TLDR: Huawei has unveiled significant advancements in its multi-agent technology, aiming to revolutionize network management by enabling higher levels of autonomy. This initiative, showcased at MWC Shanghai 2025, integrates AI agents and large language models to create self-managing networks capable of intelligent automation, improved efficiency, and enhanced user experiences.
Shanghai, China – Huawei is leading the charge in network evolution with its latest multi-agent technology, designed to usher in a new era of self-managing and highly autonomous networks. The company highlighted these innovations at MWC Shanghai 2025, emphasizing a strategic push towards achieving Level 4 autonomous networks through advanced AI integration.
Eric Zhao, Vice President and CMO of Huawei’s wireless business, underscored the company’s commitment to this paradigm shift, stating that Huawei is actively advancing ‘multi-agent collaboration’ to empower telecom operators in their journey towards higher levels of network autonomy. This move builds upon a year of successful deployments where AI agents have already demonstrated their efficacy in critical areas such as fault detection, congestion management, and energy efficiency for operators both in China and internationally.
At the core of Huawei’s strategy is the deep integration of AI, particularly large language models (LLMs), with 5G-Advanced (5G-A) network capabilities. This synergy allows for the creation of intelligent agents that can communicate, share data, and make collaborative decisions in real-time. These multi-agent solutions are designed to manage and optimize complex network operations, enabling intelligent automation of tasks like traffic management, predictive maintenance, and network troubleshooting. This distributed approach is particularly vital for the vast and intricate 5G and 5G-A networks, where manual operations are increasingly impractical and prone to errors.
The benefits of this multi-agent architecture are substantial. For instance, in collaboration with China Telecom, Huawei has demonstrated remarkable improvements in operational efficiency and service quality. An AI agent designed for operations and maintenance (O&M) has been shown to assist installation and maintenance personnel in accurately locating faults, reducing troubleshooting duration by 30% and decreasing the workload of inquiry center experts by 10%. Furthermore, the Wireless Network Optimization Task Model, leveraging high-precision network simulation and intelligent parameter adjustment, has improved user experience by 10% to 15% in pilot regions and reduced the handling time of typical issues by 20% to 30%.
Cao Ming, Vice President of Huawei and President of Huawei Wireless Solution, articulated the broader impact, noting that ‘Mobile AI is booming, bringing three major transformations to mobile networks in terms of user experience, O&M, and business models.’ He emphasized that this transformation reflects how connectivity is evolving beyond human-to-human communication to increasingly include human-to-AI and AI-to-AI interactions, demanding networks with higher uplink capacity, lower latency, and ubiquitous coverage.
Huawei’s commitment to advancing industry standards is also evident. In conjunction with China Telecom and TM Forum, the company has contributed to developing standards for foundational model lifecycle management and AI agent technical specifications, aiming to transform innovative practices into industry-wide frameworks. This collaborative effort recently earned Huawei and China Telecom the TM Forum’s Excellence Award 2025 in Data and AI Innovation, further solidifying their leadership in the AI+network domain.
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Looking ahead, Huawei envisions a future where multi-agent networks form the crucial mobile infrastructure for deploying advanced intelligent applications, including embodied robots, AI intelligent assistants, and autonomous driving. This vision is supported by the projected growth of the intelligent robot market, expected to reach 1.2 trillion RMB by 2025, highlighting the immense potential of these self-managing network solutions.
