Broadband service providers (BSPs) could soon accelerate and enhance their offerings by adopting AI, thanks to a new initiative called “AI in Broadband Networks.” Led by the Broadband Forum, this project aims to provide practical guidance for BSPs to evolve service-led broadband networks in step with rapid advances in artificial intelligence.
The initiative’s main objective is to enable BSPs to integrate AI into their networks in ways that improve speed, reliability, and operational efficiency. At the same time, equipment manufacturers will receive recommendations for embedding AI capabilities into hardware and firmware, making devices better suited to AI-driven environments.
Tony Zeng, Standard Director of EU Optical Communication at Huawei France, stressed AI’s transformative effect on data handling and decision-making. “AI is already revolutionising how data is processed and how decisions are made across domains, from smart applications to autonomous networks. In broadband networks, AI can play an important role in addressing challenges like fault prediction, quality of service optimisation, and dynamic traffic management.”
Zeng added that the “AI in Broadband Networks” effort will position AI alongside the traditional pillars of AI development—algorithms, computing resources, and data—by making AI itself a key architectural consideration in broadband networks.
The project will document how AI can autonomously detect and resolve network faults, predict equipment failures so corrective measures can be taken before outages occur, and optimise energy consumption to reduce operating costs while improving performance.
Another focal point will be deployment models for AI agents that provide intelligent user support within broadband networks. The guidance will outline how telecom infrastructure should be designed or upgraded to meet the performance and latency demands of AI-powered applications and services.
Hai Ding, Fixed Access Network and Home Networking Expert at China Unicom, highlighted the long-term advantages of AI adoption. “By embracing AI-driven approaches, BSPs can reduce costs, accelerate time to new revenue, and deliver innovative applications and services to their customers,” he said.
Planned in two phases, the first phase of the project will summarise AI development trends relevant to broadband networks, present a roadmap for network evolution, and define key service requirements for BSPs. The second phase will deliver a detailed analysis of AI-driven fixed access and in-premises network architectures, along with the corresponding network functions and operational considerations.
The project already counts initial support from several major organisations across the global telecom ecosystem, including Huawei, China Mobile, China Unicom, CAICT, and ZTE Corporation. The first phase is expected to be completed by spring 2026.
Implementing machine learning and other AI techniques across network layers can help BSPs offer more dependable services at lower cost. Techniques such as anomaly detection can preempt network faults, while AI-powered virtual assistants and chatbots can improve customer interactions and reduce operational expenses by handling routine support tasks.
By standardising approaches to AI integration and clarifying architectural and functional requirements, the “AI in Broadband Networks” project aims to accelerate the deployment of intelligent network capabilities that benefit operators, equipment makers, and end users alike.
(Image source: “Inside a broadband router (detail)” by jepoirrier is licensed under CC BY-SA 2.0.)
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