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Physical AI & Connectivity

NVIDIA technology appears across almost every layer of telecom physical AI, from AI-RAN computers and operator AI clouds to simulation tools and the processors inside robots. This article explains where NVIDIA sits, why operators build on it, the strategic questions its role raises, the wider ecosystem of chip, cloud and network suppliers, and five principles for operators building their own position on top.
Six of 40 telecom operators lead physical AI. Swipe through Deutsche Telekom, KT, NTT DOCOMO, SK Telecom, SoftBank and T-Mobile: where each is strongest and what to watch in 2027. Then download the free executive brief or get the full Leadership Landscape.
China's telecom operators have humanoid robots in service centres, a home robot on the market, robot platforms sold as a service and a dedicated network for an international humanoid robot competition. This article explains what Chinese operators are doing in physical AI, the five forces behind their lead, how Hong Kong's HKT applies a similar approach and what operators elsewhere can learn.
Robots carry their AI with them, and larger models are straining batteries and budgets. Telecom operators and vendors propose moving part of that intelligence onto the network edge and AI-RAN infrastructure. This article explains how robot AI offloading works, what early operator tests show, what the network must guarantee, where the AI should run and the conditions that will decide whether it becomes a business.
TeckNexus reviewed public physical AI evidence at 40 telecom operators. Most are entering the market as connectivity and compute suppliers, while about a dozen show a hands-on role in the robot application. This article defines physical AI for telecoms, maps the six roles operators are taking, explains where the margin sits and sets out the three routes operators are using to move closer to the machine.
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