McKinsey: AI infrastructure opportunity for telcos? AI developments in the telecom sector

new report from McKinsey & Company offers a wide range of options for telecom network operators looking to enter the market for AI services. One high-level conclusion is that strategy inertia and decision paralysis might be the most dangerous threats.  That’s largely based on telco’s failure to monetize past emerging technologies like smartphones and mobile apps, cloud networking, 5G-SA (the true 5G), etc. For example, global mobile data traffic rose 60% per year from 2010 to 2023, while the global telecom industry’s revenues rose just 1% during that same time period.

“Operators could provide the backbone for today’s AI economy to reignite growth. But success will hinge on effectively navigating complex market dynamics, uncertain demand, and rising competition….Not every path will suit every telco; some may be too risky for certain operators right now.  However, the most significant risk may come from inaction, as telcos face the possibility of missing out on their fair share of growth from this latest technological disruption.”

McKinsey predicts that global data center demand could rise as high as 298 gigawatts by 2030, from just 55 gigawatts in 2023.  Fiber connections to AI infused data centers could generate up to $50 billion globally in sales to fiber facilities based carriers.

Pathways to growth -Exploring four strategic options:

  1. Connecting new data centers with fiber
  2. Enabling high-performance cloud access with intelligent network services
  3. Turning unused space and power into revenue
  4. Building a new GPU as a Service business.

“Our research suggests that the addressable GPUaaS [GPU-as-a-service] market addressed by telcos could range from $35 billion to $70 billion by 2030 globally.”  Verizon’s AI Connect service (described below), Indosat Ooredoo Hutchinson (IOH), Singtel and Softbank in Asia have launched their own GPUaaS offerings.

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Recent AI developments in the telecom sector include:

  • The AI-RAN Alliance, which promises to allow wireless network operators to add AI to their radio access networks (RANs) and then sell AI computing capabilities to enterprises and other customers at the network edge.  Nvidia is leading this industrial initiative. Telecom operators in the alliance include T-Mobile and SoftBank, as well as Boost Mobile, Globe, Indosat Ooredoo Hutchison, Korea Telecom, LG UPlus, SK Telecom and Turkcell.
  • Verizon’s new AI Connect product, which includes Vultr’s GPU-as-a-service (GPUaaS) offering. GPU-as-a-service is a cloud computing model that allows businesses to rent access to powerful graphics processing units (GPUs) for AI and machine learning workloads without having to purchase and maintain that expensive hardware themselves. Verizon also has agreements with Google Cloud and Meta to provide network infrastructure for their AI workloads, demonstrating a focus on supporting the broader AI economy.
  • Orange views AI as a critical growth driver. They are developing “AI factories” (data centers optimized for AI workloads) and providing an “AI platform layer” called Live Intelligence to help enterprises build generative AI systems. They also offer a generative AI assistant for contact centers in partnership with Microsoft.
  • Lumen Technologies continues to build fiber connections  intended to carry AI traffic.
  • British Telecom (BT) has launched intelligent network services and is working with partners like Fortinet to integrate AI for enhanced security and network management.
  • Telus (Canada) has built its own AI platform called “Fuel iX” to boost employee productivity and generate new revenue. They are also commercializing Fuel iX and building sovereign AI infrastructure.
  • Telefónica: Their “Next Best Action AI Brain” uses an in-house Kernel platform to revolutionize customer interactions with precise, contextually relevant recommendations.
  • Bharti Airtel (India): Launched India’s first anti-spam network, an AI-powered system that processes billions of calls and messages daily to identify and block spammers.
  • e& (formerly Etisalat in UAE): Has launched the “Autonomous Store Experience (EASE),” which uses smart gates, AI-powered cameras, robotics, and smart shelves for a frictionless shopping experience.
  • SK Telecom (Korea): Unveiled a strategy to implement an “AI Infrastructure Superhighway” and is actively involved in AI-RAN (AI in Radio Access Networks) development, including their AITRAS solution.
  • Vodafone: Sees AI as a transformative force, with initiatives in network optimization, customer experience (e.g., their TOBi chatbot handling over 45 million interactions per month), and even supporting neurodiverse staff.
  • Deutsche Telekom: Deploys AI across various facets of its operations

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 A recent report from DCD indicates that new AI models that can reason may require massive, expensive data centers, and such data centers may be out of reach for even the largest telecom operators. Across optical data center interconnects, data centers are already communicating with each other for multi-cluster training runs.  “What we see is that, in the largest data centers in the world, there’s actually a data center and another data center and another data center,” he says. “Then the interesting discussion becomes – do I need 100 meters? Do I need 500 meters? Do I need a kilometer interconnect between data centers?”

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References:

https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/ai-infrastructure-a-new-growth-avenue-for-telco-operators

https://www.lightreading.com/ai-machine-learning/inaction-on-ai-is-the-most-significant-risk-to-telcos-report

https://www.datacenterdynamics.com/en/analysis/nvidias-networking-vision-for-training-and-inference/

https://opentools.ai/news/inaction-on-ai-a-critical-misstep-for-telecos-says-mckinsey

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