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Transforming Network Value for AI-Driven Growth

During the Network X 2026 event held in Vienna, the World Broadband Association (WBBA) organized the Broadband Development Congress (BDC). The highlight of the event was a keynote speech by Bob Chen, the President of Huawei's Optical Business Product Line. His address focused on the critical topic, 'Reconfiguring Network Value for New Growth in the AI Era.'

The Need for Transformation

In his presentation, Chen underscored the urgency of adjusting how networks are constructed and operated to adapt to the rapid advancements in artificial intelligence (AI). According to him, the last three decades have seen various service booms fueled by network support, ranging from voice services to the Internet and video streaming. Currently, AI is progressing at an unprecedented speed, with large AI models now containing nearly 10 trillion parameters and token consumption skyrocketing nearly 50 times within a year. As AI evolves, the dynamics of objects, connection frequencies, and the quality of network connections have drastically changed.

Chen proposed that the fundamental shift in reconfiguring network value boils down to three pillars, which he referred to as the three 'R's: Reconstructing the Network Architecture, Reconfiguring the Business Model, and Redefining Operation and Maintenance (OM). By focusing on these aspects, the industry can rethink its approach to network valuation and drive new growth.

Reconstructing the Network Architecture

Historically, networks were centered around administrative regions, segmented into national backbones, provincial networks, and metropolitan areas. However, with the rise of AI, the number of AI Data Centers (AIDC) has exploded almost tenfold. The growth in traffic is no longer dictated by population but by computing power. Chen cited Zhongwei in China as a prime example; once representing merely 0.1% of national traffic, it has now transformed into one of China's eight national computing centers, contributing over 10% of the nation's total bandwidth. This shift is prompting a necessary transformation in network architecture from administrative-centric designs to data center-centric structures.

Reconfiguring the Business Model

In the business sector, as AI accelerates, traditional business models are changing. Chen illustrated this with an example of an AI-based industrial design firm in China that leverages AI rendering to drastically shorten production cycles—a process demanding latency under 2 milliseconds. Operators can adapt to such opportunities by evolving from merely selling bandwidth to providing a multifaceted package including 'Bandwidth + Latency + Reliability.' With cutting-edge technologies such as Optical Cross-Connect (OXC), Automatic SONET/SDH (ASON), and quantum encryption, networks can ensure deterministic latency, enhanced reliability, and optimal security levels, significantly boosting the value of private lines. Additionally, by integrating computing platforms, operators can move from just offering connectivity to providing a comprehensive 'Network + Computing + Application Model.'

In residential broadband, the evolution is from simple connectivity to a comprehensive strategy termed 'One Fiber, One Network, One Home.' This involves ensuring high-quality Wi-Fi connectivity through Fiber to the Room (FTTR) or mesh networks across homes, and deploying intelligent applications powered by AI devices and agents to enhance user interaction within the home environment.

Redefining Operation and Maintenance (OM)

With the advent of AI, achieving all-encompassing intelligence across the full life cycle of planning, construction, maintenance, optimization, and operation is essential. Chen pointed out that most complaints related to home networks stem from Wi-Fi connectivity issues. AI-driven Wi-Fi optimization can automatically identify sources of interference and adjust parameters in real-time, boosting Wi-Fi speeds by about 20% in interference-prone environments.

Moreover, previous network equipment operated at full capacity regardless of traffic levels, resulting in unnecessary energy consumption. Intelligent traffic analysis now enables dynamic adjustments in power levels, allowing a reduction of total energy consumption by over 20%. For intelligent self-healing of faults, Chen outlined a tiered approach for troubleshooting home broadband issues, powered by AI agents that can resolve common problems autonomously, remotely manage configuration parameter issues, and accurately pinpoint physical fiber connection problems.

In conclusion, Bob Chen asserted, 'In the age of AI, we must transform our philosophy to reconstruct the network architecture, reform the business model, and redefine network OM.' Through these three 'R's, we can reshape UBB network value and progress towards new growth as we embrace AI's potential.