Silicon: Where should operators place their bets?

Silicon: Where should operators place their bets?

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The telecom industry is going through a period of material change in respect to the silicon it utilises. This report examines the key dynamics and considerations in the locations where processing demand is at its highest: the RAN and AI factories.

Description

Format: PDF file
Pages: 62
Author: George Glanville
Publication date: January 2026

Silicon has risen up the agenda for operators

The digital economy is going through significant change in relation to the silicon it is leveraging; telecom is no exception. There have been several internal and external changes that have driven silicon considerations up the agenda for telcos.

Our insight covers the following key points:

  • Introduction
  • Silicon implications for hosting enterprise AI workloads
    • AI is transforming the silicon landscape, driven by Nvidia GPUs
    • There are significant challenges in hosting accelerated compute
    • AI ASICs will disrupt this landscape in the medium-term
    • Operational, not technological, sovereignty is a key consideration
    • Recommendations for operators hosting enterprise AI workloads
  • Silicon implications for embedding AI in the network
    • The drive for network autonomy will not materially change silicon in the telco network
    • The same is true for greater integration of AI in the RAN for internal usage
    • Disaggregation at the RAN has not materially altered the underlying silicon landscape
    • Recommendations for operators embedding AI in the network
  • Silicon taxonomy

Technologies and industry terms referenced include:
5G, 6G, AI ASIC, AI factory, AI-RAN, AI-RAN Alliance, alibaba, AMD, ASIC, ASML, AWS, Bell Canada, broadcom, Cerebras, China Mobile, China Telecom, China Unicom, chips, Coreweave, CPU, DPU, Enterprise AI, Ericsson, Fabrication, fine-tuning, FPGA, Google Cloud, GPU, GPUaaS, Groq, HBM, Huawei, Inferencing, Intel, LLM, LPU, Marvell, Memory, Meta, Microsoft Azure, Neocloud, Nokia, NPU, nvidia, Orange, Processor, qualcomm, Samsung, Semiconductor, silicon, SK Telecom, Sovereign AI, STC, TPU, training, TSMC