In The AI Era, The Value of Structured Cabling Is Making A Comeback

In recent years, artificial intelligence (AI) has been integrating into industries at an unprecedented pace. From large language models and computer vision to intelligent manufacturing, smart campuses, smart hospitals, and intelligent buildings, AI is no longer just a cutting-edge technology confined to laboratories. It has become a core productive force driving enterprise digital transformation.

As more AI applications move into real business scenarios, the focus of enterprises has shifted from “whether to deploy AI” to “whether existing infrastructure can support AI.”

In the building intelligence industry, attention often centers on high-profile technologies such as computing servers, GPU clusters, and AI algorithm platforms. However, a more fundamental yet equally critical issue is frequently overlooked: structured cabling and network infrastructure are emerging as the new capability boundary in the AI era.

The development of AI is not only transforming data centers but also redefining the design philosophy, network architecture, and construction standards of structured cabling systems. Looking ahead, the goal of structured cabling is no longer merely to enable network connectivity. It is to provide continuous, high-speed, stable, and low-latency data transmission capabilities for AI.

Network Transmission Capability Is Becoming the New Infrastructure in the AI Era

Traditional office networks primarily served office automation, video conferencing, and file sharing. Traffic was relatively predictable, and real-time requirements were limited.

AI applications have completely changed this landscape.

Whether it is large model training, knowledge base retrieval, intelligent video analysis, digital twin platforms, robot control, or edge vision computing, all require continuous processing of massive volumes of data. For example, a high-definition intelligent video analysis system may generate several terabytes or even tens of terabytes of data traffic every day. Large language models also involve high-frequency data exchanges during internal enterprise calls.

This means that future building networks will no longer carry only office data, but increasingly computational data flows.

At the same time, AI applications demand far lower network latency than traditional services.

In real-time applications such as facial recognition, industrial control, intelligent security, autonomous driving, and robot collaboration, even millisecond-level network delays can directly affect system response speed, analysis results, and even operational safety. Therefore, network construction in the AI era requires not only higher bandwidth but also continuous stability, low latency, and high reliability in data transmission.

For structured cabling, this means that traditional Gigabit networks are increasingly unable to meet future development needs. Structured cabling systems that support higher transmission capabilities are gradually becoming the preferred choice for more intelligent buildings, data centers, and AI application scenarios.

AI Development Is Accelerating the Popularization of Edge Computing

In the past, it was common practice to transmit all data to centralized data centers for processing.

As AI applications deepen, this model is changing.

More and more data is now processed close to where it is generated—this is the rapidly growing field of edge computing.

For instance, intelligent cameras can perform object recognition locally; industrial sensors can analyze equipment status in real time; medical devices in hospitals can complete partial AI-assisted diagnosis on-site; and video analysis, access control, and environmental monitoring in smart campuses are increasingly deployed at edge nodes.

The greatest advantage of edge computing is reducing the network pressure caused by data traveling back and forth to the data center, while improving real-time response capabilities.

At the same time, it fundamentally changes the design boundaries of structured cabling systems.

Previously, structured cabling mainly focused on data centers, weak-current equipment rooms, and office areas. Today, it needs to extend to production workshops, equipment rooms, building sites, campus roads, intelligent terminals, and many other business scenarios.

In other words, structured cabling is evolving from “connecting offices” to “connecting everything.”

This places higher demands on network reliability, power supply capability, and environmental adaptability.

PoE Power Supply Is Becoming a Key Support for AI Terminals

The rise of AI has also driven more intelligent terminals to adopt network-based power supply.

Intelligent cameras, wireless access points, IoT gateways, edge servers, access controllers, environmental sensors, and various AI terminal devices are increasingly using Power over Ethernet (PoE) technology.

Compared with traditional power supply methods, PoE enables simultaneous data communication and device powering, reduces cabling complexity, improves deployment efficiency, and simplifies later maintenance.

However, as AI terminal devices become more feature-rich, their power consumption continues to rise.

For example, high-definition cameras supporting AI recognition consume significantly more power than ordinary network cameras. Next-generation Wi-Fi 6 and Wi-Fi 7 access points also require higher power. Edge AI computing devices may even need the high-power IEEE 802.3bt PoE standard.

