Dell Technologies Inc. (DELL) Earnings Call Transcript & Summary

Good morning, everyone. Asiya Merchant here, I lead Citi's tech hardware and tech supply chain, Day 3 of Citi's TMT conference. Absolutely delighted to have David Kennedy here. He is the CEO of Dell Technologies here, and we also have Paul, in the audience from IR. So I'm going to start off with just some safe harbor statement here that Dell would like me to read, so please bear with me here. This presentation contains forward-looking statements based on Dell Technologies' current expectations. These statements involve risks, uncertainties that could cause actual results to differ materially. Factors that could cause results to differ are discussed in Dell's Technologies, periodic reports on Forms 10-K or 10-Q filed with the SEC. Any forward-looking statements made today are based on assumptions as of today, and Dell Technologies undertakes no obligation to update them. With that, first question is going to be about outlook.

All right. Good morning.

So clearly, just results that are just staggeringly amazing, right? I mean you guys just reported last quarter -- last week, I should say, and your current year fiscal '27 guide is up 70% year-on-year tracking. Of course, we are at an investor conference with a lot of investors being very skeptical. Like is there a cliff ahead after these like growths, which are so much higher than, let's say, your analyst event, right, and where you guys [indiscernible] about. So just given there is pipeline, you have a very solid pipeline, you have a very solid backlog, there's supply constraints at the same time. Like what gives you the confidence that this momentum continues not just through this year, but as you kind of think about the outer years, and there's not a big demand cliff that we should be aware of?

Yes, sure. Good morning everybody. You're right. Look, what we see is this accelerating appetite for infrastructure. And I think we've seen these building blocks emerge over the last 9, 6, 3 months and it builds on each other. So obviously, the tailwind of -- from an AI server GPU perspective, we booked $61 billion in orders in Q2. We had booked $61 billion of orders in the previous 3 quarters, so $132 billion over 12 months. So you see this accelerating appetite, it's also pipelines being multiples of that backlog. So while the bookings keep coming in, the backlog continues to get bigger, and it's across all the segmentation, you can think of neoclouds, sovereigns, enterprises. Enterprise is growing the fastest from a rate perspective. Obviously, the dollars are still pretty big on the Neocloud side. You then put another layer on top, which is from a inferencing workload perspective. So your traditional data center, that had a modernization refresh cycle happening anyway. You now put inferencing and AI workloads on top of that. And an emerging theme we've seen in the last 3 months around security and resiliency. So these -- all these components are driving. If you look at our Q2 results, we had 122% growth in Traditional Server, demand was faster than the P&L. And it's broad. So if I look at that by geography, every geography growing triple digit. If I look at it by customer segment, if I look at it by customer vertical, all these boats are rising. It's not one corner or on niche piece that's kind of floating it. So you build that. And now you introduced in our Q2 results, the need as you use more tokens, do more inferencing, need more compute power for the data, you now need somewhere to store it. So our Storage growth of 26%, and we've guided to double-digit growth for the year. We're watching all these signals, and we're watching the customer count, still being fairly early adoption curve and look at the pipelines. And now all of a sudden, we see that confidence that allowed us to guide what we've guided and allow us, I think, to think about beyond into next year or 2.

Yes. And then you marry that with CPU or I should say, constraints, not just in the CPU side, but obviously, we've all heard about memory constraints, HDD constraints. Is there any line of sight to maybe when these constraints sort of ease or normalize? And so -- and could there be more upside even in the back half of calendar '26?

Yes, we'll go piece by piece. So if I look at the back half of this year, I would -- in one word, I would call our guide a realistic guide. I think I would have positioned our second half guide 90 days ago to be a prudent side. I think we see way more identification of parts, the customer needs of data center readiness. So all of that picture is guiding to the $192 billion. Demand is still faster than supply, though for a traditional server and AI server. So those two buckets continue to have demand that was really robust. As we look into next year, we see the supply differential only getting worse, not getting better. We see, yes, there is a small bit of supply growth, but it's pretty minimal on the basis of the demand signals that we're seeing. So it's actually tighter next year than it is this year in relation to that as we look out, and then we'll see as we go beyond from that perspective.

