven, and resilient, as well as agile at global scale. And then we have unmatched global services. So working with our partner ecosystem, we can deliver AI-enhanced services and support across the full solution lifecycle. So some of the things that we look at for Dell Technologies is the reason Dell wins. We're not just one product. We look at leading positions across the categories with an operating model that turns scale into consistent growth and value. So let's take a couple of these. On the left is we have what the business needs and what we see across retail or quick-serve restaurants in the industry. One of the things that we see here is we see Planning and prioritization is the first box on the left-hand side. So what are you looking to achieve? How are you planning smarter? How are you looking at proving it faster? When you're looking at AI use cases, do you have a list of 100 or 200 or 300 use cases that you haven't implemented? Are you looking at, let's prove this case? Let's look at is, are we getting a faster ROI on that case? Are we? Do we have the AI-ready data? Do we know which AI investment will have the largest payback first? And does that look like demand forecasting, maybe markdown optimization? Are there some service optimization? Do you have the data, clean unified data to fuel those use cases? And then are you looking at faster ROI? So are you looking at accelerated innovation, customer satisfaction, maybe improving your net promoter scores in your retail operation? Are you looking to reduce operational costs, increase in stocks? So what are those use cases and innovation that you're trying to achieve? And then are you looking to advance new AI experiences? Such as maybe computer vision. Without looking at overall budget, we can— without— with looking at your overall budget, we can help you with that proof of concept and scaling that into production. And then are you running your models with confidence and at scale? Greg just shared in his opening that there— that 30 minutes a day customers are looking for product. So are you forecasting replenishing? Are you decreasing out-of-stocks? Are you using agents to do some of that? Are you using agentic? Are you using computer vision or physical AI? We're seeing a lot of out-of-stocks where people are using— retailers are using robotics today. So those are some of the areas in looking at what the business needs and how you're prioritizing your use cases. Now, that's the retail reality. Here's how we look at delivering against that. Do you prioritize your strategy? Identify 2 to 3 use cases that will move sales, improve margin, reduce freight. And so think about how you're assessing and prioritizing those. And then do you have the modern AI platform? Do you have the right processes, technology, data? Platform? And then are you looking at on-prem for store-level inference or hybrid for enterprise scale? So how are you preparing and implementing those cases? And then also one thing to think about is on what you're delivering is the adoption. So when you're implementing the use cases, you want to ensure that adoption is happening. You want to ensure that onboarding programs— none of this will work without the right change management and enablement for the team. So if you think about that, it's from the store to the C-suite. You want to make sure that you have that adoption process called out. And then we bring at Dell the strategy, platform, production, and services to help you deliver that. So here's some use cases that we're seeing across retail today. So some of the areas that we're seeing is— I'll start with computer vision. So we're seeing use cases for computer vision from everything to how do I improve my net promoter score? How many registers are open? Do I have enough people at the registers or do I have too many people on the floor stocking? Some of the other is locked products. Am I dwelling at a locked product and do I need that product unlocked? Am I sending a message to that associate to go unlock that product? We're seeing digital assistance. Do I know what shift I'm working? Do I know what my assigned area is in the store that day? When is the next truck going to arrive with product? Do I have the right schedule? So those are some of the kind of use cases that we see. The other area here is it's important to look at those use cases as a whole. Look at that transformation so that you're not buying use cases one-off and buying technology one-off. So how are you planning for AI of the future? in those use cases so that you can have that connected experience. And then for the outcomes, we look at customer efficiency, customer experience, customer friction. We do not want customer friction. So how do we make it easier for the customer? How do we make it easier for the store team members? Looking at store team members is— You have employee promoter scores as well. Am I making it easier? Am I enabling the associates to do the right, the right tasks? And then store in a box and edge operations. So am I looking at compute in the stores? What is the right model for this? Is it POC? Is it going to move to the edge and you need more compute? And then is it going to move into some type of AI factory that's a repeatable process that you can use? And then secure everything is critical. Some things here for the edge, we are seeing a lot more. We have something called Dell ProMax with GB10, and it's allowing retailers to prototype AI use cases on site and then move that same workload to a PowerEdge for production. There's no rebuild, no lost time. And then we have Our edge operations are Dell Distributed Private Cloud that can help scale that proof of concept across every store with zero-touch deployment, significantly reducing truck rolls and deployment of those sites or improving rollout times. So those are the use cases that we are seeing in retail today. And then when you're looking at your use cases, be ready for physical AI. Because we're seeing robotics today, but as you're looking at your infrastructure, it's important to look holistically if you're going to keep that infrastructure for up to 5 years, or some retailers might even keep it longer. But to think about what use cases you're going to need in the future for these AI workloads. So this is what we are seeing, a lot of new use cases at the edge that I just talked about. And then we are fast-forwarding customers to results. The Dell AI Factory with NVIDIA represents a tailored platform designed for organizations looking to advance their AI capabilities. It combines robust infrastructure with NVIDIA GPUs to streamline the workflows, improve data utilization, and scale your operations seamlessly. It allows you to deploy those AI use cases, allowing the businesses or the retailers to develop, train, and implement those AI workloads with speed and precision. We're helping customers today adopt quickly with full-stack AI-powered use cases. and optimized infrastructure with services and working with companies like Connection, Brian, and, and helping drive those. We also look at simplified deployments and infrastructure management and then scale up and out with retail use cases and workflows while maintaining that performance. We accelerate this journey with the end-to-end portfolio. And some of the use cases that we see across retail that are expanding are digital assistants, computer vision, where we are moving beyond deployment into agentic and soon physical AI. So you can apply this foundation into agentic or physical in the future. Now the next slide is an example of a case study. And this is a case study here where we worked with Lowe's. Lowe's leverages this AI factory that I just talked about to transform retail with cutting-edge AI solutions, enhancing customer satisfaction, store operations, and associate productivity. Lowe's demonstrated how AI can be foundational to retail operations, transforming customer experience, and associate productivity through edge computing and real-time decision-making capabilities powered by Dell and NVIDIA solutions. Lowe's initiated a comprehensive digital transformation across their 1,700+ store network to meet increasing customer expectations while empowering their 300,000 associates with AI-enabled tools. The company deployed micro data centers with Dell PowerEdge servers in every store, creating a scalable AI ecosystem that spanned from online platforms to in-store operations for millions of customers, ranging from do-it-yourself DIY enthusiasts, enthusiasts to professional contractors. Lowe's deployed these in the data center with AI workloads for developers. Some of the challenges were real-time customer assistant needs. Customer required immediate expert guidance while shopping in store, but associates couldn't always be available at that exact moment. So that's where they needed help. Complex product knowledge requirements. Associates needed to provide specialized expertise across multiple categories like plumbing and gardening to effectively address diverse customer questions and simplify home improvement decisions. And then we helped with store layout optimization complexity. So physical store redesigns required extensive time and resources to test those different configurations, traffic pattern, or product placement. And then scalable AI infrastructure demands. The company needed low latency, real-time data processing, and inferencing capabilities across their locations to enable AI-driven experience. So some of the benefits that Lowe's saw was immediate customer assistance and delivery. The Dwell technology using computer vision algorithms accelerated computing automatically. So it detected when customers needed their help real time, creating the experience where magically an associate would appear next to you to help them enhancing that associate expertise. So Milo Companion transformed their associates into super associates by providing expert advice across categories, enabling them to effectively address complex customer questions and drive higher conversion rates with 98% neutral to positive customer reaction. And then we accelerated their store experience. So digital twins utilizing NVIDIA Omniverse and Lowe's to instantly test hundreds of store layout configurations digitally before making any physical changes, drastically reducing their redesign efforts. So that's the AI Factory and our case study. Thanks again, Brian, Greg, and Lee. And back to you, Greg.