This means that structured cabling systems must not only meet data transmission requirements but also stably support high-power PoE.

In practical projects, higher-grade structured cabling that supports 10 Gbps transmission and delivers excellent PoE performance is becoming an important choice for intelligent buildings and smart campus projects. Depending on different building environments, appropriate sheath types such as LSZH (Low Smoke Zero Halogen) or CMR should also be selected to meet fire safety and engineering application requirements.

Data Centers Enter the AI Era, Further Elevating the Importance of Structured Cabling

AI development is also pushing data centers into a new construction phase.

Traditional data centers primarily supported business systems, databases, and office applications.

AI-era data centers must support large-scale GPU clusters, high-speed storage, model training, and massive data exchange. Their network density, cabling complexity, and cooling requirements far exceed those of traditional computer rooms.

For data centers, structured cabling is no longer simply about “connecting devices.”

High-density patching, efficient cable management, proper airflow organization, modular cabling, and future expansion capability all directly affect the operational efficiency of the entire data center.

Moreover, the development speed of AI businesses far surpasses that of traditional IT systems.

What is deployed as Gigabit access today may need upgrading to 2.5G, 5G, or even 10GBASE-T within a few years. Backbone networks are gradually evolving toward higher-speed fiber optic networks to meet continuously growing data traffic demands.

Therefore, adopting Category 6A structured cabling that supports 10 Gigabit applications from the project planning stage and reserving space for future upgrades is not merely an added cost—it is a forward-looking infrastructure investment.

Especially with the continuous popularization of Wi-Fi 6, Wi-Fi 7, and 5G private networks, structured cabling systems are becoming a critical foundation that determines a building’s digital capabilities.

In the AI Era, Building Intelligence Projects Should Re-Examine Structured Cabling

In the building intelligence industry, structured cabling has long been regarded as a “mature technology.”

However, the AI era is redefining its importance.

In the past, structured cabling mainly focused on whether it complied with standards and whether it could connect the network. In the future, greater attention must be paid to whether it can meet the continuously growing data demands of AI applications.

During project planning, owners, design institutes, and intelligent system integrators should focus on several key questions:

First, does the existing structured cabling system have 10 Gigabit or higher transmission capability to support future high-bandwidth services such as AI, big data, and high-definition video?

Second, can the network support high-power PoE to provide stable power for the growing number of AI terminal devices, rather than only meeting the basic needs of traditional cameras or wireless access points?

Third, has the structured cabling system undergone proper certification and testing? For AI services, network quality directly affects system performance. Cabling testing and certification are no longer just a completion acceptance process—they form an important foundation for ensuring stable network operation.

Fourth, does the entire network have good scalability? AI develops extremely quickly. If the network only meets current needs, it may require reconstruction within a few years. Reserving bandwidth, space, and interface resources at the design stage will significantly reduce future upgrade costs.

Finally, have data centers and weak-current equipment rooms fully considered high-density cabling, thermal management, and cable organization? As AI servers and edge computing nodes continue to increase, the importance of cabinet space, airflow organization, and cable management is becoming equal to that of the switching equipment itself.

Conclusion: In the AI Era, the Value of Structured Cabling Is Returning

For a long time, structured cabling has been viewed as the most basic and mature component of building intelligent systems, and therefore easily overlooked.

Yet the development of AI is once again proving that the upper limit of any intelligent system is ultimately constrained by the capability of the underlying infrastructure.

Artificial intelligence requires more than just network connectivity. It needs continuous, stable, high-bandwidth, low-latency, and scalable data transmission capabilities. It needs more than one-time engineering construction—it needs a digital infrastructure that can continuously evolve over the next ten years or even longer.

For the building intelligence industry, the future value of structured cabling will no longer be reflected merely in “being able to connect,” but in “running fast, running stably, and being capable of continuous upgrades.”

It is foreseeable that as AI, large models, edge computing, digital twins, and the Internet of Everything continue to deepen, structured cabling will gradually evolve from a traditional weak-current supporting system into one of the most important digital infrastructures of intelligent buildings. Those who plan the network foundation in advance according to the needs of the AI era will be more likely to take the initiative in future competition in building intelligence.