Okay. And within that supply constraints, is it just memory, CPUs, HDD the usual? Are there any other pockets that are getting worse?

Obviously, dominated DRAM and NAND is by far the big brother in that equation. Given the growth in CPUs, obviously, that now comes into the equation also. But look, ultimately, any part associated within an AI box is short to some degree. So opticals, transceivers, T-glass, any component that's in there is constrained to some degree. And that's -- our job then is to try and figure out how we can put all these really [indiscernible] and parts, if you like, together into fully configured units to maximize the P&L. And that's part of the operational execution that we've talked about in our guide and to differentiate versus the competition.

And then, Jeff, on the call, you talk about this earning -- greater longer-term visibility with large sophisticated customers. Is that a function of these supply constraints that you're talking about and Dell kind of executing at its best where like you just mentioned?

Yes. I think the conversation in the market is around supply access. So if you go back to -- let's go back 6 months ago, was there a few savvy customers who foresaw some of this and did some advanced purchasing to kind of get ahead of that game. Yes, there was. But what we're now seeing is if any, pick an enterprise customer, they come forward. I know there buying history. If all of a sudden, they're looking to buy 4 years' worth of equipment from me, I'm not in a position to fulfill that. Our job is to try and make sure we diversify as many customers as we can and solve as many customer needs as we can. But what we're doing now is entering into conversations about what are your supply needs and your infrastructure needs going out into year 2, year 3 and year 4. And our commitment that for those who want to partner with us, we'll give them that supply access and provide some guarantees that we can position that further as we look out. Guarantee supply, does not guarantee price. That's a specific differentiation but that's what the market is looking for, it's that supply access.

That's fantastic. ISG margins, like eye-popping 15%, and this is in the face of AI servers, which within that segment, very lower margins, well above 3x almost relative to what you were looking at year-on-year in first half. Pricing, probably a big driver here of those margins, just given the pricing pass-through of some of these components. But what's changed here? And why do you think that could sustain?

Yes. So if you think of ISG rate, there's two tailwinds and one headwind, right? So by far, the biggest tailwind is scale. I'll touch on it later, but when you think of our OpEx as a percentage of revenue for the company, we've just guided to 8% of revenue, that's the most efficient we've been ever in the 42-year history of the company. And to give some kind of marker that was 20% of revenue 6 years ago. So that's one piece. Part two is the Storage portfolio. So as we've launched and drive our Dell IP storage portfolio, we've now had 6 consecutive quarters of demand growth almost 2x the market. Obviously, a lot of software and service components to that. So the margin rate enhancement from our Storage portfolio will lift ISG profit. And then to your point, we're using those two levers to be able to absorb the demand in AI. So almost 3x growth to $74 billion for the year and mid-single-digit margins we can absorb that with the two other tailwinds and give the outcome that you see, which is record outcome.

Okay. And within that, you also have servers, right? So additional servers, I should say. Just because these are built on next-generation infrastructure, next-generation core processors. Are you thinking about higher margins even for these products?

No. I think from our portfolio, if you think of commercial PCs and traditional servers, it's about more a sustained margin rate. Look, we're trying to make sure we can give as many customers access to the kind of compute power that's there. Our margin lever is Storage. That's our margin lever and then to lean on the scale of the company as we do that.

That's pretty impressive, too, just given the memory inflation that we have seen that you're able to sustain those margins in your core Compute business. Okay. AI backlog, I think you guys talked about $95 billion, but you do have a growing presence of enterprise customers in there, almost greater than 6,500 now. You have talked about both sovereigns and enterprises growing faster. Obviously, the Neocloud dollars is much bigger. But how does -- as you start to kind of drive the neo sorry, the sovereigns and enterprises to revenues, what is the attach rate to those AI? So could that AI pipeline and as it becomes revenue, have higher margins associated with them?