It's super. Thanks, Cindy. Hey guys, I'm going to race through these final slides really quickly so we can get to Q&A. I know we're getting late in the hour and want to give you guys an opportunity to get some questions in here. Basically, the foundation is the network first. Those that have the network ready are seeing much higher sales growth and profit growth and plan to spend a lot more AI. That's the first thing you need to fix in your stores there. We talked about the cameras, the missing opportunity. Only 9% are using computer vision today, yet 40% have cameras that are able to do that. That is a major enhancement for on-shelf. Availability. We saw huge jumps in that in our research related to on-shelf availability. You can't buy it if it's not on the shelf, and that's a big problem that the retailers are facing. Benefits of AI are heavily on the inventory accuracy side. As you can see, demand planning and forecasting, 76% of the people doing that are seeing strong positive rates of benefits by deploying AI in those areas. This inventory accuracy opens the door for being able to increase the revenue and all these other journeys. So the people that are literally doing this and have the, that are the sales leaders, so to speak, that have done these network infrastructure things are seeing 130% more of their revenue coming from BOPIS. They're losing 43% of lost sales, fewer lost sales. Than others, and they're getting a 25% reduction in inventory errors when they're leveraging digital twins as part of their activity. I'm going to skip this piece, but basically the people that are deploying edge or edge things, edge computing, are actually adding store personnel. 70% of them are adding personnel, not taking personnel away as they deploy these new technologies at the store. Really 4 different steps. This is, this is the formula. Phase 1 is your data has to be accurate. Next, you've got to have your network and your edge done. Then you start doing the pilots. The computer vision is the, the layup here. Once you have those things in place, on-device associate AI, attacking that information gap, and then you start to scale inference and custom models. So timing-wise, this is what shows you over time. I think you can compress this as long as you get that data accuracy done. We're seeing most people in that 8-month timeframe. to 10-month timeframe in reality of what's happening in retail. There are a few that are all the way up to the 16 to 17 months of things with AI. So the question you've got to decide is whether or not you build it or you consume it or buy it. So do you hold proprietary data at a fleet scale? You may need your own AI factory as a result of that. So if you can answer yes to all of those, you're going to build your AI factory. If not, you're going to be looking at partners outside that are going to be able to do this AI stuff. And you're going to need to worry about how do you do this and keep your data secure for all the things that you're doing with AI. So it's really a formula. It's a sequence, data integrity, that integration into a single view of the truth, accountability when it comes to the inventory decision, they're being able to leverage it at the decision intelligence level, having the profit discipline. Being able to do the simulations and continuing to build that cycle and that flywheel is what generates the thing. So with that, I'm going to bring everybody back on and let's do some Q&A, Lee. All right, Greg, first question is to you. For a mid-market retailer with 300 stores, what is the first infrastructure investment that pays back? Yeah, the network is by far the best, making sure your Wi-Fi network And your landlines and 5G if you need them at your WAN. Can you support all the activities that have to occur there? If you don't do the network first, you're going to be in trouble when you try to deploy these other items. So the network and always get 1 to 2 times what you think you need in the bandwidth at the store level. Okay. This one's for Cindy and Brian. What's the biggest hurdle to scaling AI across hundreds of retail store locations? And how do you overcome it?

