Everyone, I'm Fatima Boolani. I jointly head up the software research team here at Citi, and I'm very excited to host my next Fireside chat session with Dr. Tom Leighton, Chief Executive Officer and founder of Akamai. Thank you so much for being here.
Oh, thank you. Nice to be here.
I appreciate it. Well, we've got a lot to talk about, and where I want to start the conversation is Akamai's strategic evolution. The business has undergone a substantial change and transformation, certainly in the last three years, but I'd even narrow the scope and say in the last year, having essentially evolved from a predominantly content delivery services business to majority of compute and security business. In your view, as we think about the evolution and some of the milestones you've hit in the last 12- 18 months, what comes out most sharply in your mind as things that have been most salient in that evolution?
I think there's been a big advance with our cloud capabilities. We bought Linode several years ago now. Huge investment to make that be of a caliber that big enterprises can use for big mission-critical applications. Now we're to the point where we can sign up these very large cloud customers and support their AI needs, end-to-end, training all the way through inference, and get their compute applications close to users so they can take advantage of low latency and also high throughput for video kinds of situations. Maybe you're in robotics and the robot is seeing a lot of things around it, or it's a car or something, and you need to process those videos at scale really quickly. It's really been the last 12 to 18 months where we've gotten to that level.
We can go out there and compete head-to-head with the hyperscalers, the Neoclouds, whoever it might be, and succeed.
Dr. Tom, I wanted to take a step back and actually ask you maybe a little bit more of a bigger picture question. As a founder of the company, you've been at the helm and seen this business see massive evolutionary leaps, right? You were literally in the front seat guiding and architecting the role you would play in democratizing the Internet, right? If we go all the way back into the late 1990s. Seeing that transition and the explosion of the value that you created in the content delivery, then you pivoted to providing security around all this traffic that was being created. Now we're in the AI era, where compute is really shining. Can you maybe juxtapose or compare or contrast for us with the benefit of having watched and witnessed these paradigm shifts in the past?
How would you compare where we are from the AI native and AI adoption era relative to these past other cycles or computing evolutions that we've seen? What's different? What's more dramatic? Maybe what's the same? Maybe history is rhyming again. I would love to get your perspective.
Yeah, it's a great question. I think there are a lot of parallels. What we're seeing today and what we saw in the late 1990s as the Internet exploded onto the scene. A fabulous new technology is going to change everything. A lot of great use cases, also some bad use cases.
solution for that.
We are working on it, yeah. I think a lot of bubble kind of excitement in a way, but also a lot of reality. This is going to be here and change our lives. So that is all very similar. In terms of Akamai and what we can do, there is similarities there. Back in the start when the Internet came on the scene with the web, with a website, it was hosted in one spot, one data center, maybe East and West Coast.
Well, you see that today with some of the first AI use cases, all one big data center. That does not scale well. It did not work in the web. You had the worldwide wait, and of course, that is where Akamai helped by being distributed and getting the content closer to users and staged there so you get faster delivery and scalability. Same thing is happening with AI.
To scale these applications so you can handle and process lots of videos or create a lot of individual videos for users that are personalized or to have conversations in real time, you need to be distributed. We are just at the start with that, and we are using the same kinds of capabilities we developed back then now for AI. Initially, costs were very high back then, and then a lot of work was done to decrease cost. I think you are going to see that in AI. Even the notion of caching back then, which made it a lot more effective, we are at the early stages now with things like semantic caching. So, two people ask, really, they are asking the same question but in a different way. You do not want to go back to the expensive model to answer it the second time.
You want to realize, "Hey, I have answered that question, and here is what it is." To be able to do that, we have got some partners now starting to do that with video, where instead of generating the video from scratch, which is expensive, you have already got a frame for it, and you tweak it a little bit. You change how the lips move as you change what they are saying, the avatar is saying. So there is just, I think, a lot of parallels there. What we do is it is amazing how similar it is. Same with security. Again, back then you would have your WAF in your data center, which at the time was fine, but then you got these bigger attacks, the WAF is overwhelmed, and you could not do it anymore. Of course, we built the cloud WAF, so it is fully distributed.
Now you can absorb all that attack traffic because you are distributed. In just the last year, the size of the attacks has gone up a factor of 10.
The bad guys have AI, they can go take over a lot more devices to launch these attacks. It is striking, the similarities we are seeing today.
