AI-based Network & Design Automation for the Telecom Industry

Monday Minute

Transformation is nothing new for the telecom industry. In recent years, the telecom space has harnessed the power of AI (artificial intelligence) to address several key challenges – poor network management; lack of data analysis; excessive costs; and a crowded marketplace.

According to Valuates, the global AI in telecom market is expected to reach $14.99 billion by the end of 2027. What types of AI will help transform telco? Let us take a closer look on where organizations are seeing tangible results.


Machine Learning 

Machine Learning (ML) is a subset of AI which enables computers to learn without being programmed. It can be adopted to generate predictions and decisions on previous data – making it a competitive strength for a variety of industries, including telecom. At its core, with ML techniques, a machine is trained to analyze and interpret substantial amounts of data. For example, planners and designers, network operators, and engineering firms looking to adopt comprehensive fiber network planning tools can maintain full control over the resulting network design with software. Automation tools which aim to find the optimal design virtually autonomously can help optimize: 

  • Cabinet closure coverage and sizes 
  • Cable and duct routes 
  • Demand point connections by finding the right cost-coverage threshold per connection
Artificial Intelligence-based Network & Design Automation for the Telecom Industry

Network Optimization

AI has made significant contributions to the telecom space with regards to building self-optimization networks (SONs). These networks allow operators to routinely optimize network quality based on traffic information. More specifically, these networks are monitored by AI algorithms which play a key role in detecting and accurately predicting network anomalies. 


Predictive Maintenance

Another common use of AI in telecommunication lies within predictive maintenance. With advanced algorithms and machine learning techniques, finding patterns with historical data can more accurately anticipate hardware failures. As a result, telecom companies have become proactive while providing an overall boost to the customer experience.  

With AI in telecom, the entire process has become much faster and easier. Is it time for your business to consider and benefit from AI? 


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