Akamai Technologies, Inc. (AKAM) Earnings Call Transcript & Summary

All right. Good morning. Thanks, everybody, for being here. Last day of the conference. My name is Frank Louthan. I'm the senior telecom analyst here at Raymond James. We're very pleased to have Akamai Founder and CEO, Tom Leighton, here with us. We're going to start out with a few questions and then we'll save some time at the end for you.

But Tom, maybe kind of walk us through the Akamai story, kind of where do you fit into the space and what you do to kind of set the stage for everybody.

Sure. Most of our revenue is in security, growing at about 10%, market-leading products for web app firewall, stopping DDoS attacks, bot management and more recently, API security and Guardicore Segmentation growing very fast. So in Q4, they delivered $90 million, growing at 35%. And so they're driving a lot of our future growth. A lot of investment around AI-related kinds of security as enterprises adopt more use of AI. That's a big new attack surface, so developing the capabilities there. Fastest-growing product area is our cloud infrastructure services, finished $94 million in Q4, up 45% year-over-year. Even more exciting, we think that will accelerate through this year. So we're calling for 45% to 50% growth in revenue, really, really exciting. A lot of big name companies using our cloud infrastructure services and including all the hyperscalers, which is a pretty cool validation. And of course, we operate the world's largest content delivery network, the largest and most reliable and scalable by a good margin.

All right. Great. So you mentioned the compute platform. Talk to us about how that's kind of changed the business. What are customers looking for when they come to you for compute? And how does that kind of change your go-to-market approach with customers?

Yes. What we're trying to do for compute is the same thing we did for delivery when we created the content delivery marketplace. And then with security, created -- security is a cloud service, WAF operated in over 4,000 POPs and 700 cities, so we can stop all those attacks before they get anywhere near the data center. By being close to users, it's better performance, more scalable, more reliable. And now it's the same story for compute. We can get our customers' compute logic close to users. So it's faster, very scalable and at a very good price point. So it's very competitive in the marketplace.

Yes. Closing that distance comes up all the time with investors, the concept of just needing compute nodes near population densities and so forth. So with that, you've got your inference cloud product that you're launching. Talk to us about that. How does that fit in with the compute platform? And what can investors expect from that business?

Yes. As we look to the future, a lot of the use for compute is going to be AI inference agents doing things on behalf of enterprises and users. And a lot of the applications people are developing, you want to have low latency. Now historically, that was hard to do with AI because the models were slow. And if it took you a few seconds for the model to generate a response, well, it didn't really matter if you were close. But now with the latest generation of hardware, and we're deploying a lot of the new Blackwell 6000s. They are fast in response. You can generate videos pretty much on the fly. And so now the latency means something. Not only that as the web gets more of these agents and apps deployed, it's going to be more use of video. And that's bit intensive. And so even if you didn't care about the latency, which you do, you have a problem with bandwidth coming out of a data center. And so it's not possible, for example, to have millions of concurrent sessions with users that are video-based with personalized video coming from a data center. Same thing just like with -- from streaming big sporting events. You don't do that from a data center or 2. You've got to do that in a distributed way. And so Akamai, we have this fabulous unique distributed platform, perfect for AI inference in the future.

So you've got a lot of the critical components here. So when we look at AI, where do you expect to have the most revenue impact? Is it going to be -- you got delivering traffic, AI bot mitigation, compute inferencing at the edge. Where do you think you're going to see the most impact from AI on all the different parts of your business?

