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Wesco: Why AI Data Centers Need a Structured Cabling Strategy

July 24, 2025 - Wesco Why AI Data Centers Need a Structured Cabling Strategy

July 24, 2025

Structured Cabling Strategy: Implementing Effective Data Center Cabling Solutions

By: Andrew Jimenez, Senior Director, Technical Sales, Wesco Data Center Solutions

Artificial Intelligence (AI) applications are introducing unique challenges that are driving dramatic changes in data center infrastructure. Traditional design strategies may not be sufficient to support the power and cooling demands of high-density AI data centers. Developers are looking for new sources of clean energy and more efficient ways to cool AI servers and supercomputers that support intensive AI workloads.

AI is also forcing developers to rethink network cabling infrastructure. An AI data center may have tens or even hundreds of thousands of graphics processing units (GPUs) processing massive amounts of data and performing complex calculations simultaneously. These processors require high-speed, low-latency connectivity in order to communicate and synchronize tasks effectively. As a result, fiber optic cabling has become essential at an unprecedented scale.

AI workloads may require up to ten times more fiber than traditional facilities due to their massive computational demands and data-intensive nature. To manage the sheer volume of data and ensure reliable connectivity across devices, data centers must implement a well-planned and standardized cabling infrastructure.


Structured Cabling Can Solve AI Data Center Challenges

In the NVIDIA DGX reference architecture, direct-connect fiber cabling delivers exceptional performance benefits by enabling ultra-low latency and high-bandwidth communication between GPUs, storage systems, and networking components. This is critical for AI and high-performance computing (HPC) workloads, where massive volumes of data must be transferred and processed in real time.  However, each new generation of GPU design increases the amount of fiber required to support AI workloads within a server cluster. As systems scale, managing the growing number of fiber connections becomes increasingly complex, making it more challenging to maintain and upgrade the network infrastructure effectively.

That’s why AI data centers need a structured cabling strategy. While the term “structured cabling” conjures up images of neatness, efficiency and organization, it’s actually much more than that. It’s a comprehensive system for designing and implementing a flexible and future-proof network infrastructure that enables the continuous flow of information.

AI data centers typically use a “leaf-and-spine” network architecture to reduce latency, maximize efficiency and enable scalability. However, this fully meshed topology requires extensive inter-rack cabling, which can be difficult to manage. Structured cabling provides a systematic, standardized approach for managing this complexity, ensuring reliable connections and facilitating efficient data transmission.


Benefits of Structured Cabling in AI Data Centers

Structured cabling offers a number of benefits in AI data centers. It is faster to install than direct-connect cabling because it uses a predefined, standardized approach with modular components. It is also more flexible and scalable, enabling data center operators to adapt the network to support changing speeds and future growth.

Structured cabling also makes it easier to troubleshoot problems by eliminating the complexity and confusion associated with direct-connect cabling. Faster troubleshooting minimizes downtime — a key requirement in AI data centers that require the highest levels of availability.

These benefits also add up to significant cost savings. Although the initial cost of structured cabling may be higher than direct-connect cabling, it provides long-term economic benefits by reducing the need for rip-and-replace upgrades. When upgrades are needed, they can be completed faster with a standardized cabling approach.


Structured Cabling Is Increasingly Critical

Upgrades are virtually inevitable, given how fast AI technology is changing. While many enterprise organizations commonly operate 40Gbps and 100Gbps data rates, AI and hyperscale data centers are moving from 400Gbps to 800Gbps. The 650 Group expects an explosion in 800Gbps switch shipments by 2028, and 1.6TB switches are on the near horizon.

Future-proofing the network should be a top priority for AI data centers. Structured cabling is a critical part of that effort, providing a standardized framework that will make it easier to upgrade to 800G and beyond.

July 24, 2025 - Wesco Why AI Data Centers Need a Structured Cabling Strategy 1

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