The convergence of 5G technology and artificial intelligence (AI) is transforming the telecommunications landscape. Communications service providers (CSPs) can leverage AI tools — including machine learning, predictive analytics and natural language processing — to streamline operations, increase productivity and implement new monetization strategies.
While many providers have focused on incremental network upgrades, visionary leaders are harnessing 5G and AI to transform their networks. The transition to open, cloud-native architectures enables the ultra-low latency and high bandwidth that next-generation AI applications need. Early movers will gain a significant advantage in this evolving landscape.
The intersection of 5G and AI facilitates real-time decision-making and automation across complex networks, creating unprecedented opportunities for CSPs to deploy innovative AI-powered solutions across their infrastructure. This speed, agility and efficiency is driving many CSPs to begin their broader network and operational transformations.
Elevate network and business outcomes
With their distinct advantages of network control, customer proximity, data access and 5G capabilities, CSPs are well-positioned to be leaders in deploying AI-powered solutions from the data center to the edge to improve network performance, increase customer satisfaction and create new revenue.
CSPs can ensure maximum performance and reduce operating expenses when deploying AI throughout their networks. Myriad use cases for AI-enabled solutions include:
Automated predictive fault analysis: AI-powered predictive analytics can enable CSPs to proactively identify and address potential network faults before they impact customers, leading to improved operational efficiency, cost savings and enhanced quality of service.
Proactive troubleshooting: Service providers can apply AI to network data and customer feedback to quickly identify the root causes of issues and guide technicians through more efficient troubleshooting processes, reducing the time and cost associated with resolving network problems, ultimately improving network reliability and uptime.
Reduced power consumption and emissions: AI-enabled network tuning can shut down underutilized network elements, such as mobile radios or baseband CPU cores in areas that have less traffic at certain times, significantly enhancing power and resource utilization and reducing operational expenses.
Enhanced customer experiences: With close access to customer data and the ability to reach customers through the mobile devices they use every day, service providers can leverage AI-powered chatbots to provide personalized service and support, ultimately improving customer loyalty and driving new revenue.
For instance, SK Telecom has partnered with Dell Technologies to develop a chat agent that automates many customer service tasks, learns preferences over time and recommends personalized plan upgrades and new devices.
GPU-as-a-service (GPUaaS): Telecom providers can lease AI compute capacity on their network infrastructure that customers can use to run their own AI applications, creating new enterprise-level network monetization opportunities.
For example, Dell and NVIDIA collaborated with Lintasarta, an Indonesian information and communication technology solutions company, to develop AI solutions with Dell AI Factory infrastructure. Lintasarta is offering GPU Merdeka, a GPUaaS, to provide AI infrastructure, including NVIDIA GPUs with Dell servers, for national businesses.
Network slicing and quality-of-service levels: These services enable CSPs to deliver tailored performance for various applications, ranging from low-latency Internet of Things to augmented reality/virtual reality or gaming experiences, creating additional monetization opportunities enabled by AI and 5G.
Enable distributed AI computing across telecom networks
Mobile data traffic is expected to surge from 109 million terabytes per month in 2023 to 603 million terabytes per month by 2030. CSPs who continue to pursue a data delivery model will incur escalating costs without corresponding revenue growth. Operators that develop systems and infrastructure to effectively harness massive data volumes will create operational efficiencies and revenue growth.
To fully capitalize on opportunities including AI and 5G, the time is now for CSPs to fundamentally transform their legacy systems and operations. This includes shifting from siloed infrastructure to open, cloud-native solutions, modernizing IT operations, simplifying technology integration and implementing AI-driven business processes.
The future of AI in telecommunications hinges on the ability to distribute compute capacity and data processing across geographical locations to enable AI workloads to run in the most optimal locations. Telecom providers have an unparalleled opportunity right now to leverage their existing distributed infrastructure to host AI compute capacity closer to customers, enabling more efficient and responsive AI operations across their networks.
Accelerate network evolution with an open ecosystem approach
CSPs need to carefully balance network modernization for AI with service reliability by taking an iterative approach that begins with establishing a clear network evolution vision and making investments that can be leveraged to support the transition to cloud-native, open architectures. This balanced strategy allows CSPs to innovate and stay competitive in the data-driven market while minimizing service disruptions.
Open ecosystems are vital for this transition. A diverse set of partners can provide specialized expertise to help CSPs navigate transformation complexities while providing access to advanced technologies – from purpose-built AI servers that are optimized for acceleration to ruggedized hardware for AI at the telecom edge. This collaborative approach accelerates the transition to open architectures, driving innovation across networks while reducing costs and time to market, ultimately boosting revenue potential.
The synergy between 5G and AI accelerates network transformation by enabling CSPs to optimize resource allocation and enhance the customer experience. CSPs can reduce costs while improving service quality. And, by embracing an open ecosystem, providers are well-positioned to grow and compete in the dynamic telecommunications landscape.
