Cisco Systems, Inc. (CSCO) Earnings Call Transcript & Summary

Great. Well, thank you, everybody, for being here. Welcome to the Cisco fireside chat at the Goldman Sachs Communacopia and Technology Conference. It's my privilege to welcome Cisco's CFO, Mark Patterson, alongside Cisco's President and Chief Product Officer, Jeetu Patel. My name is Mike Ng, and I cover Cisco and Comtech here at the firm. We have about 35 minutes for today's session. So first and foremost, Mark, Jeetu, thank you so much for being here today. It's an absolute privilege to have you on stage with us.

Thanks for having us.

Wonderful. Jeetu, I'll start with you. In the most recent earnings call, I think you described this as the beginning of a multiyear networking super cycle. So talk a little bit about some of the demand signals, the customer deployment milestones, that give you the confidence that this AI-driven network demand represents a multiyear durable ramp? And also elaborate a little bit about how Cisco is positioned not just for the networking piece of the super cycle, but also the growing security needs that you've been investing and planning for.

Yes. So it's a great question. And so if you just take a step back on what's happening right now, we are -- I think it's nondebatable at this point that this is one of the largest secular shifts that we have seen in a long, long time, if not ever. And if you think about -- there was a very interesting data point that came out in -- with a study from Open Router, which was in February, the consumption of tokens by agents actually exceeded the consumption of tokens by humans. And since then, agents' consumption of tokens has gone up 14x. And now agents consume about 60% of the total inference capacity or the total token volume that's out there. And so that's a pretty meaningful shift. And the second thing that you're seeing is the global compute capacity in the world, 60% of that is being consumed by inferencing rather than training. Why is that significant? Because we are no longer just in the kind of experimentation phase of building a new model, hoping that the volume is going to come. It's actually the models that have been built and people are using them, and they're using them at a pretty hefty rate. And if you think about the fact that there's probably only like sub-2% of the of the humans in the world that are probably using agents in any kind of power user capacity, right? And so this is the first time that you've seen in the secular shift that you don't need to have 70% of the humans using it in a power user capacity for there to be massive kind of supply shortage on -- at a macro level on the infrastructure that's needed. So I actually don't see an end in sight as far as the demand signal because we're just getting warmed up with agents. The agents have not even gone to like 2% of the enterprise yet on going out and automating the business processes. Consumers are just starting to get warmed up with agents. And so this is going to continue for a while from that perspective. So if you assume that the demand signal -- sorry, if you assume that the demand signal continues, this way, which every piece of evidence shows that it does. Then the question is, what are the other tailwinds that are also going to continue to persist. Right now, most organizations need fast infrastructure that's low latency, high performance. These agents tend to be far more consumptive on network bandwidth than humans. So about 450% more network bandwidth gets consumed by an agent to conduct the same task that a human will conduct, right? And so one is you have many, many more agents. You're going to have trillions of agents. These agents are going to be working 7 by 24, and they consume more network bandwidth than ever before, 5x as much as a human does. And on top of that, you then have a huge emphasis on machine scale defense because the attacks are going to be machine scale with agents as well. And so the post-Nthos effect is going to need to make sure that people are saying, I need to have the right level of security and observability for agents. It turns out Cisco is in the center of all of these macro trends, whether it be the data platform, whether it be the observability platform, whether it be the security platform and then the entirety of the networking super cycle for hyperscalers for Neo clouds, for sovereign clouds for service providers and for the enterprise. So I feel like this is a very durable trend for a long time to come.

Great. And just on that, I mean, Cisco was among the first to highlight how get AI traffic was going to impact the network. And I remember that chart very clearly where the human traffic was very spiky. -- genetic traffic was high and sustained.

And physical air is not too far now. And physical AI is not too far now. But I was wondering if you could bring that back to the Cisco business, right, and talk a little bit about how this impacts the portfolio, the Cisco core business growth relative to what we may have seen in historical networking cycles? See in the past, what we used to have, like we missed the cloud wave at Cisco, right? That's pretty well known. And any of these major shifts that have happened, there was a favorable architecture for Cisco and an unfavorable architecture for Cisco. So in the cloud wave, -- the favorable architecture was on-prem, the unfavorable architecture was hyperscalers, right? And we missed that way. Right now, there's 3 variations of architecture that will persist. There's going to be hyperscalers. There's going to be actually some kind of a minor variation of hyperscalers, which is neoclouds and sovereign clouds. There will be the enterprise for on-prem data centers, and then there's going to be the edge. It turns out that regardless of the variance that the market chooses, Cisco has a tailwind, right? If you go into hyperscalers, we have a tailwind because we've actually grown our business on the hyperscaler side in 2 years from almost 0 paper taken on AI orders to $9.3 billion in the last quarter in the last year, in the last fiscal year. You will see the same kind of tailwind happened within the enterprise as people are going to want more control as models go more open source, they might want to have open rates and open source models be on-prem for them. And then what you're also seeing is there's going to be this whole new category of computing or death side computing, where you might have a Mac mini or an AMD or something of that sort on your desk side that is dedicated for agents to run the agents are going to need much more bandwidth even in the campus and branch. So our campus and branch business for networking, which historically was pegged like growing at the rate of GDP 3%, 4%. And has now been growing at like 20% for several quarters. And the reason for that is because you're actually starting to see that we have on a huge LDA cycle, which is the last day of support. And people need to make sure that they refresh their infrastructure because they need lower latency, high performance. The second thing is they can't afford to keep dated infrastructure in the facilities because of the fact that you need to ensure that the post-methos effect doesn't actually create exposure to the business. And third is agents are creating so much more traffic that you have to have a whole different level of traffic pattern accommodation than what you've had in the past. So what you see is not just in the hyperscaler business but also in the core business, you're starting to see a fair amount of tailwinds