First compute, then security, then delivery. Compute because that's where the action is with AI, you have all these individualized responses. Security in a variety of ways. First, the models are enabling the attackers to do more penetrations and be more capable, so you have more need for security services, especially Guardicore Segmentation. Second, as enterprises use AI in more places, that's a whole new attack surface and you need special defenses, which we supply with our security business. Also with the bot management or the agent management, you want tailored individualized responses based on who the agent is and what it's doing. And that's what our bot management solution does. And so that's very helpful. And then third is delivery. Now with delivery, the revenue generally is based on traffic, which is generally gigabytes delivered. Now the big sources of traffic on the Internet are video and big software downloads, so a big gaming release. A video is orders of magnitude more traffic than an image. And an image is orders of magnitude more traffic than a text, an interaction buying a sweater. And so the agents themselves aren't generating a lot of traffic per se. There can be a lot of hits, but not a lot of traffic. Where you will see the traffic generated, I think, as more of the applications on websites become video-based and more of your interaction with the web is video. You're talking to your shopping helper. And it's a person who you know and it's a video of a person, and you're getting real-time responses. And then your personal shopper says, hey, look at this sweater, here's a video of you wearing the sweater at a dinner part, okay? And so it's a personalized video. That will generate more traffic. That said, the value in terms of revenue is more for the generation of that video than the transmission of it. So compute would have more revenue benefit for it.

Okay. And so if we -- let's look at this as customers move to more to block it from optimize it on the CDN side and security, how are you positioned to kind of benefit that as you're -- because with all of this traffic, there's some of this traffic that you want to get through and some that you don't. And so how are you -- on the security side and the delivery side, how are you able to get some traction there?

Yes. We've been doing that since before AI. There's all sorts of bots out there and agents doing different things. There's been scraper bots out there for, well, a decade, doing all different kinds of things for scraping. Now there's a new scraper bot doing it to train models for AI. But there's been just a whole plethora of different kinds of bots doing different things, and our bot management solution gives a differentiated response that our customers want to give. It could be a partner bot, you want to give a good service. It could be a Google search bot, you want to give it a version of your site with all the right keywords and make it fast. It could be a price scraper bot, you want to give it false prices because it's your enemy trying to undercut you by $0.01. Could be a bot trying to fill up all the seats on your plane so that you'll buy the competitors' seats. And so we've been dealing with that for a decade. So there's nothing really new there. There are the AI bots now, and that traffic has increased, particularly the scrapers so far. And so we just continue to give whatever service -- differentiated service our customers want to give.

Yes. Okay. So talk to us about the compute platform. I get this question a lot from investors, and I think from a lot of generalists and so forth. So how is your compute platform differentiated from your competitors? And what is it about customers using your platform versus kind of the house names and the hyperscale world of large compute companies that we all know. What is it about your business that attracts customers?

We're more distributed. So we're closer to the user, gives you better performance. We're extremely reliable. I think that's really important. And we're very competitively priced. And I think a great proof point is all the hyperscalers use our compute platform to do mission-critical things. And it's not like they don't have their own big cloud platforms that they can use, but they'll get better performance for particular applications where that matters using Akamai.

What's an example of some of those applications? Because -- and just to get like a real world something that you're able to do maybe an application or a product that everybody is familiar with that your platform is much better suited for than just the generic thing on one of the large hypescalers.

Right. Well, one of the hyperscalers uses us for live video. So if you watch a lot of sports online, you're actually using our compute platform. And they chose us over their own capabilities, again, because we're close, so they can tailor the event that you're seeing to give the best possible viewing and to synchronize it. So everybody sees the action at exactly the same time, which could be useful if there's betting applications. Another hyperscaler uses us for ad selection, which, again, you want to do really fast, and it's better if you can do that locally. Of course, we have a lot of commerce companies and speed makes a lot of difference there. And as you adopt AI, you're going to get a much richer experience, translates into a lot higher conversion rate and performance matters a lot. Reliability matters a lot there. One of our very large new customers has capabilities to manage fleets of robots, cars, automated kinds of things. Again, you want that to be as real time as possible.

Okay. Great. And so then on the distribution side, talk to us a little bit about the status of sort of self-provisioning for CDN and how do you maintain relevance with all the large media companies and so forth. We've seen some M&A in that space recently with Warner Bros. How does that impact you? And talk to us about the supply for that.

Yes, I don't think there's any impact from the acquisition. Both sides use us extensively already today. There's a couple of exceptions, big media companies that do it all in-house. But otherwise, most of the rest primarily have most of the traffic with us. And most of them do some kind of load balancing among CDNs. But in generally, situations we'll have a majority share.

