Intelligent assistants respond to needs at any time, robots work bustlingly like real people, and intelligent connected vehicles navigate freely through the streets... As the dominoes of inclusive AI accelerate their fall, an era of mobile AI where intelligence is ubiquitous is rapidly approaching.

Just as 4G networks extended the reach of the internet to every corner in the mobile internet era, for AI to penetrate all aspects of social production and life like air and electricity, it also requires a more robust and intelligent mobile communication network foundation to support it.

So, what new changes and demands will the upcoming Mobile AI Era bring to mobile communication networks? How will the industry respond to these changes? On March 3, 2025, during the Products and Solutions Launch Event at MWC25 Barcelona, Cao Ming, Vice President of Huawei and President of the Wireless Network Product Line, unveiled the AI-Centric 5.5G solution and provided an interpretation.

He stated that the full eruption of Mobile AI has brought about three major transformations in user experience, network operation and maintenance, and business models. Through intent-driven AI-Centric 5.5G series solutions, Huawei achieves diverse AI application experiences, high-level autonomous intelligence operation and maintenance efficiency, and multi-dimensional commercial monetization.

Three Major Transformations for the Mobile Industry

In the future, for robots to understand data collected from the surrounding environment by sensors such as cameras, radars, and microphones, and then autonomously and dynamically execute various tasks, they need to upload this multimodal data in real-time to the edge cloud for AI training and inference through the network's large uplink capacity. The response interval in human daily conversations cannot be too long, otherwise, it will feel extremely unnatural. Therefore, for AI chatbots to achieve human-like interactive experiences, they need to ensure that the latency of natural language processing and network transmission is low enough. Intelligent connected vehicles rely on high-quality network coverage for every road, from dense cities to remote mountainous areas.

These typical use cases tell us that entering the Mobile AI Era, as AI permeates all aspects of individuals, organizations, and society, it spurs a massive number of intelligent terminals and diverse AI applications, placing more diverse demands on the network experience. This requires the network to transition from a service model focused primarily on downlink experience to one that guarantees diversified experience services. This brings an experience transformation to the industry.

More diverse intelligent applications and denser intelligent terminal connections will inevitably make the network more complex, leading to a significant increase in the difficulty and cost of network operation and maintenance. At the same time, with the popularity of generative AI, the quality and richness of digital content continue to improve, and multimodal data interactions between terminals and the cloud or edge become more frequent, driving continuous increases in network traffic and putting greater pressure on network energy consumption. Therefore, the network urgently needs to evolve towards a higher level of autonomy to further enhance operation and maintenance efficiency and network energy efficiency. This brings an operation and maintenance transformation to the network.

The booming rise of intelligent applications and intelligent terminals undoubtedly brings unprecedented revenue growth opportunities for operators. However, given the precedent of operators generally experiencing "increased traffic without increased revenue" in the past few years, for operators to seize this wave of "immense wealth," they need to accelerate their transition from the traditional "traffic management" model to the "experience management" model. Fortunately, leading operators have begun actively exploring experience management in recent years. For example, more than 10 operators worldwide have launched mobile broadband experience monetization packages; domestic operators have introduced innovative applications such as new calls and cloud phones that integrate network experience, cloud, and computing capabilities. Therefore, building experience management has become an inevitable path for industry development, and the mobile industry is ushering in a business model transformation.

AI-Centric 5.5G Reshapes the Foundation of the Network

How to respond to the three major transformations of the Mobile AI Era? Huawei's answer is: the intent-driven AI-Centric 5.5G solution, assisting operators in improving efficiency, reducing costs, and increasing revenue through three major solutions: GigaGear, GreenPulse, and GainLeap.

First is GigaGear, which provides adaptive differentiated experiences for diverse AI applications and scenarios based on real-time dynamic resource scheduling aligned with experience intentions.

Specifically, GigaGear first translates experience intentions into network requirements, then automatically allocates and configures network resources to match these intentions. It continuously senses and proactively predicts the experience SLA, and flexibly schedules resources through multi-domain coordination across time, frequency, space, and airspace domains to ensure that intentions are continuously met.

