Artificial Intelligence in Telecom

In today ’ s digital world , things are getting smarter , more connected and more sophisticated . A major role in this evolution plays innovative technologies , especially artificial intelligence . It is predicted that the AI - based solutions in the telecommunication market will reach up to 1 billion U.S. dollars by 2023 globally. Sounds impressive, right? Network solutions that can be driven autonomously are in great demand in the telecom sector that makes it a key driver for artificial intelligence growth. AI usage in the telecommunications industry helps companies to boost growth and revenues , while also opens up unique opportunities to improve the customer experience , enable self - service , improve equipment maintenance, and reduce operational costs. According to the recent stats, 63 . 5 % of the telecommunication companies started to invest in AI - powered solutions . The reason is the development of highly personalized products , improved fulfillment processes and enhanced network management. Let ’ s delve into details and find out how modern telco companies use AI - driven solutions today ?

AI Use Cases in the Telecommunications Industry

Below we have outlined key areas where artificial intelligence is changing telecommunications industry. Let’s delve into details below:

Virtual assistants and customer service

Undoubtedly , customer service is an essential component in any industry , and the telecom industry isn ’ t an exception . Several customer actions require specific support from the staff . Whether customers want to change bill plans , have difficulties in making payments or raising complaints . Intelligent virtual agents powered by AI technology are gaining traction in the telecommunication and helping to increase or replace human call centers . According to a recent survey , virtual assistants allow telecom service providers to save 1 . 2 billion U . S . dollars on customer services and support . Not only can companies to optimize a variety of support requests for billing inquiries , maintenance , etc , but also AI - powered assistants can solve all service - type questions and process transactions fast and efficiently . Other examples of AI usage in customer service / support are the following :

• contact center optimization ;
• customer voice and text analysis ;
• knowledge portals and AI assistants for the staff .

Robotic Process Automation ( RPA )

A variety of challenges currently faced by telecom companies can be addressed by RPA solutions . When implemented successfully , RPA can provide companies with a huge variety of robot helpers . Not only can RPA solutions help to minimize pressure on humans by freeing up time to focus on revenue generation , but also they deliver better customer experience and high - quality services as well . In addition to that , RPA allows network teams to discover faults faster , better deliver and maintain service quality , retrieve data for revenue forecasting , decision making and planning . Only by automating business processes through RPA can repetitive and time - consuming operations and tasks be done more accurately and more efficiently .

Better monitoring and management of networks with artificial intelligence systems

Adopting software - defined networks ( SDN ), network function virtualization ( NFV ), cloud - based applications , and 5G technologies can be done thanks to AI technology . Only by incorporating AI into network automation platforms can companies in the telecom environment deliver efficient and timely management operations . AI - powered solutions can support network operations to identify problems , such as Service Level Agreement ( SLA ) faults and breaches , diagnose root causes , correlate across multiple event sources , detect false alerts , etc . What's more , AI - based systems can predict and identify anomalies or network problems that helps companies to proactively take measures before problems arise . Also , AI is really helpful in predictive maintenance . Telecommunications services providers may face downtime that is a disaster for them . AI - powered solutions can identify patterns indicating a failure in the equipment ’ s routine maintenance checks that allows companies to take proactive actions before any downtime occurs . Let ’ s take a look at examples of network - centric applications powered with AI :

• anomaly detection ;
• performance monitoring and optimization ;
• prediction of network faults ;
• network capacity planning ;
• dynamic scheduling and resource optimization .

Artificial intelligence to detect frauds

There is a great number of users in the telecommunication environment that makes it attractive for fraudsters and thefts . The fraudulent activity involves theft or fake profiles , illegal access , cloning , behavioral fraud , etc . that has significantly impacted the relationship between a telecommunication service provider and a user . Only by using smart machine learning ( ML ) algorithms to a wealth of data retrieved from customers and operators can help providers to define the “ normal ” behavior and prevent fraud . Mentioned above algorithms learn how " normal " activity looks like and define the anomalies quicker than humans . These algorithms are highly sophisticated and can provide a real - time response if there are any suspicious activities .

The data-driven approach in decision making

Retrieving and processing terabytes of customers ’ data can be tedious and time - consuming for any industry , especially for telecoms . Thanks to AI and ML-driven solutions , companies can elicit meaningful data and provide business insights that helps them to make better decisions in business . What ’ s more , received data help with customer segmentation , churn prediction and prevention , increasing margins , optimizing prices , and so on . To sum up , applying artificial intelligence and machine learning-driven solutions , the telecom landscape generates insights and extract conclusions from the vast amounts of data . Not only can that help them to resolve issues and business problems , but also companies manage daily processes more efficiently and deliver enhanced customer services . Moreover , the adoption of AI and machine learning ( ML ) is essential for the survival of the company and its ability to outperform competitors .

AI Applications in the Telecom Industry

Below you can read how companies implement high - value use cases that transform the telecommunication sector .

• Telia : this company applies AI and ML - powered technologies to detect the most valuable accounts based on available data , keeping the company ’ s database always up - to - date . Moreover , the company has implemented virtual assistants to deliver better customer services and has saved up to € 1 million .
• Vodafone : incorporating virtual assistant app TOBi , company has improved customers ’ engagement and delivered more unique sales journey . An intelligent assistant solves the problems customers face by answering FAQs , suggesting and offering products to meet customers ’ needs .
• China Mobile : implementing AI - powered solutions , the company better identifies frauds by detecting anomalies and fraudulent activities , distinguish them and prevent fraud .

Final thoughts : Is your telecom company powered with AI ?

With the deployment of new services and associated complexities , artificial intelligence has become increasingly crucial for the telecom industry . Not only can AI - powered systems learn quickly and autonomously to optimize the network architecture , control , and management , they also exclude workforce repetitive operations , detect critical cyber - attacks and meet customer expectations . Reshaping the telecommunications industry , AI provides numerous advantages for telecom companies of any size by eliminating overload and efficiently dealing with customer inquiries . In addition to that , intelligent AI - driven virtual assistants deliver convenient and personalized services that significantly improves customer satisfaction . Don ’ t hesitate to develop and implement AI - based systems to maximize efficiency and drive business growth.telecom