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Speaking at Deutsche Telekom’s AI Investor Day, Telekom Deutschland’s chief executive officer Rodrigo Diehl said that entrepreneurs in Silicon Valley had told the German telco that network performance was already limiting the deployment of robots and physical AI

In sum – what to know

AI moves to networks – AI workloads will increasingly require intelligence closer to devices, while networks evolve beyond their traditional transport role.

Physical AI raises demands – Robots and other AI-enabled devices will require better latency, jitter, and quality of service from public networks.

Autonomous networks emerge – Deutsche Telekom is using AI and customer-experience data to optimize networks, improve efficiency, and create monetization opportunities.

German carrier Deutsche Telekom expects artificial intelligence to fundamentally change the role of telecom networks as intelligence moves beyond data centers and closer to devices, while new applications increase demands on network quality and autonomy.

Speaking at Deutsche Telekom’s AI Investor Day, Telekom Deutschland’s chief executive officer Rodrigo Diehl said four developments will drive the transformation: the need to move AI intelligence closer to users and devices, growing requirements for local trust and sovereignty, the arrival of 6G, and the increasing importance of network orchestration.

“Server farms across the ocean will not be fast enough for a lot of AI use cases and workloads that are emerging,” Diehl said. “And that means some of that intelligence will need to move closer to the device, closer to the end user, closer to the edge.”

He also argued that a world dominated by a few large clouds in a limited number of locations will not be sufficient as the global environment becomes more unstable and unpredictable.

6G will further change the role of networks, he said, because future networks will not simply transport data. “6G is also going to be about sensing that information, interpreting that information, acting upon that information,” Diehl said. “And that is a fundamental shift versus what we have seen in the last couple of years where the network was mainly a transport layer.”

Network orchestration will also become increasingly important as operators manage multiple access technologies and seek to deliver services seamlessly across them.

During the presentation, Diehl identified several emerging opportunities, including what he described as a post-smartphone world in which AI agents understand context, retain memory, and act on behalf of users. “I think the days of using our fingers to talk to computers is over,” he said, arguing that voice will become a new interface and that new connected hardware could include earphones, glasses, and pods.

Another major opportunity is physical AI, which Diehl said will place new requirements on networks as AI-enabled machines operate outside controlled environments such as factories and campus networks.

“For a lot of the AI use cases that are coming, to run in the real world, and with the real world I mean outside of factories or outside of campus networks, the networks of today will not be enough,” he said, citing jitter, latency, and quality of service.

Diehl said entrepreneurs in Silicon Valley had told Deutsche Telekom that network performance was already limiting the deployment of robots and physical AI.

This creates an opportunity for operators to differentiate through network quality, Diehl said. He also described a future “network of networks” that is seamless, always on, and built around security and trust.

Such networks could support intent-based services, with network intelligence determining what different devices and physical AI applications require and adapting service characteristics such as speed, latency, jitter, and network slices accordingly.

Sensing represents another potential transformation. Diehl described a future in which networks could “build a digital twin of our real world” based on information from connected devices.

He compared the current technology landscape with a human body, with most AI processing located in data centers and AI factories, some intelligence in devices and the network largely acting as a transport layer. As AI is incorporated into network infrastructure, Diehl expects the network itself to become increasingly intelligent.

Diehl concluded by pointing to three Deutsche Telekom cases demonstrating how AI and automation are already being applied to network operations, including AI supported fiber rollout, an AI capability already live in the network and Mindr, an MVP that he said is about to go live.

The longer-term objective is a “fully autonomous network operation,” Diehl said, arguing that the shift is already moving from vision toward practical implementation.