Yes. I guess there's a few things in that. I think -- our value proposition in terms of the wheel house will be that on-prem enterprise customer base demand, which is going beyond the GPU. So traditional server CPU based. So those tokens generating compute power, which generate the data, which generates more tokens. Would you then need storage. So that inflection point in particular, of the storage growth, that enterprise lift that we see, which we still think is very early in its adoption curve right now. I mean you mentioned the 6,500 customers. That's up over 60% in the last 6 months. But it's also -- you could argue the infancy of -- we serve tens of thousands of customers, right? We would argue likely a low percentage pick a number between 10% and 15% enterprises have only done meaningful AI agentic modernization within their company. the rest either haven't started or on the early adoption and kind of proof-of-concept kind of stage. So that element of an end-to-end portfolio from an Edge PC to your storage device, that's the wheelhouse. Are there attached motions tied to Neoclouds also from a storage and a CPU server perspective? Absolutely, we'll look to play there. I think we'll see a better conversion rate for sure on the enterprise.

And do you think that the storage opportunity could be as big as the AI opportunity, AI compute opportunity for those enterprises?

Yes. Look, I think you're not going to see in terms of the same dollar value. But the opportunity, if you look at our guide for this year, we're adding $2.5 billion of Storage revenue to our P&L. Double-digit growth. So that's something we -- you haven't seen us do. This will be a record Storage quarter for the company's history. I think the more and more you see these inferencing workloads and enterprise is adopting these use cases I think we feel it's pretty durable and robust that it kind of lives on as we kind of go multiyear.

Okay. And -- when we talk about that enterprise adoption, there's always been this debate like what is it that enterprises, what is it from a TCO perspective that's getting these enterprises to go on-prem. Clearly, you have -- they have access to the cloud. So what is -- how is Dell quantifying those economics to these 6,500-plus enterprise customers that's getting them to deploy this stuff on-prem?

Yes. Look, the best example I can give is to use our own company as customer zero, if you like, right? So one of the big "Ahas" we get from enterprises, when they come into our executive briefing center and they want to have a conversation about AI, and it's not as dumb down as this, but it's almost "hey, help us turn it on and the world is better", if you like, right? Whereas the reality is there's quarters and years of work to do before you can supercharge the AI in the first place. So we spent the last 3 years in our company, standardizing and auditing and simplifying all the different processes and workflows and cleaning up the data in the company. So many enterprises are the same. We're 42 years old, through nobody's fault, we've had acquisitions that we've done. We've empowered different teams in different geographies to create their own ERP systems and -- but ultimately, what that does is the data doesn't talk to each other within an enterprise. And so if I apply AI to that, it can't access corners of the company to kind of fully supercharge an end-to-end workflow. So you actually spend and it's enduring work. It takes multiyear, and it takes a cultural shift in the company. We were very lucky in a founder like Michael, who stood up in front of the leadership team 3 years ago and pitched this concept of modernization. In other words, if we don't do it, somebody else will do it to us. And so you see that, and where you now see the inflection point is every enterprise customer needs to identify where the value comes from. So for us, it's our supply chain, our products, our services team and our sales team. So within that, AI can be used as a power of productivity, whether that's growth, whether that's product road maps to pick your idea. Every other function should be using AI from a scale and efficiency perspective then, including my own function in finance. And ultimately then you both the decoupling effect of I can grow faster I can scale my business through OpEx spend, and they're not linked anymore. So when we talk about our 8% of revenue, that is now structurally based, and it's only going to get better. It's not going to go back to, well, if I need to grow, I need to add some more variable cost in. We've divorced those two things. They will stay permanently divorced. And I think enterprises that we showcase and we bring them in, they're seeing some of that. But I think they'll all be at different curves. Some will go faster, some will still resist. So I think it will take time for the broader enterprise to get there.

Okay. And when we think about workloads like the ones that reside on prem, private clouds versus those companies are probably still using some sort of public cloud maybe for certain workloads. Just as you think about that, any kind of -- how you think about maybe the split between that? Like do you have any kind of forecast that you think about across the...

