The Day One Keynote session at MBBF 2024 emphasised that we are entering a new era of AI facilitated by the expansion of 5.5G. With 5.5G expanding the boundaries of connections, AI allows them to connect intelligently.
Huawei’s rotating chairman Ken Hu gave the opening remarks, noting that 2024 has heralded a major milestone for 5.5G while also being a massive year for AI, and the duality and interplay between these technologies came to define the keynote presentation. Hu outlined the opportunities presented by 5.5G together with AI, but noted that to make the most of these, operators must make their networks stronger – carriers must prepare their networks to support AI, but we must also use AI to support networks. AI foundation models can help improve and guarantee network experience while making O&M more efficient. However, a greater synergy between networks, devices and applications is important for higher sufficiency . Hu noted that Huawei and industry organizations have partnered for 5.5G and AI programs to help industry players innovate together, exploring new services and creating new business models.
Dr. Omer Fatih Sayan, Türkiye’s Deputy Minister of Transport and Infrastructure, followed this with a welcome speech in which he touched on how digitalisation transforms our habits and communication styles. As technology continues to expand the boundaries of our intellectual world, it will increase intelligent connectivity, transforming lives and catalysing the growth of digital services. He emphasised that as 5.5G accelerates, new use cases will emerge as addressable markets are expanded.
The next speaker was Alex Sinclair, the Chief Technology Officer of the GSMA. He reflected on the swift progress that this generation of technology has already made – it took just three years for 5G to reach the one billion user milestone, significantly ahead of previous generations, and the rate of adoption is gaining traction. Sinclair claimed that 5.5G and AI jointly will present the next revolution, claiming that it is no coincidence that the two technologies are taking off at the same time given that AI needs the additional computing power afforded by 5.5G. Together, the technologies will push performance, enable better management and efficiency, and support more specialist use cases rather than generic connectivity. He noted that improved efficiencies could reduce network costs by as much as 80% - and that AI had the potential to contribute up to $15 trillion to global economy.
Engin Aksoy, the CEO of Vodafone Turkiye, gave a presentation entitled Accelerating 5G Progress to Move into the Mobile AI Era, in which he claimed that globally, most data is still currently 4G, by 2029 around 75% will be 5G. He noted that the possibilities 5G enables, such as boosted productivity and operational efficiency via techniques like network slicing and technologies like industrial IoT, will initially be felt in developed markets. However, by the end of this decade the impact will be hitting emerging markets, with improved efficiencies across the industrial, governance and utilities sectors – in fact, Aksoy noted that only 10% of 5G’s impact will be via services. 5G infrastructure key for transitioning to the mobile AI era with reduced latencies and hugely increased download speeds will enable mobile AI to trigger a wave of innovation and growth.
Turkcell CEO Dr Ali Taha Koç was the next to take the stage, ebulliently declaring that we are at a turning point in human history in that we have transitioned from the age of connecting everyone to the age of connecting everything. The escalating volumes of data involved in this means that bandwidth and throughput remain the critical challenges, and he argued that this would require a coordinated response from stakeholders – networks must become smarter and more compatible, as well as more cost and energy effective. Koç claimed that mobile AI represented a new growth era for this ecosystem, with 5.5G representing the highest level of technological maturity.
Marco Zangani, Chief Network Officer of Vodafone Italia, went into detail about how AI will impact mobile networks, breaking this down into three main categories: applications, network architecture, and network operations. AI-enhanced applications will drive the need for new device types, as well as placing new capacity and latency requirements on networks. In turn, this is likely to drive capacity growth going forward.
Using AI-native radio in network architecture can enable continuous performance optimisation, and AI can also facilitate efficient and secure data collection and storage in this environment, as well as distributed network functions to enable greater efficiencies. Zangani noted that amidst the increased complexity of networks, the relationship to customers is still paramount, and AI can help improve this through autonomous planning and optimisation, as well as fault detection and incident management to resolve issues quickly, and of course customer service.
CCS Insight’s Shaun Collins built on the idea of using AI for RAN network optimisation, and highlighted that using AI for core networks would improve system performance, while AI for devices and the cloud would improve user experience. By orchestrating networks more responsively in the event of an outage, AI implementation will make the 5G core more resilient, as well as reducing energy consumption in line with operator goals.
The presentation was closed out by Li Peng, Corporate SVP and President of ICT Sales & Service at Huawei. Li declared that we have entered the era of mobile AI, bringing huge new opportunities for the mobile industry. In this era, intelligence will become a universal service, and the mobile industry will play an important role. Li claimed that there would be huge changes in how information is created, shared and used, and this would necessitate a major shift in traffic models, with transmission required between the cloud, the edge, and devices. Facilitating reliable connections between these will involve reshaping network infrastructure for reduced latency. Currently, data is generalised and flows in a single direction, from data centre to smartphone, whereas AI will transform this – data will be personalised and will flow in multiple directions. Li gave the example of LLMs requiring fast transmission between data centres as well as AI applications and AIGC needing to transmit between edge, cloud, and devices.
With the structural changes in traffic models, network optimisation will be more critical than ever, with new services requiring larger uplink bandwidth, deterministic latency, and more reliable network capabilities. Li outlined four key focus areas for capitalising on new opportunities in the AI era: network services, infrastructure, O&M, and business models.
Li explained that since mobile products and services are the perfect access points for AI, they must be restructured to better meet demand. For individual consumers, carriers can take advantage of common touch points to provide intelligent services for areas such as calling, messaging and customer service. Li gave the example of 5G New Calling, launched by carriers in China, which offers users the ability to create digital AI avatars, access real-time translation, and even have their AI assistant book appointments. The service already has over 24 million users in China.
AI agents are a major use case for homes – Li gave the example of one carrier launching an AI box supporting applications such as interactive sports watching and AI fitness for TVs. As a result, TV usage doubled and ARPU grew by 28%. Outside the home, carriers can also provide stable, high-speed connectivity for carmakers to enable intelligent cockpits and vehicle-cloud collaboration. Li also outlined AI opportunities in the B2B market, both for SMEs and enterprise. Combining connectivity, networking, and AI capabilities makes the intelligent transformation offering more affordable.
Li said that infrastructure must also be reshaped to reduce latency and thereby support a wider range of experiences for AI services. Carriers must focus on deterministic access, elastic scheduling, and lossless WAN to ensure their networks are AI-centric. This reduces air interference latency to help deliver on-demand, reliable connections between cloud, edge, and devices.
While this makes networks more complex, AI for networks can help address the O&M challenges that will arise from this. Carriers can use AI agents and copilots to make both operations and maintenance much more efficient: for service operations, AI agents can support real-time simulation of multi-modal data, helping carriers evaluate network resources more efficiently and provision new services more quickly. For network maintenance, AI agents can automate task planning and orchestration, solving problems caused by software. At the same time, copilots can help field engineers to quickly locate and fix any hardware problems.
Li argued that experience can now be monetised, so business models should also be reshaped. Demonstrating this, more than 30 European carriers have launched speed-based mobile plans, so consumers are evidently willing to pay more for a guaranteed experience, while Chinese carriers are exploring multi-factor monetization to open up revenue streams based on computing power, storage, and VIP services. For enterprise customers, carriers can also learn from cloud service models, and expose network capabilities with open APIs. Carriers can monetize these capabilities, and expand into the B2B2C market.
In conclusion, Li outlined the two main preparations necessary for capitalising on new opportunities in the mobile AI era: preparing our networks to support AI by boosting network capabilities, and using AI to support our networks – for example by automating O&M and optimising network efficiency to guarantee a solid user experience.
