A look at how AI is used in the telecom industry
This is the age of information, and it is driven by the Telecommunications industry. AI and Telecom are uniquely suited to each other

A look at how AI is used in the telecom industry

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Despite the enormous amount of hype generated by Artificial Intelligence, the technology is fast becoming indispensable to most industries. This is the age of information, and it is driven by the Telecommunications industry. AI and Telecom are uniquely suited to each other, given that the telecom industry is already dealing with big volumes of data, which is what drives AI.  

Why the sudden interest in AI/ML in telecom?  

The potentialities of AI and Machine Learning in transforming telecom have been under discussion since 1993. The recent resurgence of interest is due to the fact that the industry is faced with increasing challenges in providing services. Network technology is becoming more complex due to rapid technological innovations.   

The requirements of the latest wireless networking systems are complex and diversified in nature. These days we have so many applications for so many services. We have all kinds of devices like phones, laptops, and tablets. We have a choice of networks, and we need access even in remote villages. Connectivity is an important commodity to people of every walk of life.   

Gartner’s report says that there will be 20 billion connected devices (not including phones and PCs), and Cisco predicts 50 billion connected devices across all sectors in the world by 2020. With all these complications and the release of 5G on top of it all, telecom companies will crumble if not for the helping hand of AI.   

More than 50% of network providers will have actively adopted AI by the end of 2020. AI drives the automation of processes and optimizes them. Customer experience, network stability, and reliability and maintenance are just a few of the areas in which AI finds application. Predictive Analytics and Machine Learning work with the huge datasets that the telecom company provides to offer clear insights for improving the efficiency of processes. They identify threats or errors and engage in timely corrective actions.  

Potential use cases of AI in telecom

The uses of AI in telecom are myriad; however, we discuss seven major ones below.  

Network operations monitoring and management  

With people spending more and more time in the virtual world, the demands for innovative networking are increasing. The efficient automation of networks with AI is a must to provide timesaving, smoother operations. 

AI and ML together tackle many functions at the operational level, notably anomaly detection. Performance is monitored, analyzed, and optimized constantly. With unsupervised learning technologies like clustering, systems can be taught to deal with alarms. With end-to-end monitoring, risks, or faults which might escape human detection are identified and reported, and they are addressed and resolved automatically, without human intervention. Predictive Analytics helps to plan network capacity requirements using congestion predictions.

In the mobile context, AI can be applied at the core, at the RAN level, and end-to-end.  

Predictive maintenance   

Predictive maintenance is an important area of AI application in telecom. Real-time and historical data are analyzed to gauge network performance and understand which services are functioning well, and which are failing. Companies around the world put predictive maintenance at the top of their priority list, even ahead of security and management.  

Fraud mitigation 

Fraud detection and prevention are major functions of AI and ML in telecom. Frauds cost telecom companies billions of dollars’ worth money every year. 

Cybersecurity 

Innovations in networking mean hackers need to come up with insidious ways to attack cybersecurity. Traditional security technologies are fast becoming redundant. AI algorithms have been used for many years to deal with problems of this type. The algorithms are trained to detect scrupulously in the unlikeliest quarters for threats. Internet of Things (IoT) devices are being managed better through baselining the behavior of connected devices, thanks to AI. 

Customer service and marketing  

AI facilitates virtual engagement with customers using chatbots and IVR technology. AI in knowledge portals and assistant bots help to augment human resources. Customer relations and management is optimized, and customer voice and sentiment analytics help to provide better insights to enhance performance. 

Intelligent CRM systems 

Promotional campaigns can be based on data provided by AI. AI helps in identifying new opportunities for business, and possibilities for cross-selling or up-selling. Predictive analytics provides insights into changes in customer behavior and the mitigation or expansion of their base. 

CEM  

Customer Experience Management (CEM) is the key for telecom service providers to ensure the retention of existing customers and attract new ones. AI plays an important role in helping telecom companies to track and oversee all interactions with customers. This helps them to understand the performance of their network and the quality of services provided by them, such as billing and complaint redressal.  

Top 10 AI-powered telecom companies in the world 

Many telecom companies in the world have successfully adopted AI. Below are the top 10 of them: 

AT&T 

The company has been working with AI for many years. It has successfully adopted AI for customer care services, networking operations, and management and for security purposes. The implications of the 5G network have also been addressed by the company through its ML innovations. It launched the Acumos project to build AI projects more efficiently. 

Colt 

Colt has developed a project called Sentio, which is in proof of concept stage (PoC). Their priorities are network optimization, network security, operations automation, and customer experience management. 

Deutsche Telekom

Deutsche is developing AI solutions in-house in areas of customer service and experience management. It has its own teams of experts to design these solutions. It has developed chatbots such as Vnada, Tinka and Sophie. eLIZA is their AI program that links all the AI solutions within their group. 

Globe Telecom 

Globe Telecom has implemented AI in all three main spheres of business: customer service, operations, and security. The company works with AI through The Forum Catalyst Program.  

KDDI 

The Japanese telecom giant has been working with AI-assisted automated operating systems for a few years now. Their innovations in anomaly detection in NFV technologies are important breakthroughs in the onward journey into the 5G era. 

KT 

South Korea’s KT entered the AI game with its announcement of the Neuroflow program, for network operations. The program is expected to be established by the end of 2020, and it has been made available to other companies as an open source. 

SK Telecom 

SK Telecom operates T Advanced Next Generation Operational Supporting System or TANGO. TANGO AI-assisted and deals with network operations using data analytics and ML. Indian operator Bharti Airtel has struck a partnership deal with SK Telecom for the use of TANGO. 

Swisscom 

Swisscom has developed chatbots through Deep Learning, namely Cosmos and Marmo, for optimizing customer services. 

Telefónica

Telefónica uses a voice-activated assistant called Aura for enhancing user experience and interactions. Apart from this, the R&D teams of the company are actively involved in identifying use cases for AI and ML in networking and operations and have published many academic papers on the subject. They are also using AI for anomaly detection and predictive maintenance. 

Vodafone 

Vodafone’s chatbot TOBi is the first live one to be released in the UK market. Vodafone is also collaborating with Amazon on software for Alexa. The company is also experimenting with ML for network automation.  

Conclusion  

The adoption of AI in telecom is happening slowly but surely. AI offers many benefits and considerable value in addition to business. The future looks promising with more and more companies going the AI route.

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