Hi, everybody, and welcome to the Dell Technologies keynote at the Goldman Sachs Communacopia + 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 will kick it off with a 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 obligations to update them.
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 have 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. A re we at the beginning of a new enterprise virtualization cycle or enterprise infrastructure cycle? 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. It's a multi-speed world. Not everybody's going to go at the same speed. 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. The data that exists inside companies is being unlocked and unleashed in a new way. They're sort of in this process of figuring out that they have to reimagine their companies. We started this about three 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. What you have to do is map out every single process in a company and then simplify, standardize the process, get all the data together, and then come to the last step is you're applying AI. Also understanding that the AI today is pretty extraordinary, but it's also the worst that it'll ever be.
It's improving, and you can apply technology to replace a lot of the workflows that used to be done by humans, so it can be done way faster. So you're innovative, more innovative, you get speed. 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'll take time. We are seeing with these 6,500 Dell AI Factories in enterprise, we're kind of in this S-curve adoption.
Well, maybe let's talk more about those 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?
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. If you're in advanced manufacturing, you want your AI in the factory. If you've got a restaurant chain, you want your AI inside the restaurant, retail stores, logistics. You've got this wide variety of small models, large models, open models, closed models. We're bringing the frontier models on-prem. 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. 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. 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. 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. Yes, the cloud is a real thing, no denying that, but it's really more of a hybrid multi-cloud. If you think about it, most of the data in the world is going to be created in the future. Again, as we adopt AI and agentify, we create way more software. We're creating more data, and it's all happening in real-time. Again, you want the AI as close to the data as possible. So, this is kind of what we're building out. Of course, with enterprise, we have more opportunity to architect the full solution. You need more CPUs because of agentic behavior, obviously data storage, where we have a leading position, networking has to be re-architected. The frontier models also want to come on-prem with us.
How much does the ROI of these investments drive some of these decisions as well?
I would say this is part of also this change that's been happening inside companies. It used to be we were all talking about the IT budget. What's the IT budget? Is it going up? Is it going down? Is it this? 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. 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. 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?
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. We actually see demand being deferred in many cases. Right now, there are 400 million PCs that are over four years old. Because the cost of memory's gone up so much, you have people sweating assets, so they're just deferring future demand that we know is going to come. Your PC's now five years old, it's six years old, it's got rust around the edges. This is no good. If you're a knowledge worker, you need modern tools, so those will all be replaced. 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 when 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. All of the improvements in the models, particularly from basic LLMs to reasoning to agents, has occurred well within the timeframe required to build a new semiconductor fab. You just have a structural shortage, probably worse in 2027 than in 2026 from everything that we see. Yes, costs are going up. Yes, we price all that through. But customers sort of go through five 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. They tend to go to, okay, are you going to be able to supply us with what we need over the next year, two years? 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.
T alk 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. That's been the 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. We have the broadest set of customers, and they want to know that there's going to be demand in 2032 and 2038. The relationships go back many, many decades. That's incredibly important.
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 $95 billion in AI server backlog, even after converting $130 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 with the 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 power and land, and ultimately, we look through them to understand where the real demand is coming from. On the other side, it's Anthropic and it's OpenAI, it's Microsoft, it's Google, it's Meta, so we want to see those contracts, and if they don't have one of those contracts, not 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. So there are lots and lots of these companies. They're not all the same.
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, so they do need them, and I think a number of them have been super clever in how they've built their businesses. We have given them an incredibly fast time to first token. If we're delivering a massive cluster of these in a super reliable way, and we're six weeks ahead of a competitor, well, that six weeks is worth more to them than whatever premium that we're charging. So it's been a great business and certainly the pipeline and the set of demand opportunities we see is quite strong there.
Enterprise is growing faster, not as big, and you've got this sovereign which is sort of a bit of a hybrid of the two, and it 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?
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 short-term financing that we bridge to all the sort of longer-term sources of capital that want to finance these projects. Of course, many of them want access to the enterprise, which we can help them with. So customers come to us, they're like, oh, I need 5,000 Vera 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?
If you take the top 50 countries in the world by GDP, you can find two or three sovereign AI projects in pretty much every one. These are quite important. Nobody talks about sovereign AI in the United States because it is sort of like the non-U.S. AI thing. But in these countries, it is quite important. Sometimes they are government-sponsored, sometimes it is a telco, sometimes it is 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 is coming. They might be 12 or 18 months behind, but sizable economic activity, maybe half the opportunity is outside the United States. So it is substantial.
