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

Hi, everybody, and welcome to the Dell Technologies keynote at the Goldman Sachs Communacopia and Technology Conference. I have the privilege of hosting Michael Dell, CEO and Founder of Dell Technologies. My name is Kat Murphy. I cover IT, hardware and Dell here at Goldman Sachs. We have about 35 minutes for today's discussion. I'll kick it off with the Safe Harbor, and then we can dive right into it. This presentation contains forward-looking statements based on Dell Technologies' current expectations. These statements involve risks and uncertainties that could cause actual results to differ materially. Factors that could cause results to differ are discussed in Dell Technologies' periodic reports on Forms 10-K and 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. So with that, Michael, thank you very much for joining us here today.

Thanks for having me. Great to be here.

To kick it off, Dell has been at the forefront of multiple technology eras with leading portfolios in PCs, servers, enterprise storage and most recently, in AI rack scale infrastructure. You've talked in the past about how the data center, in particular, is moving from being thought of as a cost center to a center for value creation. I was wondering to start, if you can talk about where you think we are in the role of infrastructure for an enterprise. And are we at the beginning of a new enterprise virtualization cycle or enterprise infrastructure cycle? And how might that compare to prior transitions?

I think we're in this sort of gradual process where more and more organizations are figuring out that AI is incredibly powerful in terms of reimagining how they achieve outcomes in their business. And it's a multispeed world. Not everybody is going to go at the same speed. But it is quite evident that this is very different than the technology of the past. We had sort of calculating and computing and now we have intelligence. And the data that exists inside companies is being unlocked and unleashed in a new way. And they're sort of in this process of figuring out that they have to reimagine their companies. And we started this about 3 years ago. I would say maybe 10% or 15% of companies understand that this is a really important thing, and they have to go do it. A lot of them are very confused about what to do, how to do it. There's an easy first phase of this, which is you just give individual people better tools and they can be more productive in doing whatever they were doing. Maybe they could do it 10% better or 20% better. That's kind of extraordinary in and of itself, but that's not really the plot. The real opportunity is reimagining the whole workflows. And what you have to do is map out every single process in the company and then simplify, standardize the process, get all the data together and then kind of the last step is you're applying AI. And also understanding that the AI today is pretty extraordinary, but it's also the worst it will ever be. It's improving. And you can apply agent technology to replace a lot of the workflows that used to be done by humans, and so it could be done way faster. So you're more innovative, you get speed. And I would say we're really at the very beginning of that in most companies. They don't know how to do it. It's hard. It's also the barrier to adopt technology, it's not technology. It's people, it's cultures, it's regulation, it's courage, and it will take time. But we are seeing with the 6,500 Dell AI Factories in enterprise, we're kind of in this S-curve adoption.

Maybe let's talk more about the 6,500 AI Factory customers. Can you talk about how Dell's AI Factory model helps customers bring AI closer to their own data while also getting the benefits of the broader AI ecosystem?

Right. So as customers go through this, they begin to understand that it's not one size fits all and you really want to have the AI as close to the data as possible. So if you're in advanced manufacturing, you want your AI in the factory, okay? If you've got a restaurant chain, you want your AI inside the restaurant, retail stores, logistics. And you've got this wide variety of small models, large models, open models, closed models. We're bringing the frontier models on-prem. And for your most valuable data, your proprietary data, your hard-fought knowledge that only you have inside your company, you don't want to send that off to somebody else. And so we're seeing tons of this infrastructure being built around solving that problem. But again, it takes some time to organize all that, pick the right models. And this is what we help our customers do. We have hundreds of reference platforms, starter kits, blueprints and a variety of partners in all sorts of verticals. And so we can help customers kind of get going here. But it takes time. There's an instinct to want to just say, okay, I press a button now I have AI, right? And it's way more complicated than that. It just takes time.

Talking more about this idea of moving on-prem as a function of protecting your hard-earned data. What are some other considerations that are driving unit economics and considerations to repatriate data, move workloads on-prem, a hybrid model as opposed to that cloud model?

Well, by various estimates, 85% of data is still on-prem, right? And so yes, the cloud is a real thing, no denying that. But it's really more of a hybrid multi-cloud. And if you think about it, most of the data in the world is going to be created in the future. And again, as we adopt AI and identify, we create way more software, we're creating more data, and it's all happening in real time. And again, you want the AI as close to the data as possible. So this is kind of what we're building out. And of course, with enterprise, we have more opportunity to architect the full solution where you need more CPUs because of agentic behavior, obviously, data storage where we have a leading position. Networking has to be re-architected. And the frontier models also want to come on-prem with us.

So how much does the ROI of these investments drive some of these decisions as well?

Yes. I would say this is part of also this change that's been happening inside companies where it used to be we were all talking about the IT budget, okay? What's the IT budget? Is it going up? Is it going down? Is it this? And so now companies sort of understand that this is how you become more efficient, how you become more innovative. If you had 200 people doing something, now you can have 50 people doing the same thing with $10 million of AI spend and it costs half as much. And it actually works better. And so what's happening is the CEOs, the business line executives, they're all figuring out, we need AI to be more competitive, to be more innovative, to be faster. And so the conversation is sort of leaving the traditional budget discussion because this is actually how you create value inside companies.

On the point of IT budgets, there's a lot of questions today from investors around the durability of demand for hardware spend and maybe looking through Dell's very strong recent results and trying to understand how much of that might be attributed to pull forward or otherwise pricing increases parsing that out from the uptick in demand. Can you talk about, from your vantage point, what gives you confidence that this is a durable demand vector and not some of these more idiosyncratic issues that are happening right now in the market?