I know we are going to talk a lot about the compute business, also known as the CIS business. Before we focus on that, while delivery is only 1/3 of your business, it is also still 1/3 of your business. I know you have worked very hard to diversify from the content delivery, building adjacent product capabilities and security, and on the connected cloud vision. As you talked about the explosion of the Internet, the Internet is exploding again by way of AI traffic and traffic growth. The surface area of the Internet is just expanding and metastasizing because of AI. You have bots, you have AI bots, you have machine-generated traffic.
Can we unpack a little bit of that in terms of, because you see so much of the Internet traffic essentially flowing through your pipes, how should investors get a handle on what the complexion of Internet traffic looks like today than what it did even, let us say, three years ago? ChatGPT came out back half of 2023, right? That composition and complexion of Internet traffic today and how it differs or contrasts traffic patterns from three years ago even.
Yeah, good question. I think there's probably a lot of misconceptions out there. Already for probably most of our customers, most of the entities that were coming to their sites and apps weren't human. They were bots of various kinds. Of course now, the variety of those bots or agents that are coming to their site is proliferating. This does present challenges for our customers in terms of what they want to do in response. The good news is we have the market-leading solution for Bot & Agent Control, so when our customer decides how they want to treat any particular kind of agent, we can make that happen for them. Of course, with the proliferation of agents, they aren't all secure, and you've got a big security challenge there.
I was talking to a banking customer yesterday, and they're going to block agents, user agents, just because they don't have the level of security, and the bank's on the hook if user data gets out through them. So there's a lot more entities out there, but it was already mostly automated interactions. Now, in terms of traffic and the revenue for our delivery business, that's based largely on the number of bytes we deliver. That's not yet changing because of AI. When the agent is transmitting text back and forth, that is tiny.
Bits, yeah.
The bytes come from video watching, so if everybody watches more video online or watches in a higher quality, that can make a difference. For software downloads, gaming releases or all the stuff you put on your devices. AI's not really changing that yet. Now, someday it might. If our agent manifests itself as a human and we're talking to it all the time, it's like our personal shopper, we become buds with our AI personal shopper, well, now video's going. Or if really all the devices out there are recording what's happening and video's being processed, okay, that makes more bytes. I was in China recently and saw some cool AI glasses that are recording everything that's going on that the person sees and sending it into the cloud real-time, and then information comes back and is displayed on the glasses in real time.
In this case, they were using the glasses to translate my talk. So I've got English up on my PowerPoint, and they're seeing Chinese on their glasses. If you start having that at scale, that can generate more traffic. But today, those things really haven't started happening yet at scale. But you're right, there's a zillion agents out there, and they're only increased, and that's a big security challenge. Helps with our security revenue, and of course, helps with our compute revenue because that kind of stuff runs on our cloud. And that's where we're seeing the big growth.
Is it fair to characterize that the way you win AI dollars and AI budgets, so to anoint you an AI winner, let's say, would it be as a manifestation of your security business outperforming expectations? That's actually where you would be capturing a lot of this value from AI because it doesn't seem like geographically it would land on the delivery side.
Yeah. I don't think it's going to change our delivery business anytime soon. It's helping our security business, which obviously is important. But really, it's our CIS, our cloud business. We're talking next year that revenue overall for the company going to get into the low teens, which is a big acceleration. That's being driven by the cloud business, the compute business.
Then just to kind of round out on the delivery side, another sort of monumental change in the delivery market is it's a much more rational, competitive or competitor and peer landscape, right? You yourselves have been in a position to consolidate some of these assets from these companies that are no longer around, right? So can you give us a state of the union on the classic delivery realm, how much of that has influenced the stabilization you've seen in the business, right? Your ability to capture more traffic growth in the classic sense with the live events and the software downloads. And then relatedly, the influence that's had on pricing, because I think there is generally a view that this business had to fight or circumnavigate commoditization effects and price deflation, right?
I am wondering if you can just characterize the health of the core delivery business from the price side of the equation, and we have discussed the volume, but the volume side of the equation, especially in light of the fact that the competitor and peer landscape has changed so dramatically.
Yeah. Delivery is a good business, really important for our customers. We are the leader at that by far. Pricing is still very competitive, and we walk away from deals where we do not like the price. Also spiky stuff that we do not like, where if we are not getting paid enough, we will not do it. We do have competitors that will go out there at any price to win business still, even though at least several of them went broke in the last few years doing that.
There are still others that do that. We do not operate the delivery business to go get all the traffic or to drive revenue growth. We operate it strategically and to drive cash flow. In some cases, we will say, "You got to pay us more or we are not going to do it." In some cases, we will not take it. For most of the major players out there, we will do the majority of their delivery, but we really do care about the price there.