Next is GreenPulse, which is based on the intention of improving network quality and efficiency. According to multi-dimensional requirements such as spectral efficiency and energy efficiency, it achieves precise energy savings of "0 Bit 0 Watt 0 Loss" and high-level network autonomy of "0 Touch 0 Wait 0 Fault" through the professional collaboration of multiple agents.

GreenPulse first receives and understands the intentions expressed by operation and maintenance personnel through seamless human-machine interaction, then conducts multi-dimensional diagnosis of network issues and makes precise decisions through the professional collaboration of multiple agents, and finally efficiently executes strategies through end-to-end full-link collaborative digitalized sites across all domains.

Finally, there is GainLeap, which, based on the opening up of network capabilities, can orchestrate new services on demand by understanding commercial intentions such as experience monetization and contextual monetization. After launching new services, it monitors and proactively predicts service quality and resource usage in real-time, dynamically adjusts resources and autonomously optimizes performance, and continuously guarantees service experience, thereby helping operators quickly seize service monetization opportunities for different user groups, business types, and scenarios.

In short, facing the network experience transformation and business model transformation in the Mobile AI Era, GigaGear can help operators create differentiated, high-quality service experiences with optimal resource utilization, realizing the transformation towards experience management; facing the operation and maintenance transformation, GreenPulse pushes the network towards a higher level of autonomy, helping operators significantly improve operation and maintenance efficiency and network energy efficiency, and significantly reduce operating costs; facing the continuous emergence of new businesses and scenarios in the Mobile AI Era, GainLeap can assist operators in flexibly and agilely launching new businesses and services with excellent experiences in the fierce market competition.

Intent-Driven Advancement Propels the Industry to Leapfrog Progress

It is not difficult to see from the above three capabilities that the core highlight of AI-Centric 5.5G lies in intent-driven. What is intent-driven? Simply put, it's like an autonomous vehicle: you just need to tell it the destination, and without worrying about driving skills or road conditions, it can safely take you there via the most convenient route.

Connected autonomous driving, through the coordination of vehicles, roads, and the cloud, can perceive global information and make global strategies. It can not only automatically plan the most reasonable routes but also flexibly respond to unexpected situations on the road. The intent-driven autonomous network also has similar characteristics: it can deploy network capabilities on demand based on specific goals or expectations (intentions); it can comprehensively perceive network conditions; it can balance multi-dimensional conflicts within the network to formulate comprehensive and precise network strategies; it can also dynamically respond to new changes in the network and business; meanwhile, the entire process requires no manual intervention.

These capabilities are particularly important for the continuous high-quality development of networks and businesses. Taking the field of network operation and maintenance as an example, it is well-known that the user distribution and business characteristics of mobile networks dynamically change, and there are many factors that affect network performance and user experience, which are interrelated. This makes it difficult for traditional operation methods to make optimal network decisions by integrating multi-dimensional factors, and even problems often arise where "solving one problem creates another." For example, when operators implement energy-saving shutdowns, if the energy-saving solution does not have a global perspective and cannot dynamically respond to business changes by timely shutting down and waking up equipment, it will not only be difficult to maximize energy savings but may also affect the user experience. Thanks to intent-driven, Cao Ming introduced at the conference that an operator achieved a 36% increase in traffic during holidays through GreenPulse while reducing energy consumption by 18%, achieving both energy savings and performance excellence.

How exactly does AI-Centric 5.5G achieve intent-driven functionality? During the MWC, Zhao Dong, Vice President and Chief Marketing Officer of Huawei's Wireless Network Product Line, said at the media conference that the key lies in the construction of the Agentic Workflow. Based on the three-tier architecture of the Radio Intelligent Service Engine (RISE), MBB Automation Engine (MAE), and digitalized sites, the Agentic Workflow first translates business intentions in different scenarios, then decomposes tasks to multiple agents for parallel execution. Multiple agents can collaborate like a team composed of experts in different fields to achieve optimal overall accuracy of business results. At the same time, the digital twin system evaluates the business operating status in real-time and provides closed-loop feedback on scenario changes to the agent team for iterative optimization, ensuring optimal business results at all times.

Albert Einstein famously said, "The measure of intelligence is the ability to adapt to change." Obviously, intent-driven with a high degree of adaptability represents a leapfrogging advancement for the mobile industry towards intelligence and adapting to the new demands of the Mobile AI Era. Huawei Wireless has taken the first step.