AI Core Unlocks Agent Networks with Terminal & Service Collaboration
At the 10th 5G Core Network Summit hosted by Informa Tech, George Gao, President of Huawei Cloud Core Network Product Line, delivered a keynote address calling on telco operators to capitalize on AI opportunities. Mr. Gao advocated for building an agent communication network featuring terminal service collaboration through network agentization. Huawei also released the Striding Towards the Intelligent World White Paper 2025 on cloud core networks at the summit, which illustrates seven core network development trends around intelligent terminals, service scenarios, and AI core networks, facilitating industry collaboration and innovation.
Mr. Gao emphasized that as terminals and service applications increasingly incorporate intelligent agent capabilities, networks must evolve to bridge ecosystem gaps.
First, we can use intent entry, network service agents, network capability agents, and network O&M agents to make the network agent-based. The agentized network supports the agent-to-agent (A2A) protocol and the model context protocol (MCP), allowing agents to communicate with each other. This brings more efficient and intelligent terminal and service collaboration. The intent entry interacts with the terminal-side agents, letting them invoke network agents exactly when needed.
Second, we can build an agent communication network across ecosystems. We can introduce A2A session management capabilities based on IP sessions, and expand the authentication mode from SIM card-based authentication to digital identity authentication and authorization.
Mr. Gao also proposed four strategic actions to speed the evolution of operator networks into AI core networks:
Intelligent Network Services
Leveraging AI agents, we can roll out various intelligent services on the core network. AI Calling is a prime example. By introducing AI capabilities to calling services, we can build an AI call assistant that can understand user intent, emotions, and contextual information, creating more intelligent and efficient call experiences. Based on the data channel (DC), we can support interactive calling, which facilitates closed-loop service handling during calls. In this new model, the familiar dial pad serves as an entry point for AI services.
Network Capability Productization
By productizing network capabilities, we can help operators shift from just selling traffic to selling premium service experiences. Huawei has defined five essential elements for effective experience monetization: definable experiences, guaranteed quality, marketable products, perceptible exclusive identity, and reliable service provisioning. With technologies such as media relay, we can greatly improve HD video penetration rates and third-party service experiences, and reshape operator’s business model.
Network O&M Autonomy
We can also introduce digital employees to advance network O&M autonomy, achieving high O&M efficiency and secure, high-stability networks. The AI core network uses key technologies such as agents, digital twins, and the industry’s first mixture-of-models (MoM) architecture facilitating intelligent scheduling and collaborative inference between fast inference models and deep reasoning models. With the fusion of these technologies, we can enable the AI core network to achieve single-domain autonomy and accelerate the evolution to level-4 autonomous networks.
Diversified Telco Cloud Computing Power
We can integrate AI computing resources into the telecom infrastructure. Through resource pooling and unified orchestration and scheduling, we can build one cloud for general computing and intelligent computing, accommodating hundreds of billions of agents and vast service traffic in the mobile AI era.
Mr. Gao concluded by stating that the introduction of AI Core is not only a technological advancement, but also a reconstruction of the entire industry ecosystem. Huawei is committed to continuous innovation, to help operators unlock new revenue opportunities and secure a stronger position in the market.
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