I want to shift gears into the security business. I would say Guardicore on the micro-segmentation side and API Security have just been all-stars in that portfolio. Wondering if you can help bifurcate kind of the health of the segment by way of some of these newer kids on the block, so to speak, and some of your more mature growth businesses where you have a tremendous amount of market share on the DDoS and WAF side. If you can kind of walk us through some of the dynamics, because we talked earlier about, hey, security is going to be the landing zone for you to win AI wallet share, right, for the most part. Are you starting to see maybe a little bit of a renaissance on some of the older products in the security portfolio? What has been coming up in your conversations?
Yeah. The majority of the security revenue is the more mature products where we've got huge customer penetration, WAF and DDoS, and we are seeing some tailwinds there. As I mentioned, in the post-Mythos world, the bot networks are 10x as big, and that's helped our DDoS business. With WAF, a lot of the world's major banks, emergency programs to make sure all their apps are behind Akamai's WAF, so they'll be protected from the zero-day. Bot & Agent Control getting tailwinds from the fact there's all these agents out there. No question the security business as a whole is benefiting from these trends. That said, I think the big excitement from AI in terms of driving revenue growth at Akamai is on the cloud side.
Like we talked next year, we're going to have dramatically accelerated revenue growth going forward, and it'll be faster than the security business even is growing. Security is great where it is today. Cloud is a much bigger market, and we have a compelling value proposition, and we're seeing incredible growth there, enough to take the whole company into a different zip code with growth.
Good segue into talking about CIS and compute. Initially, there were aspirations to compete with the hyperscalers, but now the opportunity has become more multifaceted. Can you help walk us through sort of the vision for the compute hyperscaler, which was kind of the first step or the first kind of foray in scaling the cloud business by way of Linode and kind of your rationale to acquire Linode, your aspirations to be a specialized edge cloud, and then also your aspirations to be a quasi-Neocloud as it relates to being a destination for model training and distillation. I'm wondering if you can sort of go a layer deeper on where you think and feel and believe your most killer advantage is going to be between those opportunity sets inside CIS and-
Yeah. Great. I'd say the first two, very relevant. Competing with the Neoclouds, not so much. Most of the Neocloud revenue is training the big foundation models, gigawatt data centers. That's not us, not where we're going. We are doing the end-to-end AI for our big enterprise customers, training all the way through inference. Today, a big data center for us is tens of megawatts. That's fine for training enterprise-grade models. Of course, we already have the Edge platform where we now can deploy containers, function as a service, so you get really close to end users, all on one platform connected by one of the world's largest backbones. In fact, all the hyperscalers are using our compute service today. Obviously, we compete with AWS, Azure, and Google.
Their parent companies are using, for applications where latency really matters, using our cloud to do that, and two of the three are very large Akamai customers. We compete with the hyperscalers. We have for a long time. Now we compete also on cloud, where we didn't before. We don't compete so much with the Neoclouds. I think one of the big deals we did, they were in there competing. Generally, we're not head-to-head with them like we are with the hyperscalers.
I think what's captured everyone's excitement for the business and the opportunity is just the edge inferencing use cases. Those are absolutely lighting up. I wanted to ask you at a very technical level, and feel free to go in the technical nuts and bolts, professor. The edge latency and the use cases you've built over a $2.8 billion book of business in signing some very marquee transactions that absolutely validate what you're doing. Can you help, in plain terms, express why you've been winning these very watershed deals for you and why investors should be paying attention to the use cases here?
Well, the Edge platform enables us to get the compute logic closer to the user or the data or the bot or the robot or the sensor. That's important for applications where the latency matters. Driving a car, a robot that's doing things in a factory, you're talking to the agent, you're getting a personalized video from a commerce site showing you're wearing some clothes, you're talking to your personal shopper. Before, AI wasn't to the point where the AI could generate something like that in real-time. Now it is. Now the last barrier is, okay, if the AI is running across the company or across the world, it's still going to be too slow just to be able to have that conversation because of the latency.
If you've got a sensor kind of a robot kind of application and you got to process a lot of videos, you don't have the bandwidth in the central location to do that. It's just like you can't broadcast the World Cup game from a data center. You don't have the bandwidth out, and it's the same problem in reverse. If you're doing video applications for commerce sites that are personalized at scale. You're not watching the World Cup, you're watching yourself wearing the sweater. Can't do that at scale if it's all coming from the central data center. You just can't get it out. Same problem we solved 20+ years ago with delivery. You need to be distributed.
That's what we do, and I think now is really the time where that's just starting to see, and a big runway ahead. We do it end to end. You don't have to do your training somewhere else and then use us. It all works on the same platform connected by one of the world's top 10 backbones.
