Zayo is working with NVIDIA to expand the high-capacity network infrastructure needed to connect AI factories, GPU clusters, neoclouds and enterprise artificial intelligence deployments across North America.
The digital infrastructure provider is building more than 8,000 miles of new long-haul fiber across rapidly growing AI corridors while significantly increasing capacity across its existing network.
The expansion is intended to address a growing imbalance between demand for AI computing resources and the network capacity available to connect increasingly distributed infrastructure.
Zayo said AI development is creating demand for connectivity at a scale the telecommunications industry has not previously experienced. As data centers and GPU clusters expand beyond established technology hubs, high-capacity long-haul fiber is becoming an increasingly important part of the AI supply chain.
The company’s buildout will establish six new long-haul routes across emerging AI corridors. Zayo will also increase capacity on existing infrastructure across 10 high-demand markets.
Zayo said it has analyzed where AI-related network demand is likely to emerge and is investing in infrastructure before that demand fully develops.
Rather than concentrating only on established routes, the company is building connections in markets where new AI computing capacity, data centers and power resources are being developed.
The infrastructure will support AI factories, which combine accelerated computing, storage and networking systems to train, deploy and operate AI models.
Long-haul fiber allows workloads and data to move between distributed computing environments, including training clusters, inference locations, cloud platforms and network interconnection points.
Zayo is combining its experience building and operating large-scale communications networks with NVIDIA accelerated computing and AI infrastructure expertise.
The companies believe that connecting distributed computing resources will become as important to the continued development of AI as expanding the underlying availability of compute.
Zayo’s network investments are intended to support a broader range of AI infrastructure providers, including hyperscalers, neoclouds, frontier model developers and enterprises.
Neocloud companies provide access to specialized GPU infrastructure and other computing resources. Their ability to bring capacity online and make it available to customers can depend on whether sufficient network connectivity exists in the markets where the infrastructure is deployed.
Zayo said access to high-capacity wide-area networking is also becoming essential for enterprise AI projects in healthcare, financial services, manufacturing and other industries.
Without sufficient network infrastructure, organizations may struggle to move large datasets, distribute workloads or connect computing resources located across different facilities and regions.
The latest initiative builds on Zayo’s broader AI-focused infrastructure expansion. Over the past 18 months, the company has launched new construction and network-overbuild projects spanning more than 15,000 route miles across North America.
Zayo also expanded its metro network through its acquisition of Crown Castle’s Fiber Solutions business.
That transaction added approximately 90,000 metro route miles and 40,000 on-net enterprise locations to Zayo’s infrastructure.
The additional metro density is expected to support AI inference workloads, which increasingly need to operate closer to users, businesses and devices rather than only inside centralized computing facilities.
Zayo’s long-haul network can connect large training environments and regional data centers, while its metro infrastructure provides connectivity between those systems and enterprise or inference locations.
The company also recently introduced its AI Infrastructure Blueprint, a framework for connecting AI training, inference and interconnection environments.
The blueprint is designed to help organizations plan the networking architecture required to support AI workloads across multiple infrastructure layers and geographic locations.
Zayo believes coordinated investment across compute, storage and networking will be needed for the AI ecosystem to continue scaling.
The company said its expansion will help remove network capacity as a potential bottleneck while allowing more providers and enterprises to access the connectivity required for large-scale AI deployment.
KEY QUOTES:
“AI is fundamentally reshaping where and how network infrastructure needs to be built across the U.S. Zayo has invested significantly in modelling where AI-driven demand will emerge and is actively expanding infrastructure ahead of that demand.”
“As AI infrastructure becomes more distributed, access to high-capacity connectivity in the right markets is becoming critical to how quickly providers, like neoclouds, can bring new GPU capacity online and support customer demand. Building new AI corridors where infrastructure is actually scaling helps remove a major bottleneck for the broader AI ecosystem.”
Steve Smith, CEO of Zayo
“AI is moving faster than ever, and the network is quickly becoming just as critical to that progress as compute itself. Zayo’s work with NVIDIA is helping us get ahead of that curve, pairing Zayo’s expertise in large-scale network infrastructure with NVIDIA’s AI leadership to build the connectivity backbone the entire ecosystem needs to keep innovating.”
Vladimir Troy, Vice President of Engineering for AI Infrastructure at NVIDIA
“The next constraint for AI is not just compute. It is the ability to connect massive, distributed AI infrastructure at scale. As GPU clusters, AI factories and hyperscaler deployments expand beyond the traditional data center hubs, long-haul fiber becomes a critical layer of the AI supply chain.”
“Zayo’s work with NVIDIA directly addresses one of the most important infrastructure gaps in the market: building new high-capacity corridors where AI demand is emerging, not just adding capacity where networks already exist.”
Dylan Patel, CEO of SemiAnalysis
