As networks expand in scope and areas of use, modern new services demand always-on performance, ultra-reliability and low latency, high levels of security, and networks that can support diverse use cases. Networks face increasing demands, requirements, and rising expectations, from improved performance and capacity to reduced energy consumption.
 |
| Rita Mokbel, Head of Ericsson Vietnam |
Furthermore, the network must deliver a superior experience for each service and user. At the same time, the evolution to 5G, the Internet of Things, and edge computing is making the mobile ecosystem and networks more complex. Networks must deliver value beyond connectivity.
Here, advanced AI network technologies will leverage ever more powerful machine learning and inference, generative AI and more to achieve complex and diverse business objectives, bringing service providers closer than ever to a fully autonomous intent-based network with minimal human intervention.
This is achieved by deploying AI agents within the network itself, replacing existing rule-based algorithms, adding new AI-based components with new capabilities, or adding AI-based controls to existing network components. These agents leverage the vast amounts of real-time data generated by today's networks to predict outcomes, detect anomalies, dynamically allocate network resources, optimize the network's quality of service, and much more.
The advent of cloud-native networks has opened up the entire network architecture to the possibilities of AI. Today, AI can be deployed across all network domains, from the network core to the RAN to the network edge, and at every stage of the network lifecycle.
Key use cases for AI in communications networks include customer and service experience. Cognitive tuning and optimization technologies contribute to a great user experience and reduce poor quality areas through timely enhancements, timely releases, and proactive network optimization. AI can also be deployed to improve customer service experience, with use cases covering customer relationship management, channels, sales, and marketing.
To drive cost-efficiency, AI-based network planning and design leverages deeper analytics that can accurately predict needs, including highly accurate traffic forecasts, KPI predictions, and identification of bottlenecks and load balancing opportunities across the network lifecycle. Service providers can also leverage live over-the-air measurements, such as subscriber traffic patterns, to ensure optimal 5G network expansion.
AI-based network diagnostics continuously optimizes and improves network performance and efficiency, scanning every network cell in minutes to identify issues quickly and with high accuracy, proactively identifying 50 percent more issues with up to 98 percent field-validated accuracy, improving operational efficiency by up to 30 percent.
Meanwhile, through new innovative means and technologies, AI can enhance and automate the current security of 5G networks, not only detecting zero-day attacks but also predicting upcoming attacks, detecting ongoing attacks, and testing and deploying new defense mechanisms at runtime.
AI is revolutionizing the concept of network operations, moving service providers closer to zero-touch, end-to-end network automation, which will progressively reduce manual operations and increase business agility based on augmented decision-making and data-driven predictive and proactive operations.
We are already seeing some key benefits of AI in communications networks: Where AI truly shines is in automating repetitive tasks, working faster and more efficiently, freeing up staff and resources for other areas. By taking over routine tasks and increasing network efficiency, AI-driven automation can optimize network operations and reduce costs.
In turn, communications service providers (CSPs) can leverage AI to manage growing complexity and improve customer experience while maintaining high network performance.
AI also pioneers a new paradigm for self-healing networks, improving the accuracy of root cause detection and accelerating time to resolution. When deployed at telecom sites, AI reduces the need for dangerous on-site work and remotely notifies engineers about outages and predicted service degradation.
It can also improve the energy efficiency of the network, maximizing network utilization without impacting performance with energy-saving features. AI can also act autonomously on real-time and even predicted traffic, helping CSPs reduce energy consumption and lower their carbon footprint.
The impact of leveraging AI in networks is truly transformative, not just in network performance but also in optimizing and reducing costs, resources and energy across the network, unlocking future business potential.
 |
New AI products raise more questions
As the AI explosion gathers steam with new product offerings from the world's largest technology companies, ethical concerns and investment considerations are coming into increased focus as industries such as media and manufacturing adjust their priorities. |
 |
Redefining journalism in the age of AI
The recent rise of AI has some journalists and media agencies fearing an invasion of their journalistic work, where it will be used (sometimes without permission) as a source to generate personalized content or to assist social media users who aspire to be opinion leaders. |
 |
AI-based solutions for responding appropriately to threats
Tinkering with the latest generative AI tools is fun for many, but AI has gone far beyond personal use to profoundly transform organizational and business operations. |
 |
Now is the time for Vietnam to seriously develop AI talent
Vietnam is well positioned to develop AI talent through government support, international collaboration and an influx of foreign experts. |
 |
Preparing for AI Innovation in Asia: Lessons from South Korea's Digital Transformation
The groundbreaking event, bringing together leading experts, academics, government officials and the innovative community to foster collaboration in AI research and development business across Asia, was held in Hanoi on July 11-12. |