Okay. And that business trended pretty well for the industry last year. Pricing was a little bit better, traffic better than folks thought. What is the longevity of that? Do we expect -- is that -- have we kind of reached a plateau for that sort of business? How do you -- what's sort of the outlook for that going forward?

Yes. We've guided this year mid-single-digit decline in the delivery business. Revenue is the combination of traffic growth and per unit pricing decline. We're continuing to be very diligent about the pricing we offer. There is business that we don't take and share we don't take. And some of the big spiky events, we won't do if the economics aren't right. So we, I think, are seeing better traffic the last year or so and looks like that trend should continue. And we're being a lot -- very diligent on the pricing. And so that helps us. There's some revenue we let go somewhere else, but it helps our business and certainly the profitability of that delivery business.

Are you seeing any aspect of that business, especially with AI traffic and so forth, where customers are willing to -- are seeing value to using you and paying more? Are we seeing some stability of that? I've seen that in some other areas of my coverage where the hyperscale customers want -- they want execution, and they want it as quick as possible, and they're willing to pay better margins to some infrastructure companies and so forth. Are you seeing the same thing for some delivery applications and maybe that's getting a little bit extra life?

Yes. We generally are paid more than the competition, depending on the particular product and the application could be a lot more to a little more because we offer better performance, and we are a lot more reliable.

All right. So let's talk a little bit about security on that side of the business. How is pricing holding up on security? How should we think about that for the...

Pricing is holding up well there. We have the market-leading solutions by a good margin. And in some cases, this year, we'll be increasing pricing. As you know, the cost of memory has gone up quite a lot in the last few months. And so some of that will be passing on to customers.

So how does that cost of memory affect your business? Talk to us about the capital investment you have to make on the security side. And is that an impediment to your growth? Are you seeing any issues with your ability to get the memory? Or is -- how does that...

No. It's not an impediment to growth. We can get everything that we need. We're a big buyer in the marketplace, but it's more expensive. So we're doing a lot internally to buy less than we might have otherwise. A lot of our servers that we might have decommissioned this year, the math has changed on their useful life. And so we're going to leave them in the field. And they'll be working longer just because the memory cost has gone up so much. We've estimated that this year, after all the puts and takes, it will be an extra $200 million for us in the increased pricing. Usually, with these things, the supply gets increased, the capacity and the production has increased, and that will help abate the cost going forward. We're not counting on that. So we're doing everything we can to optimize, but we -- it will be an extra $200 million this year.

So when we look at that -- what is the breakdown of that $200 million from additional data center space or servers? Or what do you -- what is it...

That's purely the memory cost.

That's purely the memory cost Okay. So it's not -- you're not having to -- if you're keeping these older servers on, are you having to take on more data center space to...

No, it's just we're not taking on as much CapEx, buying less of the memory, using the stuff that a little less efficient. It's not a 6-year-old server, but working fine. And now the math has changed so that we're going to keep it in service longer.

Okay. Great. All right. So with that, thinking about the guidance for the year. So what does it take to kind of reach the high end of the guidance for this year? And let us -- what are your -- what's kind of built into the assumptions for that?

Yes. So the amount of traffic can be variable and a strong traffic year helps the delivery business. How fast we sign on the new compute business can make a difference towards the back half of the year. Security, that's a little bit more predictable. There are sometimes license deals, particularly as you get, for example, sovereignty, other issues with critical infrastructure, maybe they want it in-house, which we can do. And then the accounting treatment is different if they take control of it versus our taking control as a cloud service. So that can swing things a little bit. Dollar fluctuations can make a little bit of a difference. If the dollar is stronger, that can depress the revenue through the conversion a little bit. Dollar weakens, the revenue goes up.

Yes. Okay. And then walk us through the path of inference cloud for the year. You're making an investment in that. I think it's roughly $100 million, something like that. Walk us through the pace of that investment. And then when do we start to see that revenue coming in? How actively are you selling it? And when will we start to see that showing up in the income statement?