Yes. I think this goes back to sort of the fundamental root element here, which is the creation of intelligence and just the demand for that inside organizations. And we actually see demand being deferred in many cases. I mean, right now, we have, there are 400 million PCs that are over 4 years old, right? And because the cost of memory has gone up so much, you have people sweating assets. And so they're just deferring future demand that we know is going to come. And the PC is now 5 years old. It's 6 years old. It's got rust around the edges. This is no good, right? If you're a knowledge worker, you need modern tools. And so those will all be replaced. And then in servers, we have 1.3 million servers that are 13th generation or older. Some customers have definitely not refreshed because they thought the price went up too much or wasn't going to keep going up or whatever. What I see and I step back and think about this is the ROI that customers have and that the NeoClouds have and that exists around compute is pretty extraordinary, and that's what's driving the demand. And all of the improvements in the models, particularly from basic LLMs to reasoning to agents has occurred well within the time frame required to build a new semiconductor fab. And so you just have a structural shortage probably worse in '27 than in '26 from everything that we see. And so yes, costs are going up. Yes, we price all that through. But customers sort of go through 5 stages of grief. It's like, okay, price went up. I don't really like that. You know what's worse than that is they don't have availability because they can't run their business, and that's a disaster. And so they tend to go to, okay, are you going to be able to supply us with what we need over the next year, 2 years. And so that's what we work on with our customers. But we watch closely for any signs of double ordering or things that are not being utilized, and we don't see that.

To talk more about the ways in which Dell's supply chain execution has helped in many instances, gain share in some products and navigate through a lot of the constraints that you've talked to? You've talked in the past about the nimbleness of your operations, the strength of your relationship with suppliers. Why is that a moat more now so than ever? And how should that compound over time?

I think the tighter the supply environment, we're probably going to do better. I mean that's been heuristic for a long time. We have incredible relationships with our supplier partners. We also have this broad portfolio. We can sort of move supply around to where the demand is. They also know that we are a reliable counterparty that will continue to require the output of their high CapEx investments through all the cycles. And we have the broadest set of customers, and they want to know that there's going to be demand in 2032 and 2038. And the relationships go back many, many decades. And so that's incredibly important. And also, the volatility of our demand signal and the integrity of our demand signal is, we believe, the best in the industry because we're more directly working with customers of all types. And we see what the actual demand is from the end customers.

That's very helpful. Switching gears, I want to talk more about the AI server opportunity. You exited the quarter with $3.8 billion in AI server backlog even after converting $3.2 billion in orders in the last year. NeoClouds is a big part of that story still today. Investors are naturally comparing the AI server opportunity within NeoClouds to that of the x86 server cloud build-out of the last decade. We touched on why this is a different technology transition than the cloud. But can you help us better understand why this NeoCloud customer may be a more durable customer than the cloud customers of a decade ago and thinking about how sticky that type of opportunity might be?

The NeoClouds have done a very good job finding powered land. And ultimately, we look through them to understand where the real demand is coming from. And on the other side, it's Anthropic and it's OpenAI, it's Microsoft, it's Google, it's Meta. And so we want to see those contracts. And if they don't have one of those contracts, interested. So we're really understanding what's going on and why this demand is occurring. I think it's also maybe not completely appreciated what's going on with sovereign AI and demand outside the United States where there is power also and lots of customers. And so there are lots and lots of these companies. They're not all the same. And when this started many years ago, I think a lot of the sources of demand maybe thought that they didn't need them. And it turns out the demand has been way more than anybody thought. And so they do need them. And I think a number of them have been super clever in how they've built their businesses. And we have given them an incredibly fast time to first token. And if we're delivering a massive cluster of these in a super reliable way, and we're 6 weeks ahead of a competitor, well, that 6 weeks is worth more to them than whatever premium that we're charging. And so it's been a great business. And certainly, the pipeline and the set of demand opportunities we see is quite strong there. But enterprise is growing faster, not as big. And you've got this sovereign, which is sort of a bit of a hybrid of the 2 and also has public sector in there.

Can you talk more about how the complexity and the rate of change in some of these AI platforms and chips is also creating a competitive advantage for Dell?

Yes. The complexity is our friend because it's complicated to install, deploy these things, make them operate reliably with incredibly high uptime, and orchestrating all the supply chain. It's not just the engineering and innovation, it's all the other aspects, including our kind of short-term financing that we bridge to all the sort of longer-term sources of capital that want to finance these projects. So, and of course, many of them want access to the enterprise, which we can help them with. And so customers come to us, they're like, oh, I need 5,000 [ Rubin ]. Okay. Well, you're not ready to build your own data center, but we have this partner over here. And so we help all that happen.

Can you also talk more about the sovereign opportunity and maybe the opportunity within the public sector as well that you talked about?

Right. So if you take the top 50 countries in the world by GDP, you can find 2 or 3 sovereign AI projects in pretty much everyone. And these are quite important. Nobody talks about sovereign AI in the United States because it's sort of like the non-U.S. AI thing. But in these countries, it's quite important. Sometimes they're government sponsored, sometimes it's a telco, sometimes it's just private industry. But there are lots of reasons why these are occurring. And I would say, in some countries, the adoption has been a little slower than the U.S., but it's coming. They might be 12 or 18 months behind, but sizable economic activity, maybe half the opportunities outside the United States. So it's substantial.