This year, the event itself is all about AI. On the posters, in the demos, and on the stages, everything revolves around models, agents, and new use cases. But if you listen closely to the keynotes, you’ll notice that the real conversation goes a layer deeper—namely, to the infrastructure that has to support all that AI.
In my previous blog post, I mentioned that the real challenge of AI rarely lies with AI itself, but with the foundation beneath it: network, data, compute, and security. At the Partner Growth Summit, CEO Antonio Neri summed it up with a title that says it all: building AI starts with your network. On the main stage, Rami Rahim then delves deeper into this topic , which is why that one foundation deserves a blog post of its own.
For those who don’t know Rahim: he headed Juniper Networks for many years and, since the acquisition by HPE, has been leading the entire networking division. He is a passionate speaker who effortlessly captivates an audience, and his story has really stuck with me.
Rahim opens with an image that sums it all up. He refers to the Millennium Tower in San Francisco, a prestigious residential tower that began to sink years after its completion because its foundation could not support the load. His message is clear: If you build your AI ambitions on a shaky foundation, the whole thing will collapse sooner or later. And that foundation, he argues, is your network today.
HPE’s acquisition of Juniper lends extra weight to that message. The entire networking sector is receiving a striking amount of attention here, and it becomes clear why HPE is investing so heavily in this area. For me, it sums up the biggest shift I’ve seen this year: The network is no longer infrastructure; it’s the platform.
The network is no longer just a background layer
For years, we talked about storage, compute, and the cloud as the drivers of innovation. The network was somewhere in the background. Important, to be sure, but rarely something that excited the executive committee. Today, that logic has completely reversed.
The reason is simple. AI places extreme demands on your environment. Massive data traffic, real-time inference, and low latency require an infrastructure that can continuously scale. As soon as one of those links fails, the performance of your entire AI application drops. Or as it was put on stage: AI innovation can only move as fast as the network allows. In the workplace, that is simply the reality.
Two Trends at Once: AI on the Network and AI in the Network
What I find compelling is that the story doesn’t stop at “networking is important.” It goes a step further. We are, in fact, in the midst of a dual evolution.
On the one hand, the network must be able to handle the AI workloads on its own. That’s what “networks for AI” is all about. On the other hand, AI is increasingly taking over the management of that network. That’s “AI for networks.” Rahim puts it nicely: The future of networking will not only support AI—it will run on AI.
You can already see concrete examples of this today. Self-managing networks, AI that detects problems before a user even notices them, and automatic optimization. These technologies are already in full production today.
HPE is bringing this to life with new hardware and software built specifically for this wave. Behind the scenes, management platforms that used to operate independently—such as Aruba Central, Mist, and OpsRamp—are increasingly converging. The message is clear: the network is now viewed as a single, cohesive platform, rather than a collection of disparate devices.
Self-driving networks are finally becoming a reality
In recent years, I’ve seen “AI in networking” come up more often. Usually, it was limited to dashboards and alerts. What we’re seeing now is fundamentally different. Systems detect a problem, determine the cause, and resolve it without human intervention.
Someone put it very aptly during a session: If humans still have to fix the problem, where exactly is the self-driving part? That, to me, is the crux of the matter. This goes beyond tools that support the administrator. It’s about a new operational reality in which the network largely runs itself.
Security is moving to the inner part of the network
A second trend that stands out to me: security and networking are converging. This makes sense, because every attack occurs over the network, and every action leaves traces on the network. Security should therefore be woven into the network itself.
In practice, this means zero trust all the way down to the network layer, AI that detects anomalous behavior, and policies that automatically trigger a response. The network thus becomes both your first line of defense and your detection system.
For security teams, this is a huge relief. They’ve long been grappling with a growing attack surface and a shortage of personnel to monitor everything. When detection and response take place at the network layer itself, you gain valuable time when it really matters. The question then shifts from “will we see the attack in time” to “how quickly does the network act autonomously.”
What this means for your organization—and for us
The impact extends beyond technology alone. Three things stand out to me.
First, the network is back on the executive agenda. The focus is shifting to a higher level: Will your AI applications continue to perform when usage peaks? How will that affect the user experience? And what risks are involved? These are decisions that come with a cost and have an impact on the business, which is why they belong at the executive level—not just with IT.
Second, this requires a different way of working in operations. The traditional approach of monitoring, creating a ticket, and then resolving the issue falls short when it comes to the speed and complexity of an AI environment. Autonomous management takes over the routine tasks, freeing up your IT team’s time for work that truly drives your business forward.
Third, the role of a partner is changing. For us at Xylos, networking is an integral part of every project involving AI, the cloud, and security—rather than a separate chapter that you just take care of afterward. Anyone who continues to view these layers in isolation is once again building on shaky ground. That is precisely the fallacy Rahim sought to expose with his tower.
What I’m taking with me so far
The event is still in full swing, but the common thread running through these first few days is already clear to me: AI is only as strong as the foundation on which you build it. That foundation consists of your data and your integrations, but above all, your network.
We’ve been saying for years that data is the new gold. Maybe that’s still true. But if you ask me today what will really make the difference, it’s not who has the most data. It’s who has the best control over their network. Because without a high-performance, intelligent, and secure network, no AI ambition will ever get off the ground. Otherwise, Rahim’s tower will simply start to wobble.
By the way, there’s a second keynote on the program that really interests me, and I’ll come back to that in my next blog post. For now, I’m curious to know how you’re experiencing the network today. Is it already a topic of discussion at the executive level with your clients, or is it still confined to the technical realm?
About the author
Frank Dierckx is a Partner Alliance Manager at Xylos and tracks developments in infrastructure, partner ecosystems, and emerging technologies. His expertise helps clients make technology choices that are technically sound and economically sound.