Over the last six months, there has been much more of a focus across the industry around the role of general purpose compute, which is really core to Dell's offering. As enterprises continue to modernize, you talked about those 1.3 million servers that are 13th- generation or older. How do you see the opportunity for continued momentum in traditional compute? The company is guiding for 100% growth in your traditional compute business for this fiscal year, but how do we think about the runway and durability of demand beyond fiscal 2027?
Well, one reason why you have durability of demand is you have this massive installed base of old things that have to be replaced. If you are modernizing your company, you are sort of preparing for all this onslaught of cyber threats and even beyond that, sort of the post-quantum encryption challenge. The stuff that is four or five, six years old, forget about it. You are going to be replacing a lot of that. But you still have a lot of traditional server demand that has been there for a long time and keeps growing. Then, of course, you have the agentic behavior, which drives tons and tons of CPU usage. We are just kind of at the beginning of that. So, we see tons of demand. In five years, are we going to be talking about traditional servers and AI servers?
No, it is just all going to be servers. It is a fuzzy line that is going to get blurrier all the time. But ultimately, we are the scaled infrastructure player with incredible operating leverage across our scale in servers, storage, and increasingly data center networking. And with the customer relationships, the supply chain, the services, the financing to be able to continue to lead in the sectors we compete. And we still make PCs.
There you go. We will talk about PCs. But ultimately, AI is running on data. You have touched on this. We have talked a lot about the compute side. You have alluded to the role of data and storage as part of a data platform, but the enterprise storage TAM we will talk about, has not seen the same inflection as compute has. From your view, what do we need to see to build confidence that the storage opportunity is going to be a significant one for the enterprise? Is this more about simply storing more data? Is that what is happening here, or do we need to be more thoughtful about how enterprises are moving and protecting and extracting data from these platforms?
There has always been a lot of data, and data has been at the center of everything sort of important and interesting, and if you want to do AI, you need data. No data, no AI. Bad data, bad AI. Actually, as these models get more powerful, you are creating more and more data. We have the broadest portfolio of enterprise data storage. Increasingly, these AI factories have our PowerScale and ObjectScale storage platforms attached to them. You have seen the sort of acceleration in the storage growth. With our pivot to Dell IP storage, 26% growth in the last quarter. Again, we are largest there, larger than number two, number three, often number four combined together. Yes, I think AI is making better AI, that is creating more data, and then that is making better AI.
It is sort of a self-improving process that is driving demand. Again, most of the data will be in the real physical world. By the way, we are talking about AI on the screen, we are not even talking about AI in the physical world, which is just starting to come with robotics. That will be another massive demand driver.
For enterprise storage?
For enterprise storage, for sure. Multi-robot agent coordination in factories and transportation. Everything generates data and requires data to make it more intelligent and more effective. We have leading position, leading capability there.
Off my PC question now. We have talked a lot about the data center. Intelligence is also moving closer to the edge, mostly through endpoints like the personal computer. How does this change your outlook for the PC opportunity overall? Obviously, a very significant leading enterprise portfolio there, but how does this change your TAM outlook as well as Dell's strategy within the PC category, especially as you navigate these input cost increases the broader industry is digesting?
The device market has been challenged, b ecause the cost of memory has gone up so much. If you look at our PC business, last quarter revenues grew 20%, and units, that didn't do so well. Average selling price is going up. What's happening is you are actually growing the install base of older machines. You are deferring this future demand into whatever. It is either some breaking point where it is like, my computer is too old now. You expect me to work at this company, you need to give me a computer that actually works. If I want to use AI, I have got to have a modern computer. I need better tools. Or it just breaks, stops working. It is too old. Again, I think the most cost-effective token is going to be the one generated closest to the data.
These small models are operating locally, and it will continue to be a hybrid architecture. The PC is still the productivity device that people use in the modern world to get things done.
Across the breadth of your portfolio, PCs at the endpoint edge all the way into the AI Factory with your full stack solutions there, how has the breadth of your portfolio helped with the sales motion and bringing to market to your customers a variety of solutions that might help them in different operating environments, cost constraints, things like that?
