How Are Telecoms Saving Millions On Network Operations And It? These Ai Use Cases Show You The Way

By Author: Frame Outlook
Total Articles: 14
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A recent study by McKinsey found that AI-driven automation in telecom operations could lead to a 25-30 % reduction in operational costs. This includes automating network planning, IT processes, and support functions, allowing companies to operate more efficiently and quickly. These improvements are becoming critical as telecom operators face growing pressure to roll out new technologies like 5G, maintain network performance, and reduce downtime.

In this article, we'll look at how Gen AI is transforming two major areas in the telecom industry: optimizing network operations and speeding up IT processes through automation. By using AI-powered solutions, telecom companies can improve network planning, accelerate software development, and reduce technical debt, positioning themselves for future success in a competitive market.

This move toward AI-driven operations goes beyond just improving efficiency—it's about reshaping how telecom operators manage their entire IT systems, enabling faster service delivery, lowering costs, and boosting customer satisfaction.

Network Operations Optimization

Telecom ...
... networks are growing more complex with the rollout of technologies like 5G and IoT, making efficient network management a critical priority. Gen AI offers telecom companies new ways to optimize network operations, improve capital efficiency, and reduce operational costs. One of the most impactful areas where Gen AI is being deployed is in network mapping and planning, where it can analyze unstructured data, streamline maintenance schedules, and optimize network resource allocation.

Network Mapping and Planning with Gen AI

Traditional network management relies heavily on manual processes and structured data analysis, which can be time-consuming and prone to human error. Gen AI, however, can process unstructured data such as supplier contracts, technical reports, and network component specifications to provide a comprehensive view of a network’s infrastructure.

For instance, a European telecom operator used Gen AI to automate its network mapping processes, reducing the time required for network audits and assessments by 40%. By leveraging AI’s ability to analyze vast amounts of unstructured data, the operator was able to more accurately assess compatibility between network components, predict maintenance needs, and identify areas where operational planning could be improved. This level of insight is vital for preventing costly network outages and ensuring optimal performance during peak usage times.

Read More: https://www.frameoutlook.com/cxo-viewpoint/how-are-telecoms-saving-millions-on-network-operations-and-it-these-ai-use-cases-show-you-the-way-nid-671.html

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