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America’s AI revolution needs the right infrastructure
In this article, Ivo Ivanov, CEO of DE-CIX, argues his case for why America’s AI revolution won’t happen without the right kind of infrastructure:
Boom or bust
Artificial intelligence might well be the defining technology of our time, but its future rests on something much less tangible hiding beneath the surface: latency.
Every AI service, whether training models across distributed GPU-as-a-Service communities or running inference close to end users, depends on how fast, how securely, and how cost-effectively data can move.
Network latency is simply the delay in the speed of traffic transmission caused by the distance the data needs to travel: the lower latency is (i.e. the faster the transmission), the better the performance of everything from autonomous vehicles to the applications we carry in our pockets.
There’s always been a trend of technology applications outpacing network capabilities, but we’re feeling it more acutely now due to the sheer pace of AI growth. Depending on where you were in 2012, the average latency for the top 20 applications could be up to or more than 200 milliseconds. Today, there’s virtually no application in the top 100 that would function effectively with that kind of latency. That’s why internet exchanges (IXs) have begun to dominate the conversation.
An IX is like an airport for data. Just as an airport coordinates the safe landing and departure of dozens of airlines, allowing them to exchange passengers and cargo seamlessly, an IX brings together networks, clouds, and content platforms to seamlessly exchange traffic. The result is faster connections, lower latency, greater efficiency, and a smoother journey for every digital service that depends on it.
Deploying these IXs creates what is known as “data gravity”, a magnetic pull that draws in networks, content, and investment. Once this gravity takes hold, ecosystems begin to grow on their own, localising data and services, reducing latency, and fuelling economic growth.
I recently spoke about this at a first-of-its-kind regional AI connectivity summit, The future of AI connectivity in Kansas & beyond, hosted at the Wichita State University (WSU) in Kansas, USA. It was the perfect location - given that WSU is the planned site of a new carrier-neutral IX - and the start of a much bigger plan to roll out IXs across university campuses nationwide. Discussions at the summit reflected a growing recognition that America’s AI economy cannot depend solely on coastal hubs or isolated mega-data centres. If AI is to deliver value across all parts of the economy, from aerospace and healthcare to finance and education, it needs a distributed, resilient, and secure interconnection layer reaching deep into the heartland. What is beginning in Wichita is part of a much bigger picture: building the kind of digital infrastructure that will allow AI to flourish.
Networking changed the game, but AI is changing the rules
For all its potential, AI’s crowning achievement so far might be the wakeup call it’s given us. It has magnified every weakness in today’s networks.
Training up models requires immense compute power. Finding the data centre space for this can be a challenge, but new data transport protocols are meaning that AI processing could, in the future, be spread across multiple data centre facilities. Meanwhile, inference - and especially multi-AI agentive inference - demands ultra-low latency, as AI services interact with systems, people, and businesses in real time. But for both of these scenarios, the efficiency and speed of the network is key. If the network cannot keep pace (if data needs to travel too far), these applications become too slow to be useful. That’s why the next breakthrough in AI won’t be in bigger or better models, but in the infrastructure that connects them all. By bringing networks, clouds, and enterprises together on a neutral platform, an IX makes it possible to aggregate GPU resources across locations, create agile GPU-as-a-Service communities, and deliver real-time inference with the best performance and highest level of security.
AI changes the geography of networking too. Instead of relying only on mega-hubs in key locations, we need interconnection spokes that reach into every region where people live, work, and innovate. Otherwise, businesses in the middle of the country face the “tromboning effect”, where their data detours hundreds of miles to another city to be exchanged and processed before returning a result - adding latency, raising costs, and weakening performance. We need to make these distances shorter, reduce path complexity, and allow data to move freely and securely between every player in the network chain. That’s how AI is rewriting the rulebook; latency, underpinned by distance and geography, matters more than ever.
Building ecosystems and 'data gravity'
When we establish an IX, we’re doing more than just connecting networks; we’re forging the embers of a future-proof ecosystem. I’ve seen this happen countless times. The moment a neutral (meaning data centre and carrier neutral) exchange is in place, it becomes a magnet that draws in networks, content providers, data centres, and investors. The pull of “data gravity” transforms a market from being dependent on distant hubs into a self-sustaining digital environment. What may look like a small step - a handful of networks exchanging traffic locally - very quickly becomes an accelerant for rapid growth.
Dubai is one of the clearest examples. When we opened our first international platform there in 2012, 90% of the content used in the region was hosted outside of the Middle East, with latency above 200 milliseconds. A decade later, 90% of that content is localised within the region and latency has dropped to just three milliseconds. This was a direct result of the gravity created by the exchange, pulling more and more stakeholders into the ecosystem. For AI, that localisation isn’t just beneficial; it’s also essential. Training and inference both depend on data being closer to where it is needed. Without the gravity of an IX, content and compute remain scattered and far away, and performance suffers. With it, however, entire regions can unlock the kind of digital transformation that AI demands.
The American challenge
There was a time when connectivity infrastructure was dominated by a handful of incumbents, but that time has long since passed. Building AI-ready infrastructure isn’t something that one organisation or sector can do alone. Everywhere that has succeeded in building an AI-ready network environment has done so through partnerships - between data centre, network, and IX operators, alongside policy makers, technology providers, universities, and - of course - the business community itself. When those pieces of the puzzle are assembled together, the result is a healthy ecosystem that benefits everyone.
This collaborative model, like the one envisaged at the IX in WSU, is exactly what the US needs if it is to realise the full potential of AI. Too much of America’s digital economy still depends on coastal hubs, while the centre of the country is underserved. That means businesses in aerospace, healthcare, finance, and education - many of which are based deep in the US heartland - must rely on services delivered from other states and regions, and that isn’t sustainable when it comes to AI. To solve this, we need a distributed layer of interconnection that extends across the entire nation. Only then can we create a truly digital America where every city has access to the same secure, high-performance infrastructure required to power its AI-driven future.
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Joe Peck - 5 November 2025