Yes. We talked about a $250 million investment into inference cloud and a large purchase of the Blackwell 6000s. The initial tranche we deployed last fall in 20 cities. That actually goes GA at the end of the quarter, but it's already sold out from the beta customers. So we're deploying a much larger tranche now. And as we talked about on the call, we have a good chunk of that already committed in a 4-year deal with a large account. And as we sell out the rest of it, which is not deployed yet, then we would add more after that. The revenue associated with the tranche that we're in the process of doing now, we'd be looking at towards the end of the year to start to get revenue. First, we got to get the servers. We've got to deploy them, get them all turned on and then used. So that's towards the end of the year, we're looking for revenue generation there. So that's really more a big impact next year.

And is this incremental data center space that you're taking on this year to deploy that? And have you had any issue -- how about how many -- roughly how many megawatts of space does that require?

Yes. So a bunch of it we already have from -- as we initially deploy, we signed long-term colo deals for increasing amounts of usage. We are adding new data center space now on top of that. So it's a blend. The typical large-sized data center for us now is 10-ish, maybe 10 to 20 megawatts that we take on as a large-sized data center for us.

Okay. And then as you -- with breaking down some of that investment, how much of that is the servers? How much of that is the data center space you're taking on to deploy this?

Yes. So that would be the CapEx side of things. The -- so the -- say, the Blackwell 6000s, associated hardware. Typical use cases are not just the 6000s, but we use actually our whole platform. And so it's the CapEx needed for that. In addition, there's colo space that, in some cases, we're already paying for or is already on our books because you linearize the counting when you take on a longer colo deal. And in some cases, it's new.

Okay. And so you mentioned there's 20 -- I think you said 20 cities that you'll be going to. The thing that, I think, is interesting for me being a telco guys is looking at the 4,600 locations you have on the delivery network and being able to -- finally being able to use that to bring this elusive concept of edge computing that has never seemed to have materialized, and you are finally in a position to do some of that. So as you look out at that network, talk to us about -- this is a question I get a lot from investors, like why couldn't they do -- how much can they deploy and where can they go? And one of the gating factors there is the power because a lot of your locations are on telco data center facilities or telco facilities that were built for voice. And so maybe you have a little bit less power. But if you look at all those locations, how many of those can you realistically deploy? I mean you're looking at inference cloud, how many megawatts does it take to put a pod of servers out there and GPUs? How should we think about that?

Great question. And the answer is it's hierarchical and depends on what you're trying to do. So in all 4,300 locations, 700 cities, we operate function as a service, our EdgeWorkers solution. So that's everywhere, totally serverless, and that's been out there for a little while now and used actively. Then the next tier up would be our managed container service. And this is where we deploy customer containers in software into our existing hardware. So no extra deployments and stuff needed. Now that can go into any of the 4,300 locations. We're actually using it live today. It's been between 100 to 150 cities. So not all of them, but 100 to 150 of the larger regions. And actually, one of the hyperscalers is using that capability today. And that does your container. Then stepping up another level is you have full stack compute and storage, VMs, big storage, object store. And that runs today in 36 cities, about 40 data centers. That's where we're deploying by and large, the Blackwell 6000. Now we're in 20 cities today. And the next tranche will be maybe some new locations, but mostly beefing up the existing ones for the next tranche of the 6000s.

So the critical place is having it in the city, not necessarily in all 4, 5 or 6 POPs in the city for having this deployed.

Yes. And you're right, the 6000s, they're not going into the 4,000 locations, and they're not set up for that. But they could go into 100 to 200 cities over time.

Okay. Great. That's great. All right. Well, why don't we see if we have any questions from the audience, and I got a couple more. Eric, go ahead.

Who are the buyers of the new full stack that you're building out?

Usually, it goes to the CIO. You mean by the function -- job function or...

The kind of organization. Are those hyperscalers or more enterprise buyers?

Enterprise buyers, including the hyperscaler companies. But yes, the major enterprises for us initially was big media. Now commerce is heavily engaged. And our biggest customer is industrial.

Did you mind a follow-up?

