How AI Is Transforming the Future of Mobile Networks

Tashkent, Uzbekistan (UzDaily.uz) — Over the past four decades, the mobile communications industry has evolved from simple voice calls to intelligent networks capable of analysing data, adapting to traffic loads and managing their own operations. Today, the sector is entering a new stage of development in which artificial intelligence (AI) plays a central role.

The first generations of mobile communications were designed exclusively for voice transmission. Networks functioned as electronic switching systems that connected subscribers. With the introduction of 3G and 4G technologies, the industry shifted to packet-based data transmission. The emergence of smartphones and cloud-based over-the-top (OTT) services ushered in the era of Mobile Broadband (MBB), fundamentally changing the way digital services are consumed.

The industry is now approaching another technological transition — the era of AI agents. As AI-powered devices become more widespread, mobile networks face fundamentally new requirements.

Where networks were once designed primarily to transmit information, they are increasingly expected to support the intelligent exchange of data required by AI models. At the centre of this concept are tokens — units of information used by modern generative AI systems.

In this environment, the network is evolving from a data transport channel into an intelligent platform that integrates connectivity, computing resources and user experience management. At the same time, the density of connected devices is expected to increase rapidly, while requirements for latency, bandwidth and network reliability become increasingly critical.

To examine how the global ICT industry is preparing for these changes, a UzDaily journalist attended the GSMA Mobile World Congress (MWC Shanghai), held in Shanghai in June. Leading mobile operators, technology companies and industry experts presented their vision for the future of mobile networks.

During the three-day event, which combined a large exhibition with forums and industry conferences, more than 37,300 participants from 143 countries attended, including representatives of Uzbekistan's telecommunications sector.

Huawei, which has operated in Uzbekistan for more than 26 years, was among the event's most active participants. Together with mobile operators, industry partners and experts, the company discussed the development of next-generation communications technologies, computing platforms, 5G-Advanced (5G-A) networks, high-speed uplink technologies and the integration of AI into telecommunications infrastructure.

Dmitry Konarev, Huawei's Lead ICT Solutions Architect, presented practical examples of the intelligent transformation of telecom networks. His presentation focused on the transition from the traditional internet to an ecosystem of AI agents and the emergence of a new token economy, in which networks serve not only as channels for data transmission but also as intelligent infrastructure supporting AI interactions.

As part of the programme for media representatives, participants also visited Huawei's research and development centre at Lianqiu Lake in Shanghai. The centre demonstrated technologies capable of delivering data transmission speeds of up to 10 Gbit/s by combining millimetre-wave and C-band spectrum, as well as intelligent streaming services and personalised user experience technologies.

Another session focused on the role of artificial intelligence in the development of mobile infrastructure. The speaker was Eric Zhao, Vice President and Chief Marketing Officer of Huawei's Wireless Solutions division.

According to Zhao, the industry will eventually move towards an end-to-end intelligent architecture in which the cloud becomes the centre of intelligence generation, devices serve as application platforms, and the network functions as an intelligent intermediary between them. In this model, networks will be responsible for transmitting not only data but also tokens — the elements required for AI models to operate and make decisions.

Such a transformation requires significant changes to mobile network architecture. Among the priorities are reducing latency, increasing uplink capacity and integrating AI into infrastructure management. Machine learning algorithms are already being used to optimise radio resource allocation, increasing network efficiency, expanding capacity and improving service quality.

Artificial intelligence is also becoming an important tool for improving energy efficiency. Intelligent management enables base stations to reduce power consumption without affecting performance, making network operations more economical.

Industry specialists also highlighted the growing role of digital twin technology. Instead of addressing faults after they occur, operators are moving towards predictive maintenance, allowing them to forecast equipment conditions and prevent potential failures.

AI models can create digital twins of networks, providing real-time information on coverage, signal strength, frequency usage, data transmission speeds and service quality across the network. This gives operators a comprehensive view of infrastructure performance and allows them to respond more quickly to changing conditions.

The next stage of development could involve integrating digital twins of equipment, networks and the surrounding environment into a single intelligent system. Modern antenna systems are gradually evolving from passive hardware into intelligent network components. They can independently report their position, vibration levels and weather conditions, while automatically adjusting beamforming parameters to ensure more stable coverage.

According to industry experts, further digitalisation of infrastructure will provide the foundation for the full integration of artificial intelligence into mobile network management. Unlike traditional algorithms, AI is capable of making decisions based on the analysis of vast amounts of data, creating opportunities for fully autonomous networks.

In the future, mobile networks could independently detect deteriorating service quality, redistribute resources, predict failures and perform most operational tasks without human intervention. In the absence of critical hardware failures, infrastructure could maintain stable operations autonomously, significantly improving the reliability and quality of communications services.

The mobile communications industry is now entering one of the most significant transformations in its history.

The networks of the future will no longer function solely as platforms for transmitting voice and data. Instead, they will become intelligent, self-learning systems capable of analysing information, making predictions and taking decisions in real time.

Artificial intelligence and digital twins are becoming the foundation of the next generation of mobile communications, while the pace of their adoption is expected to shape the development of the global digital economy in the years ahead.