Dr. Tom, what about the data center architecture and your point of presence footprint is extremely advantageous in this environment? A lot of peers talk about maybe having a different network topology, some kind of differences in opinion on, again, network architecture. You've got the 4,000 pops. You have been very assertive on the CapEx and been very front-footed about that to support these growth opportunities. Can you help investors understand what about your distributed footprint is very advantageous and where you are actually rolling out racks of GPUs to be able to immediately support this demand in your compute and CIS pipeline?
Yeah. There's a bunch of reasons, but we probably deal with all the world's data center companies, probably more than anybody. We're in 700 cities and, as you said, 4,000 pops. We have good relationships there. We have good relationships with all the hardware vendors. We've been buying from them for a long time. It's tight market for both, but we're in a great position to get what we need in both cases in a reasonable timeframe. Then you've got the platform where we have large, for us large, small compared to the hyperclouds, but plenty big for us in hundreds of cities around the world. Then smaller locations in hundreds more in a platform connected by one of the world's largest backbones, so we can communicate very efficiently and quickly.
It allows us to have a lot lower egress cost than the hyperscalers charge. For a lot of applications, we're head-to-head with the hyperscalers competing for a deal. We'll be less expensive because of that. Also on top of this, we've got the world's biggest and best delivery network, and a lot of the applications ultimately need delivery and security. That's going to be super important for these agents and AI that you actually have really good security. The hyperscalers, most of them use us for security. Even though we compete with them, they do have security offerings in their clouds, but they'll use us for ours because they're stronger.
I wanted to spend a little bit of time on you are spending a lot of effort, energy, and executive focus on scaling up what is structurally a very attractive franchise in your compute business, right? It is going to be the power source for the acceleration that you are anticipating in total revenue growth next year. But so far you have been in the mode of winning the beachheads with the very large Frontier Lab customer that you referenced earlier in the year as a big win, the $1.8 billion deal. Subsequent to that, there has been a couple of hundred million dollar deals, excuse me, that you have bagged. These are very consequential wins. But at the same time, they have come with increased CapEx intensity, right? How can you help investors get comfortable with the medium and long-term unit economics of this business?
Because you are in investment mode, right? We are seeing gross profit and gross margin compression as you tackle these opportunities. We are seeing operating margin compression as you chase these and execute on these opportunities. But how should investors get comfortable around deals from here against the CapEx footprint that you have and that you will continue to build to support this demand are going to come at better unit economics for Akamai at large?
Yeah, the economics on these deals are pretty good. We have talked about the very biggest ones, which would have, I guess, the least good economics, but still very good. Gross margins, mid-60s to mid-70s. Operating margins, low to mid-20s to low 30s. Very profitable deals for us. In terms of the CapEx investment, we have talked about a dollar of CapEx generating $0.50-$1 a year in revenue. The biggest deals, down at the lower end. Other deals up at the high end or beyond. These particular deals are four to seven years. The biggest deal was a seven-year commitment. And it is not that we are upgrading the hardware during those seven years, it is those servers for seven years. These are great deals for us financially.
Now, where you see it and you could say, "Ah, that is going to hurt your cash flow up front." Yeah, you put the cash in up front, and then six to nine months later, well, now you are generating a ton of cash going forward. And as you do a lot of these deals to jumpstart the business, well, you notice it with your, "Hey, our cash flow is much worse." Yeah, but the generation of cash going forward is huge, really good. And yeah, when you do these deals up front, it hits your margins because you are locking down and paying for the data center space, take another six months to get the revenue for it. And yes, we have said margins.
We are taking down about 5 points to operate in the mid-20s. But we are going to become a growth company now, okay? And we were not that before. Growth not going to be in the mid-single digits anymore. We're talking about much, much bigger growth for the company going forward. I think very attractive proposition for investors. We start with some big deals, and we're going to try to sign more big deals like that and then take that through our large enterprise customer base. A typical customer today will spend 10x doing cloud than what they would spend in security or delivery with us, and that's a great value proposition.
And then, you have been very disciplined about managing the cost structure in the business, very rigorous. Is there an opportunity to continue to drive efficiencies in other parts of the business at large to essentially mitigate some of the dilution impacts as you pursue growth and accelerate growth by way of compute?
We're always looking to be more efficient. AI is actually a little helpful there. There's positions we aren't backfilling or not hiring into because we are going to be gaining more and more efficiencies going forward with AI. Our software base, we're always working on to make it be more efficient, so that we get more bytes delivered or more computations done per kilowatt hour or square foot of colo space. That's always an ongoing effort.