Mark, if we could bring you into the conversation here, the fiscal 2017 revenue guidance at the midpoint implies 15% total revenue growth. And even if you take out the AI tailwinds, the underlying is still up double digits. So could you talk a little bit about some of the enterprise or service provider dynamics that are driving this excluding acceleration? How durable is this baseline growth? And where do you see near-term upside optionality if there is any?

Yes. It's what we get asked a lot in terms of how durable is it, right? Or is this just kind of a cyclical thing? And maybe just to reiterate a couple of points that Jeetu made. I think the 3 big things that we're seeing is everything that Jeetu talked about in terms of AI, AI applications, whether it's the models themselves or it's a genetic AI really being built out in the enterprise. -- or just the preparedness for that and the bandwidth, the latency requirements, et cetera, that are being put on the network. That's obviously, I think, the first thing that I'd highlight. The second thing, I think, is just this whole notion of security and networking coming together and the fact that Cisco is very unique that we're both a security player and a networking player. It's -- you're seeing it play out with our smart switches and running Hyper Shield alongside it. You've got the Live Protect capabilities to be able to patch and protect from vulnerabilities as soon as those are known until you can actually do the patching and the upgrades. And then I think just the overall need for modernization and this Mythos effect that is being turned that way anyway. But basically, the frontier models and the way that they're being able to provide the capabilities to really identify and exploit vulnerabilities at machine scale. And so the notion of sweating an asset another year is a very dangerous notion, if you will, where in the past companies, I think, thought of this as sort of a nice to have and really scrutinize the ROI. It's now becoming a security imperative, and you're seeing Boards and CEOs I want to know everything that's in my environment. I want to understand the risks and what's our path to actually upgrading that infrastructure, too. So -- and you're also seeing a huge opportunity from the -- just the need to refresh and modernize infrastructure. So what's coming end of life, end of support for us just in the next few years, we've identified over $100 billion worth of opportunity just for Cisco upgrade and refresh. And by the way, we're going after our competitors end of life, end of support as well, and you're starting to see some of that be reflected in some of the market share reports here as of late, showing that not only are we holding share, but we're actually taking back share in most, if not all, of the networking categories for us. So I think in terms of durability, as you look at each 1 of those sort of 3 big areas that I outlined, those have all been tailwinds for us if you go back a few quarters or even another fiscal year or so. But they're all more pronounced today than they were before, and they're all very early stage in terms of where they're going to be headed over the next few quarters and years. So I think the fact is this is going to be very durable. It's a multibillion dollar opportunity for us in many facets. And and it's kind of this refresh opportunity is creating a bit of a demand floor, if you will, as you look out over the next couple of years. And you're seeing it play out. I mean networking has now been double-digit growth for 8 quarters in a row. It grew 40% actually in terms of orders overall for the company this last quarter. So we feel pretty good.

Great. That makes perfect sense. No enterprise wants to be caught running devices that are under support just given the emerging threat landscape especially not today. as Jeetu always reminds us, these are the worst models that we'll ever see. So 90 days from now, the sophistication is going to be incrementally better. That's exponentially better. Mark, just on gross margins. You have fiscal first quarter 2017 gross margin guidance of 65% to 66%. How much of this gross margin guidance is driven by potentially just lower-margin hardware, scaling into the revenue mix or commodity cost inflation, memory and things like that. As we look throughout the balance of fiscal 2017, how should we think about the trajectory of margins?

Yes, I'd say if you look at the last quarter we've actually been able to manage the memory price increases pretty well and being able to pass the costs on to our customers and largely in part because of the demand tailwinds that we talked about I think that as you look at gross margins overall, there's a couple of things happening here. One is bottom line, as Jeetu outlined this networking super cycle, if you will, we're leaning into these opportunities, and we're shipping a lot of hardware, whether it's predominantly hardware-driven hyperscale space or this significant uptick that we've seen on the enterprise side, while you've got hardware that gets recognized day 1 in terms of revenue, the software that gets attached to it is a subscription and that gets recognized ratably as well as the services that ultimately get put into place also ratable. So there's a bit of a timing difference on that side. But I think what we said was there's sort of a slight headwind to tailwind to the numbers in terms of gross margin as we go through FY '27. And we've looked at the analyst estimates that have come in and feel comfortable with kind of where they're sort of stepping it slightly down as we move through FY '27. And -- but I think the biggest thing to look at, frankly, is operating margins. So while gross margin, there was a headwind. And if you take Q4, for example, gross margin was off about 2 points relative to the year before. But OpEx was actually down almost 4 points in terms of the percentage of revenue and operating margin then was at a record level for the company. up almost 2 points on a year-over-year basis. So that operating margin, we actually did guide, which was kind of unusual because we wanted people to understand that, look, we are going to be dropping money to the bottom line at a faster pace and in a more efficient pace than we have ever before Cisco.

