‘A huge amount of network traffic now comes from machines talking to other machines’: what rising data demand means for networks
The growing overlap between cloud computing and artificial intelligence is impacting how data centers operate, pushing infrastructure toward faster, more flexible, and more energy-aware systems.
As demand from 5G services, immersive applications, and connected devices continues to rise, operators face mounting pressure to handle heavier workloads without significantly increasing power use.
Energy consumption remains a continuing concern as infrastructure expands to support real-time services across sectors such as healthcare, transport, and urban infrastructure.
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Mastering Data Centers for the AI Era
Industry focus is steadily moving toward how data centers fit into broader digital environments rather than operating as standalone facilities, and AI is becoming more closely tied to how infrastructure is managed, particularly in identifying problems before they escalate into service failures.
Those pressures formed part of the Cloud Fusion: Mastering Data Centers for the AI Era panel at MWC 2026, where Professor Dimitra Simeonidou joined the discussion.
As an IEEE Fellow and director of the Smart Internet Lab at the University of Bristol, she brought a telecom perspective shaped by years of research into network resilience and distributed systems.
I wanted to know more about the topics raised, so I spoke to Professor Simeonidou about how she sees data centers evolving as cloud, AI, and telecom networks continue to merge.
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- What are your thoughts about the data center of the future, from the optics of the telecom expert that you are?
The data center of the future probably won’t sit on its own in the way we’ve been used to. It’s increasingly becoming part of a much broader digital environment where networks, edge computing and cloud platforms all work together.
Over the past twenty years, cloud computing has gradually reshaped the role of the data center, and more recently AI has started to accelerate that shift. What we’re seeing now is a much closer relationship between computing infrastructure and telecom networks.
Networks themselves are becoming far more software-driven and programmable, which means they can move data, workloads and services around distributed environments much more intelligently.
As AI applications continue to grow, data centers will also need to become more flexible. They’ll have to respond to changing demand, manage energy use more carefully and support real-time applications in areas like healthcare, mobility and smart infrastructure.
From a telecom perspective, we’re moving towards a world where networks and data centers operate as part of the same system rather than as completely separate layers of infrastructure. That’s quite a meaningful shift in how digital infrastructure is designed and managed.
- You call for automation and predictive analytics to be harnessed for next-generation data centers. What real-world examples can you provide of how things would be done differently?
Automation and predictive analytics could really change how digital infrastructure is run.
Right now, a lot of data center and network operations are still fairly reactive. Engineers usually step in once something has already gone wrong, or when performance starts to drop. AI-driven analytics will allow us to move towards a more predictive model.
By analyzing large amounts of operational data like traffic patterns, equipment performance and environmental conditions, these systems can start to identify early signs that something might fail. That gives operators the chance to step in earlier, or in some cases automatically shift workloads across the infrastructure before anyone experiences a disruption.
Energy management is another area where this could make a real difference. Predictive systems can monitor usage and environmental data in real time and adjust cooling, workload placement and power consumption as conditions change.
Over time this leads to infrastructure that is more efficient, more resilient and much better able to adapt as demand shifts.
- It’s incredible to think that the first commercial rollout of 5G happened in the same year as COVID-19 (2019). Almost seven years later and talks of 6G were already abuzz at MWC. What do you make of it and what are your thoughts on 5.5G?
In telecoms it’s quite normal for research into the next generation of technology to start long before the current one is fully rolled out.
5G is still evolving and many of the capabilities people associate with it are only now starting to appear in real-world applications. The idea of 5.5G is about extending what we already have, improving performance, enabling more advanced services and introducing more automation into the network.
At the same time, work on 6G has already started, simply because development cycles in telecoms are so long.
What’s interesting about 6G is the expectation that future networks won’t just provide connectivity. They’ll likely bring together communication, sensing and computing in a much more integrated way.
Rather than focusing only on speed, the real opportunity is to build networks that are more intelligent and adaptive, and better able to support the increasingly complex digital ecosystems we’re starting to see.
- Where do humans stand in this conversation? Increasingly communication throughput will increase between humanoids and the universe of things.
Humans will still be very much at the center of all of this. It’s true that a huge amount of network traffic now comes from machines talking to other machines. Sensors, connected devices, automated systems and digital platforms are constantly exchanging information.
In many ways what we once called the Internet of Things is expanding into something much broader and more complex.
But people are still the ones designing these systems, setting the objectives and deciding how they should operate. As AI and automation become more embedded in telecom and data center infrastructure, that human oversight becomes more important than ever.
We don’t need to build networks that run themselves, we need to create systems that are smarter and more efficient while still remaining transparent, accountable and ultimately designed around human needs.
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The growing overlap between cloud computing and artificial intelligence is impacting how data centers operate, pushing infrastructure toward faster, more flexible, and more energy-aware systems. As demand from 5G services, immersive applications, and connected devices continues to rise, operators face mounting pressure to handle heavier workloads without significantly increasing power…
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