Some of you will remember, almost exactly 10 years ago, we bought EMC, combined with EMC. Our presentation to our customers was we are number one in everything, all in one place. It has worked out quite well. We have continued to gain relative share and scale. That is basically still the same story with customers. Let us say there is 10 different areas or 20 different areas. We are number one, pretty much every single one. You can buy 20 things from us, or you can buy 20 things from the number two company, but it is 20 companies. Nobody wants that. We continue to gain share really in all these categories, and we have this compounding advantage of scale, cost structure, the aggressive application of modernization, AI inside our own business to deliver great value to customers.
Does that create a stickiness in your customer relationships as you think about your enterprise buyers potentially re-architecting or rethinking their broader infrastructure stack? The fact that you can be one vendor who provides all of those types of engagements in what is sometimes considered to be a commoditized hardware industry.
I believe it has. Because we have everything and you sort of wrap it with services and with Dell Financial Services as well, and you just make it easy for them. It does not mean we have a license to just do whatever we want or price it ridiculously high. We have to be competitive and deliver great value to customers. That is absolutely what we do, and we do what we say we are going to do. We do it reliably. Customers can count on us. Particularly now, when there are these supply chain challenges, they know from prior periods, we deliver what we say we are going to deliver. Not everybody does that.
We have talked about all the ways in which Dell is helping your customers implement AI, but you are also a large enterprise yourself. On earnings last week, the company talked about record low OpEx rate levels. You are being very efficient in driving operating leverage. What are the applications of AI that you are seeing be most successful internally within your organization, and how does that help in the sales motion to customers?
We started this modernization a little over three years ago. Essentially, I stood up in front of our leadership team and said we were going to have a new competitor five years from now. This competitor was going to be in every business that we are in, except they are going to be more innovative and faster and lower cost, and they are going to put us out of business. The only way we are going to prevent that is we are going to become that company. You look at our OpEx as a percent of sales, we are down to roughly 8%. Pretty extraordinary operating leverage. We have totally decoupled revenue and cost. How have we done that? Well, it is back to reimagining the outcomes and mapping out every process in the workflows, agentifying everything that we possibly can, and we are still going.
There is still a long way to go here. That is super helpful. Customers want to learn about that. They want to know how we have done that, and they need a lot of help doing it. It is not an easy thing to do. Not everybody has the appetite to do it, but it has put us in a great position to be able to. Obviously, with an 8% OpEx, we can sell things at a given price and earn a very nice operating margin.
There are many companies here today at this conference overall that are participating in AI, but few have Dell's combination of portfolio breadth, customer relationships, and global reach, importantly. When you think about these sorts of advantages over the course of the next 5, 10 years, what stands out to you as most differentiated for Dell?
I think the breadth of technology portfolios is incredibly difficult to replicate. Plus now we have this scale advantage and operating leverage that's just extraordinary, and we have an execution-oriented machine. That's kind of what we do every day. The supply chain relationships, t hey've always been important. They're more important in times like this. But it's always been a durable advantage for us. Ultimately, we have a process and a set of systems that allow us to understand what the unsolved problems are for customers, and then quickly go create the innovations with our own teams and with lots of partners to be able to go solve those problems. It's an enormous overall market that we operate in, and we're well positioned to deliver value to our customers and ultimately our shareholders through that.
Obviously, look at the financial model, operating leverage, negative cash conversion cycle, how we deal with capital allocation, our share repurchase, dividends. It all works.
We have a few more minutes here, but maybe just in closing, can you talk to what your vision is for the future of Dell across these four major product line items that you participate in, and what you think investors should be paying most attention to in the years to come?
I really do see that we're at the beginning of an S-curve adoption in infrastructure related to this takeoff in intelligence capability driven by data, and that is just going to require enormous amounts of infrastructure, and it will be everywhere, actually. It'll be at the edge, it'll be in the data centers, it'll be the neoclouds, it'll be the hyperscalers. It'll be all over. I think we've also opened up enormous amount of development capacity, because of AI changing the way we develop products. The speed at which we're introducing new features and capability is massively accelerated. Put all that together with what I said previously, I think a great set of opportunities. I think the operating leverage might be the part that is not completely understood by everyone because they're just not used to it. We're just kind of different.
Great. Well, Michael, thank you very much for being here and joining us today at the conference.
Thank you.