The Myth and Reality of Using AI for Network Evolution

AI’s power and potential

Artificial Intelligence (AI) is rapidly transforming industries, and telecom is no exception. AI technology offers the ability to analyze vast amounts of network data in real-time and will be integrated into telecom chips to enable network optimization and predictive maintenance within the network infrastructure. As AI solutions become more advanced, they simplify the process of monitoring and managing service performance. However, while the promise of AI is enticing, understanding how it truly works within the complex environment of telecom networks requires a closer look at both its capabilities and limitations.

Network Complexity and AI

Networks are not static; they are dynamic systems that are constantly evolving while also increasing in complexity and capacity. Automation plays and will continue to play a significant role in network monitoring, capacity planning, and predictive maintenance. As technology advances, AI will go beyond enhancing the network and become a foundational technology directing how networks are designed, built, operated and optimized.?

AI Network Hardware and Software Requirements

A telco infrastructure needs a uniform, software-based, multi-purpose, and distributed edge platform to create and enable an AI-powered telecom infrastructure and the integration of AI into telecom software development will unleash immense potential. TeleWorld Solutions can help pave the way to leverage software evolution and advance telecom networks.

AI and RAN

AI can play a crucial role in making an operator’s first line of defense smarter. For example, AI can help customer care teams get to the root cause of an issue by correlating network data from various elements and analyzing customer usage patterns to allow telecom operators to speed up the resolution process and enhance customer satisfaction. By rapidly collecting this data and patterns, telecom operators can leverage AI to make smarter decisions that improve network performance.

Using and Training AI

The reality is that operators can improve their networks by using AI to help identify limitations within their current tool set. Data scientists and engineers are vital to understanding machine learning algorithms. They help to classify segments and performance trends using both domain-specific knowledge and data science. While chips have the capability to perform necessary tasks, the algorithms must learn decision-making processes through machine learning. As operators are deploying AI, there needs to be a focus on the AI systems using machine learning to build robust AI models so that there is a continuous feedback loop and an adaptation to the evolving network needs. All AI models must learn—and learn correctly—to ultimately be effective for the network’s requirements.

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TeleWorld Solutions – Your Partner on Your AI Journey

TeleWorld Solutions offers expert support to operators looking to build robust AI software models that will evolve and gain efficiencies for their telecom networks.

?·???????? Faster Decision-Making: With AI, operators can quickly resolve customer problems by diagnosing and addressing issues with reduced response times.

·???????? Automating Repetitive Tasks: RPA technology has helped to streamline operations with automation however with AI, is faster, more dynamic and with self-learning capabilities allowing operators to more effectively handle repetitive tasks and free up resources.

·???????? Enhanced Observability and Analytics: Our solutions provide operators with deeper insights into network performance with enhanced observability and analytics allowing operators to have an end-to-end view of network and customer performance.

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