One of the other elements that's unfurled since the last earnings call is, you're really getting good at deploying the CapEx and building more capacity for, let's just call them bluebird inbound demand. Correct me if that characterization is not quite precise. When you think about the pipeline for the compute business and the pipeline for the CIS business, we've clearly seen you bring down the whale-sized deals, AKA the $1.8 billion, but we've also seen you do the $250 million deal that you did in 4Q of last year, and then you just did the $600 million. So it's quite a wide range and a wide spectrum. What does that normal distribution look like for that 66% of deals kind of in the middle? What's that sweet spot and zone of deal size?
Do you believe that the CapEx that has been deployed thus far, and that is on target to be deployed, can support without incremental push better revenue leverage, let's say, on that deployed CapEx?
Yeah, good question. Before the big deals, it was all small deals coming out of the Linode business that became our cloud business. When the billion-dollar whales jump into the pool, they take up a lot of it.
They drink all the water.
Well, yeah. You notice them. They become a big part of it. Now we are very quickly transitioning to where a large fraction of the revenue is going to be large customer deals. I think you will see that for the next couple of years. We are signing up the full spectrum as we go. It is just when you have very large ones, if you measure by revenue, they are going to be a big part of it. I think over the next couple of years, it will be these large tranche deals that grab the headlines. Then there is a part that is going to be, I think, growing and become important in the long term, which is not reserving GPUs of a certain type in a certain city.
It is a model as a service, which we are beginning to do. The customer does not even specify what the hardware is. We take care of that. We are developing the capability to do these things in a serverless way. They are not even saying, "I want 10 models in this city." It just spins up on demand. I think that is where the future goes, and it is a lot more customers, not all obviously at the $1 billion a year level or even $100 million a year. Probably more in the tens of millions a year that are signed and brought onto the platform. For the next year or two, the spectacular growth that I think we are looking forward to will be large customer deals that you notice.
Dr. Tom, just in terms of CapEx utilization, how do we get comfortable that you are not going to be on this CapEx treadmill, so to speak, for the next three years? Is there a distinction you can draw between latent CPU capacity to power these edge AI and inferencing use cases? Is that something you believe maybe is not well understood in the investor community? Because maybe the sense is, hey, you need the Ferrari GPUs for every AI and edge use case? Is that what you are seeing in the trenches with-
Yeah. We do not even buy the Ferraris. The Neoclouds buy the Ferraris, and they need them to train the next amazing Frontier model. That is not our business. We are buying at least a stage 1 down GPUs that are really good at what our customer base wants to be.
The Toyota or the Lexus?
Yeah, maybe some Toyotas and Lexus and a bunch of CPUs too. In fact, before these big deals, today the majority of inference in AI on our platform is done on CPU.
There's the next generation CPUs coming out, and AI is going to get a lot more efficient. I think a good portion of it is going to be done on CPU. Now, we'll have CapEx to drive the CIS business. It's that kind of a business. It's not like security, where it's the world's best developers developing the latest product and not much CapEx. This is not so much that as the CapEx for CIS. We will have that, but you will see, I think, very strong growth on the top and bottom lines.
It's not like margins keep deteriorating. I think margins, we've said as best, we haven't given guidance for next year, but ballpark where we are today, but big increase in revenue. As you get a big increase in revenue growth and your margins are pretty consistent, y ou see that now on the bottom line. Good increases in your bottom-line growth, which is pretty exciting.
That brings me to capital allocation. You have been a voracious buyer of your own stock, but we have put a pin in the share buyback program. How is the philosophy around capital allocation going to change and give us sort of the current state of where you are, what you're focused on.
Yeah. We said we paused for this year, for now. It doesn't mean we wouldn't do something, but we've paused for now because we already bought back a lot more than we ever have in one year this year. We bought back all the dilution we incurred with equity programs for our employees and then some. It seemed like, hey, we don't need to do more than that this year, especially when we've got these really compelling opportunities in terms of the CapEx investments.
Last question I have for you. What's one thing that with a magic wand you could wish away in terms of educating or disabusing the investor community on whether they're underappreciating something or something that you believe is very severely misunderstood about the Akamai story?
I think we're going through an interesting transition where we're going to have some pretty exciting growth. We've got a great security business doing very well. Delivery. Okay, not exciting obviously in terms of the growth, but a very good business. Now we've got CIS is exploding, and you're going to see some real excitement there.
Great. Well, thank you so much, Dr. Tom. This was a fantastic conversation. I appreciate it.
Very good. Thank you.