Akamai Technologies Inc Citi’s 2026 Global TMT Conference

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, CEO 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 to 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.