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A collection of over 250 uses for artificial intelligence

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Automated network configuration and optimization

Introduction

With the technological advancement and integration of the digital world, the telecommunications networks are also experiencing pressure to develop and provide efficient services to the customers. Some of the issues that the industry grapples with include management of complex networks, quality of service and customer satisfaction. Two techniques that have been identified as having potential to solve these challenges include Machine Learning (ML) and Artificial Intelligence (AI) which offer automated network configuration and optimization. These technologies are capable of processing large data sets, predicting trends, and even make decisions based on the analysis of the data which is a great benefit for telecom companies.

Challenges

There are several issues that telecom companies face when it comes to managing their networks. The first one is the challenge posed by the network itself which is made up of several components, all of which are further subdivided into several sections with their own parameters. Also, the amount of data produced by such networks is vast and therefore difficult to process and understand. Another challenge is that there is always an expectation of high quality service since any downtime or service delivery issues may have severe consequences on the customers and the company. In addition, the enhanced pressure for faster and more reliable services also creates a burden on the telecom companies to upgrade their networks. Last but not the least, the rate of change in technology forces the telecom companies to upgrade their networks from time to time.

AI Solutions

These challenges are addressed by AI and ML solutions which automate the network configuration and optimization through application of artificial intelligence. These technologies incorporate the use of algorithms that are used to evaluate the large amount of information collected from the network and thus, are capable of identifying the correct patterns and trends that are likely to occur in the future. This enables the telecom companies to see future problems and solve them before they become dire, which in turns reduces on downtime and enhances quality of service. Also, AI and ML can help in setting up and managing the network with minimal human intervention thus saving on time and resources that would have been used in managing the network and thus enable organizations to attend to other strategic business tasks. Nokia and Ericsson are some of the companies that have integrated AI and ML in their networks to enhance efficiency and dependability.

Benefits

There are a lot of advantages of using AI and ML in the network configuration and optimization. The first one is to enhance the network performance and availability as these technologies are capable of predicting and solving the problems that may occur. This results to less service interruptions and therefore happier customers. Another advantage is that, AI and ML can handle many of the functions involved in managing a network thus reducing the time and resources needed to attend to other business needs. Also, AI and ML can help in understanding the behaviour of the network and thus enable telecom companies to plan for the right time to upgrade or expand the network. Last but not the least, these technologies can enable the telecom companies to keep up with the change as the world becomes more and more technological.

Return on Investment

The use of AI and ML in the network configuration and optimization is a great investment for telecom companies as it gives a high return on investment. These technologies can cut down the expenses that are incurred in the process of network management since a good number of the processes are able to be handled automatically and they can also cut down on the costs that are associated with service disruptions through anticipating and managing potential problems. Furthermore, the information gathered from AI and ML can assist the telecom companies in making better decisions on the upgrade and expansion of the network and thus be cost effective in the long run. Last but not the least, with the enhancement in network performance and reliability, these technologies can enhance customer satisfaction and loyalty which in turn enhances revenues.

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