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Artificial Intelligence - The opportunities for Mobile Operators | NETMANIAS

Technology, in general, is continuously evolving, creating a challenge for CSPs to cope with the versatility demand of the market without exploring the latest technologies from both technical realization and business perspectives.

ML can study the data and inputs from previous years and build a model that predicts the traffic forecast helping the company to set the exact budget for expansions.

behaviors to be able to dynamically identify any unusual pattern that can be considered as a fault or a potential problem and trigger other systems to perform preventive maintenance actions.

building a model for each traffic stream identifying patterns that map to degradation in user experience such as the silent period in a VoIP call.

Touching the main business strategies, Marketing differentiation is where ML enables the DSPs to offer unique innovative services especially in the B2B domain where marketplaces and upsell recommendations are governed by ML.

The second common direction is the Focus on new segments and verticals and this is enabled by the wide variety of use cases that ML/AI brings to many verticals such as Medicine, Agriculture, education, etc.

Also, understanding the market trends via ML helps to stop spending money on unsuccessful products thus focusing on the exact market requirements and trends.

Each functionality in the ML pipeline is defined as a node as per the below definitions In the next article, I will start to put more practical use cases and define potential relations between the new logical functions and 3GPP/ETSI Standard Functional Blocks.