Yes. I mean if you listen to the Amazon earnings call from a few weeks ago, they talked about 85% of the data still on-prem. If you look at that perspective. Look, ultimately, it's going to be about the cheapest token you can have is the one that's closest to the data. So for a big take a finance function, like is on linear planning, decision-making and processing. You do not need a frontier model to do that. You can work off N minus 1, N minus 2 models. You can do anything from Power BI up to the lowest form of AI. You can do all that on-prem, on your edge device, in your own data center on your powerful PC. Obviously, there are also proprietary information that drive value for your company that you want to keep in a sandbox and keep away from everybody else. And then there are legitimate workloads you need to send to the cloud in a hybrid world to get supercharged compute power from a large language model perspective and look at that. Finding that right equation and balance we'll find you the right cost structure and efficiency. And that's why we think there's a strong value prop for the print piece of it. And again, because we sell across the portfolio, it bleeds into our storage portfolio, in particular, which is where the value creation can be for us.

Okay. Wonderful. We have seen the transition from full rack solutions. We started this AI journey. It was all about just GPU chips. And now we're starting to see full rack solutions come out from some of the largest chip makers. How do you think about Dell's addressable market opportunity in this space like as we're getting more and more complex, and in some cases, there's disaggregated architectures as well.

Yes. I would say complexity is our friend. We're pretty agnostic in terms of if a customer in any segment is looking for something they need help with to build, we're available to build it with them and have that conversation. Obviously, we have a deep and fantastic relationship with NVIDIA today. The majority of our business is with NVIDIA today. But ultimately, when I say complexity is our friend, we bring and we've defined the value we're bringing to the conversation. So this idea of time to token, any multibillion-dollar deployment, we're on average 4, 5, 6 weeks advantaged in that differentiation to the customer. So in that time to token, the economic benefit they can get from that because it's monetizing is worth all the conversations. So when we procure the inventory to build it to ship it, install it to deploy it, when we turn it on, it stays on 99.9% of the time. We use far less parts than everybody else in terms of that uplift, and we white glove that service. So you get an engineering team and a pad that helps the design of a neocloud design T minus 3 months goes through 30, 40, 50 iterations. They are also the ones who will turn it on and make sure it stays on and almost live on site there as a stint with us in Dell. And so you have that end-to-end kind of relationship. The other piece is because we sell across the portfolio, we can be more fungible with the supply that we've got. So one tangible example, we would have taken a decision in the spring time foreseeing the PC market, particularly in consumer, was going to get squeezed a little bit. It's projected to be minus 18% to minus 20% on units. So we purposely send some of our wafer supply for consumer PCs and reconfigured it for for infrastructure for the second half. Now you can't do that quickly, it takes 5, 6, 7 months to do that, but we made some of those bets then which allows us then to enhance some of our guide for the second half of the year. So that fungibility is a good asset for us, too.

Okay. And it's often lost -- like investors will often ask me, but -- and this moat that you've talked about this time to deployment, which is critical in terms of monetization. Seems lost on investors because often they'll say, well, why can't this business just easily flow through to ODMs? And why is it why is Dell getting more than their fair share? So I think that's a very valid point when you're talking about it. Do you think that, that -- most that you've just talked about time to deployment helps with the underlying AI profitability as you think about the AI compute profitability as you think further down?

Yes. Look, I think we expect that to stay fairly stable from a rate perspective. We're in that mid-single-digit range. Obviously, it's a competitive market. So all those players you just referenced they turn up and bid just like we do in all of these big deployments. We feel that's the right sweet spot because obviously, in a multibillion-dollar deal, mid-single digits, it's still a lot of margin dollars for them, but that's the value point we found for sure.

Okay. And then just shifting to the traditional servers. Obviously, very strong growth here -- the growth is frankly greater, I mean on a year-on-year basis relative to the GPU side of the things. So how big could this traditional server opportunity be, especially when you think about many years that you've seen this business and it does go through a boom in a bus cycle?