Well, sorry, Reagan.

Yeah, go ahead.

Challenges managing the data at the edge stores generate massive amounts of data. So if you think about cameras, sensors, POS systems, I would say, where is that data going? Looking at cloud and token economics. And then the solution deploying edge computing infrastructure, you could process data locally in the store and get those real-time insights for things that you need, like inventory management, and then sending only the essential data back and forth to your core data center.

Yeah, I'd agree completely. And just add in, I think that is the crux of why it's so important to build those consolidated partner relationships that I was talking about. Think when you're doing that across 10 stores, okay, and the pain in the butt, right? When you got to work with multiple, maybe OEM in one store rollout or refresh or build. But when you're doing that across 300 or 3,000, maybe across the nation, the coordination of little things like timing and what that means for your business, having things there at the right time and working with your contractor to Deploy the actual infrastructure to get all those outcomes Cindy was talking about really becomes imperative. And I believe that's why the CIOs are going, get us partners that you trust, not just partners who always give you the lowest dollar amount for every single purchase. Sorry, purchasing people on the line. All right.

Greg, this one's for you. You called AI a formula, not a technology. What are the terms of that formula and which one do retailers most often skip? Data accuracy is what's skipped the most. Then it's the network. That's the second one. It's those 2 foundational ones. They build on each other. So you got to think of it almost as a triangle, so to speak. And if you're not doing the data accuracy first, you're just, you're just going to make fast decisions on bad data, which doesn't help anything, makes things worse. One of the most disturbing things we've seen in our data is the number of poor-performing retailers who have not done that work. who think generative AI is their end-all to success, and it's just going to just hasten their speed to disaster. Yeah. Cindy and Brian, how can we ensure our AI investments actually deliver a measurable ROI as we scale them across our businesses?

Yeah, I'll jump in. And some of this ties into some of the programs that we've specifically built for just this reason at Connection and through our Helix Center. And you mentioned the GV10 program, really cost-effective ways that we've specifically designed that when you're trying to understand ROI specific to your business, we're finally to a point where we have affordable ways to come in and build those. The GV10 connection, Helix, we actually have what, what we refer to as a jumpstart program. Where we come in and we stand up your individual POCs based on what's been going on in the market, but at a really affordable price point. Like I'm talking like 5 digits instead of 6 or 7 digits a launch. Like you don't have to be investing in your own factory to understand what your ROI is. Yeah, but you've got to start playing with those things. And we're seeing the largest enterprise retailers work in that space to test their outcomes and the smaller. It's a really affordable and fantastic hardware that gives a lot of flexibility.

Okay.

Greg, you mentioned a surge in entrepreneurship from AI tools. Is that a labor supply problem for retailers or a new competitive set? Yeah, it's funny. I had a slide in here that's showing it. The number of single-person or technology companies that have now been created as a result of AI is literally on an almost singularity slope right now. Just a massive number of people that are trying to be AI agencies to help others or build apps or things that can, can do stuff. So we've had a striking increase in the number of 1 to 2 person businesses, and there's never been a better time to just say, if you got an idea, Vibe coded into reality with a variety of different tools that you that you can use there. I think even ChatGPT sites now has the payments and the infrastructure and the servers as part of it in their ChatGPT sites. So you can do it through Forcel, you can do it through Gemini, you can do it through Claude to a certain degree. But the main thing you got to be careful of is you just don't want to vibe code it and then leave it. As it's vibe-coded, you need to have somebody that's really a developer look at it from the security and the, and the database and the payments and all that sort of stuff there. But so many different opportunities to build a business and grow.

All right.

I'm looking and we're 6 minutes after the hour, so let me toss it back to you.

All right.

Well, thank you everybody. We're thankful that you're here. I shared a second ago, our next webinar is going to be in a couple of weeks. Let's see if I can share. Share the slides again here just so you can see it. So if I go back up one, this is the link to our next one on Spend Smart. This is going to be focused specifically on specialty stores on September 10th. And then our contact information is here for each of us if you need to reach out and, and talk to us about any of these topics. So we want to thank you guys for taking your time today. I know we went a little over. I apologize to those on LinkedIn. Everything was working fine and then it just stopped. I'm not quite sure what, what happened there, but we'll upload a recording so that you can get that. So thanks so much. Enjoy the football games, guys, and look forward to seeing you soon.

Take care.