Great. Makes perfect sense. Jeetu, you ttalked about the $9.3 billion of hyperscale AI orders last fiscal year. That does not even include the enterprise and rest of cloud orders that are for -- could you talk a little bit about how you expect Cisco's overall AI revenue mix to evolve? How are you positioning your product portfolio within Silicon One optics smart switches to capture demand across both ends of the hyperscale AI and then the enterprise and rest of cloud orders.

Yes. So just for those that haven't been following it closely 2 years ago, we had said, Hey, we need to do $1 billion in orders taken and put a stake in the ground for AI orders. We ended up the year at 2.3. So we said, oh, seems like it makes sense to double it. So we doubled that the following year and said, why don't we do $5 billion, we ended up at 9.3%. And we literally, in Q4, did $4 billion of orders, right? And so there's clearly momentum there. Before we do that, let me take a step back on like what is the structural shift that happened in Cisco because Cisco has been around for 40 years, 41 years. And when you start thinking about 1 of the biggest challenges that we had is we used to operate like a holding company. We had acquisitions. We had a bunch of GMs running their own businesses. Those businesses actually, each 1 of them was managed like its own feet. And before you knew it, like it was very hard for customers to tell how these things all kind of came together. What we've done over the course of the past few years is we have actually become a vertically integrated platform that is a co-design full stack. We make our own silicon without which we would not have a hyperscaler business because they want choice and diversity from the others in the market. We make our own photonics. We have our own systems business with systems hardware. We have our own system software. We have our own platform for security. We have a platform for observability. We have a platform for data. We make our own models in some cases. for networking and time series and security. We have our own applications, we have our own agents. And we have 1 unified management plane for all of this. So regardless of what you're managing with us, whether it be WebEx or Splunk or Nexus switches or catalyst or Meraki, what have you, it's all managed in 1 management plane, 1 control plane, right? This is a very different Cisco than what it used to be. And that transformation would not have happened without AI, not just from a demand perspective but also because we now have 32,000 of our engineers using AI to build products on an ongoing basis. And the speed and velocity with which we're building has really kind of sped up. We used to get these kind of estimates that to go out and create a unified platform will be 7 to 10 years. In fact, Mark was in the first meeting when we first -- when I took over all product where they actually said that to me. Within 9 months, we were able to go out and get that built. We now have like -- by the end of this year, we'll have half a dozen products that are going to be 100% written with AI. By the end of next year, we'll be like 70% of our portfolio will be 100% written by AI, no human lines of code. So there's a level of momentum that just is -- they're in the business where if you have scale and you can inject speed, that's a superpower that's just very hard to replicate. And we have scale and speed, not just in 1 tier of the stack. We have scale and speed across the entirety of the stack, from silicon and the physics to the semantics, right? And so that's -- that's a hard thing to go out and just say, let's go replicate that. And as we think about our overall business, we grew our orders 35% for the overall business for the past 2 quarters, but ex hyperscalers in Q4, we grew at 25%, which means that we've got these inherent tailwinds. And as Mark said, there's also -- there's not only durability of demand there's also a floor because -- you need people to upgrade your infrastructure. You need people to go out and make sure that you prevent against methods and you need to make sure that your agents are associated with the right level of intro. And so all of those things become massive tailwinds. And then we've got the security and observability with they are kind of fusing together as markets as well. So it's much harder to tell today whether an agent was influenced because of an external prompt injection attack or an agent just decided that it was the right thing to do to go out and escape containment from open AI's container and go attack hunting phase and steal the weights there because it was just following orders to say, go out and make sure that you pass the eval. So the fact that we have both security and observability, and we can fuse them together and fuse them in the fabric of the network creates very asymmetric structural advantage for us that is -- it's just hard to replicate. And that, along with the fact that we've got scale of the number of customers, over 960,000 customers. When we build our own silicon, 1 of the things that you need to have is scale so that you can amortize the cost of silicon across multiple different volume segments. And now by 2029, we will be completely independent of merchant silicon providers because we have made our own silicon. All of these things start to compound on top of each other. And so -- and these are hard businesses to be in, like being in the silicon business is a 5-year planning cycle, being in the agent business is a 3-year planning cycle. Being in the hardware business is a 24- to 30-month planning cycle. Being in the software business is a 12- to 18-month planning cycle, we've actually been able to perfect all of those and have them work harmoniously together, which is why you think about a co-design full stack. And that, I think, is what creates the level of excitement both within Cisco or within our customers and partners. And you can see spring in the step in both our customers and partners as well as our employee base our 90,000 employees ship and operate at a speed of a startup while still maintaining the scale that we've maintained.