2025 is set to be the year when 5G will achieve maximum momentum. According to GSMA Intelligence, 5G has experienced the fastest mobile generation rollout, with connections expected to surpass 5.5 billion by 2030. So, what is behind the projected acceleration of 5G adoption from 18% in 2023 to 51% by 2029? Increasingly, the market is betting on the advancement of Generative AI (GenAI) in wireless networks. Let’s break down GenAI’s role and how CSPs turn 5G’s potential into a reality.
1. GenAI will evolve telecom’s focus from connectivity to intelligent digital ecosystemsOne of the key benefits of the advancement of GenAI is that it cannot just analyze existing data but also create new original content such as images, text, videos, sounds, and other outputs. This marks a rapid change from machine learning, which focuses on making predictions or decisions based on historical results or patterns. For Communications Service Providers (CSPs), GenAI can unleash the real potential of 5G from simply delivering connectivity to fostering intelligent digital ecosystems to support the expansion of IoT, smart cities, and enterprise applications with AI-optimized solutions. For example, according to City AI Connect, a global community for cities to learn about generative AI, nine out of ten mayors in cities across the world want to engage in GenAI - where they see the potential for it to address their traffic and transportation, infrastructure, public safety, environment and climate, and education challenges. Some even go further and want to use GenAI to help them predict where house fires might occur, how to lower healthcare claims, and even anticipate street violence. To do this, smart cities need more than just connectivity from CSPs; computing power at the edge of the network close to where data is generated and consumed will be required. The vision of truly smart cities requires intelligent digital ecosystems that are only possible when CSPs expose their network capabilities via APIs to empower these smart city applications and use cases.
2. GenAI will drive network transformation and fault-free networksAccording to a recent report by TM Forum, 55% of communications service providers surveyed said they have made good progress using AI and machine learning across their business from customer experience to network operations. While enhancing customer experience with AI-powered support systems has seen the most traction with the rise of AI, CSPs have a variety of ways where GenAI can benefit them as they transform and manage their networks. For example, GenAI can help to slash the time it takes for field teams to install network elements, such as switches and routers, reduce downtime with automated predictive maintenance, and accelerate how network engineers respond to network outages. With GenAI, network engineers can perform root cause analysis and resolve issues more efficiently using tools that reference historical data and consult manuals to identify solutions for similar past incidents. Ultimately, GenAI will help with proactive network management identifying and resolving technical issues before they impact the end customer. On the network provisioning and management side, GenAI brings zero-touch provisioning and automation one step closer to reality by using agents to monitor and help manage the network.
3. GenAI will strengthen network security and trust
AI has been a force for good and evil, particularly when it comes to telecom security and fraud. Today, deepfake scams commonly target us through voice, SMS, and video, with AI increasingly amplifying both the scale and sophistication of these security and fraud attacks. However, with GenAI, CSPs can get ahead of bad actors by simulating potential security threats and attack scenarios in turn training their security systems and teams. This not only enables network security teams to better prepare themselves for the challenges of an AI enabled world, but also strengthens their network security and trust mechanisms. For example, with GenAI, fraud systems will be able to identify synthetic content, such as fake images and voice clones, to help distinguish and block untrustworthy content. This is especially critical as consumers increasingly fall victim to telecom fraud, with regulators placing the responsibility on operators to combat this growing threat.
4. GenAI will ensure fault-free and reliable networks
When combined with advanced analytics, GenAI can ensure fault-free and reliable networks. For example, GenAI can help create synthetic data that emulates actual customer usage patterns for testing and development. Likewise, when adding unstructured data from customer interactions, such as social media comments or conversations with customer service representatives, CSPs can add a new layer of precision to their network investment, planning, and design decisions. In addition, GenAI can support dynamic resource allocation to optimize performance across a diverse range of use cases. Soon, the days of buffering videos and lag times will be a thing of the past. With GenAI, networks will be able to identify the content, predict user demand for it, proactively pre-cache at the edge, and improve user perceived latency. GenAI can then enable intelligent systems to adjust the streaming quality based on the user’s device or network congestion to ensure a high-quality, seamless user experience. At the enterprise level, GenAI can be used to develop customized 5G network solutions that best fit their needs across IoT, smart factories, and AR/VR.
5. GenAI will enable digital transformation across industries
The promise of GenAI cannot be understated. According to McKinsey, GenAI could add the equivalent of $2.6 trillion to $4.4 trillion annually to industries across the globe. Banking, high tech, and life sciences are among the top industries that will benefit the most from GenAI developments across their sales, marketing, software engineering, product R&D, and customer operations. The telecoms industry is positioned to help accelerate the digital transformation across all those verticals due to its role as the connectivity fabric; for example, supporting smart cities, hybrid work environments, and enterprise solutions. GSMA predicts a fourfold rise in mobile data traffic between now and 2030, with monthly global mobile data traffic per connection growing from 12.8 GB in 2023 to 47.9 GB in 2030. But instead of focusing just on how networks can ensure high-quality connectivity, the telecom sector must also see GenAI as a driver of innovation and new revenue opportunities for the telecom sector itself. McKinsey sees that the telecom sector could experience 2.3-3.7% revenue and productivity gains with GenAI, equivalent to $60-100 billion globally. To seize this opportunity, CSPs must leverage the vast volumes of unstructured data outside their OSS/BSS systems and integrate it with the structured data within. By bridging this gap, they can unlock the potential to only optimize their networks but also drive significant revenue growth.
Let Us Know What You Thought about this Post.
Put your Comment Below.