Yes, go ahead.

And how do you normally price these? Are these 1-year deals? Are they -- if they're longer, are there escalators for things like memory...

Again, it's hierarchical depending on what you want to do. So you can buy product-led motion on the website. It's $2.5 for a VM hour, and you buy 1 hour, if you want. Then as the customers get larger, now you're probably in a sales-led motion. Often there'll be a commit to a certain amount of usage over a period of a year, 2 years, 3 years and the reps comped for longer-term deals. And what's new for us now is you can buy clusters, and that would be multiyear commits. And we talked about our first customer in that motion that with a 4-year $200 million commit, and they're basically buying a cluster of the GPUs.

And what does the revenue kind of breakdown look like that at the low end of a cluster? What are we talking about as far as monthly recurring revenue, just to get an idea?

Well, it depends on the size for the monthly recurring revenue. But if you buy at list, $2.5 oer VM hour, obviously, if you're buying a cluster for 4 years, you're going to pay a lower rate than that.

Yes. Okay. Great. All right. Any other questions from the audience? All right. Okay. So talk to us about capital allocation priorities for the next 12 months. How should we think about that?

Pretty much where we've been all along, I would say. We buy back the equity generally that we distribute to employees. We opportunistically buy back a little bit more on average, maybe 1% of the equity outstanding a year. Last year, we bought back more, more than we'd ever done before, about $800 million. Part of that was we did a convert and as part of that, bought back some as part of closing the convert. But our strategy is the same. We use the capital for M&A. We also use it, obviously, for CapEx, which is part of the operating of the business. But there's no intended shift in terms of our use of capital and buying back stock.

So -- and then talk to us about M&A. You bought quite a few different companies. Usually, it's -- you're buying a product, you're buying a capability, it's more of a buy versus build strategy. You're clearly -- you're building the inference cloud yourself. What kind of -- where do you see opportunities for M&A? Is it in security? Is it in the compute? Where you think the things to plug in some platforms?

Yes, we're looking in both areas. Security, very fast-moving landscape. So obviously, a lot of interest there. We've been very happy with our major acquisitions there with no name for API security and Guardicore for micro segmentation. There's other areas we're looking at. We're also -- we're very disciplined. So we're not going to pay a crazy amount of money for something. It has to be something that will return real value to shareholders. And on the compute side, we're looking at ways that we can enhance our capabilities there. It's not quite the same thing as security doing a lot of the compute in-house.

Does anything stand out to you on the security or the compute side to say that it's something that you would need to have or is it an area that you'd like to move into the M&A might be more of a possibility?

Generally, it would be some kind of product adjacency. So it fits within our current product set, it makes sense to enhance our security platform play, something that we think our reps can sell that we know the buyer because it's close to the buyer of some of our other security products. So having it fit with Akamai is the kind of thing that we'll be looking at.

Okay. Great. Anybody else got a question in the audience? All right. So kind of to wrap up here, talk to us a little bit about the company. I've been asking all my companies this question, sort of what's one big sort of misperception about the business? I think the obvious one for you guys is you're not a CDN necessarily anymore. That's part of the business, but that's not really what you are, even though you're often thought of that. So maybe just to level set take that one off the table, what is sort of -- when you talk to investors and you're talking to customers, what's the biggest misperception about Akamai that you'd like to kind of address and set the stage for?

Well, I think the biggest change that investors are starting to understand is that, yes, we are a cloud company and have a strong capability that's accelerating at a very fast rate. I think cloud has been sort of a show-me story for investors, and I think we're showing them. We're getting very fast growth on a meaningful number now, signing up some impressive enterprises, including, I don't know any cloud company that has all the hyperscalers as customers of their cloud business. And I think that's a good proof point that if they're buying our cloud services, there's something there, really does give better performance. And for non-cloud companies that don't have their own cloud, it is very competitively priced.

Okay. All right. Great. Well, Tom, thank you very much for being here. Appreciate everybody coming. We've got a breakout session after this. If anybody is interested, feel free to join us. Thank you very much, Tom.

Great.