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AI within telecom – Automatic, Adaptive, Autonomous

Everything that was ever created in the previous 150 years will be reinvented leveraging AI within the upcoming decade and a half. This is a quote by Randy Dean, Chief Business Officer at Sentient Technologies. 

Presently, we are dwelling in a planet of ubiquitous connectivity. Stuff around us are getting quicker, intelligent more connected, and even more digital, on an ongoing basis. It’s expected to play a significant role in this evolution, alteration of both consumer and developer behaviours has been played by the telecom industry. 

Artificial intelligence (AI) is identifying its usage in quite an array of industries, the telecommunications segment persists to be the leader. A massive number of telecom operators have begun experimenting through deployment of AI-driven solutions in both business-to-business and companies’ internal procedures and processes. 

Going by Tractica, the telecom domain is forecasted to invest $36.7 billion yearly in AI software, hardware, and services. 

The telecom industry encounters presently an array of challenges connected to growing market demands and economic pressure. 

With millions of subscribers and a growing number of telecom products, present day communication service providers (CSPs) have to invest a ton of effort and resources in the pursuit of optimizing the operational support services. As the telecommunications domain grows its networks at a swift pace, service configuration, customer care, and billing process becomes more complicated. Facing escalating client demands for improved quality services, CSPs seek useful innovations and applications on an ongoing basis to furnish their clients with improved client experience and service. 

Another dominant challenge for the telecom domain is the advance of the newest wireless networks like 5G (the fifth generation of wireless networks) and IoT (Internet-of-Things) that lead to a massive generation of humongous amounts of data. To effectively handle this data, CSPs are encountering an escalating requirement for data-driven solutions. 

As an outcome of the swift growth and proliferation of IoT, a ton of new devices emerge on the market, which on one side contributes to the market growth, while on the other hand brings fresh challenges in terms of security. As several IoT devices are at risk for malware-carrying apps, fraud prevention has now turned the primary priority for the telecom domain. In order to safeguard personal data gathered from IoT devices, telecom providers require to consider opportunities that emergent technologies are offering. 

What is AI? 

Artificial Intelligence, shortened as AI, is a term, which garners a ton of hype presently. Essentially, AI is a branch of computer science that develops a system able to carry out human-like tasks, like speech and text recognition, learning, problem solving. Leveraging AI-driven solutions, computers can achieve particular tasks through analysis of massive amounts of data and recognizing in these data recurrent patterns. 

AI’s Role in the Telecommunications 

According to IDC, 31.5% of the telecommunications enterprises are mainly operating on utilization of present infrastructure and 63.5 are making investments in AI-based systems. 

The primary drivers for AI growth within the telecom domain is an escalating demand for autonomously driven network solutions. The networks of the telecommunications domain broaden at a swift pace, becoming more intricate and tough to handle. By leveraging AI-driven network solutions, CSPs can minimize network congestions and enhance network quality, thus improving the client experience. 

Market Research Future forecasts that, by 2023, international AI in telecommunication market will attain $1 billion, with 32% CAGR during 2018-2023. 

The telecom sector has been a breeding ground for AI-driven applications. In the opinion of Arjun Vishwananthan, Associate Director, IDC India: “AI is expected to have an impact in a multitude of spheres – the most critical being traffic classification, anomaly detection and prediction, resource utilization and network optimization, combined with network orchestration. Further, it will additionally help the mobile devices with virtual assistants and bots.” 

As an umbrella terminology, AI can be subdivided into differing technology segments, like machine learning, deep learning, natural language processing, image processing, and speech recognition. However, a core role in the telecommunications domain belongs to ML, deep learning, and NLP (Natural Language Processing). 

Modernization of telecom legacy systems 

Legacy systems are outdated apps that can no longer keep up the pace to meet their goals and function efficiently. Ongoing support of legacy systems is very labour-intensive, and a lot of money. According to Dell, in the course of the previous ten years, a considerable number of all apps leveraged by Fortune 5000 companies “run in legacy environments built 20, 30, even 40 years ago. Further, Dell specifies that a normal corporation spends between 60% and 80% of its IT budget simply to upkeep maintain current mainframe systems and applications. Substituting outdated ineffective systems with more efficient AI-based applications will assist telecommunications organizations optimize workflow and maximize profit. 

AI Use Cases in the Telecommunications Industry 


Telia Company AB is the 5th telecom operator in the European region with more than 20k staff members and over 23 million subscribers. It is existent in Sweden, Finland, Norway, Denmark, Lithuania, Latvia and Estonia. Application of AI and ML-driven technologies has facilitated the identification of the most valuable accounts on the basis of available data, keeping the organization’s database always updated. Further, the organization has included virtual assistants to its client services and claims in a case study that within the 1st month one of the chatbots has saved 1 million Euros in expenses. 

China Mobile 

The planet’s biggest mobile provider with a subscriber base in excess of 902 million, China Mobile Communications Corp, is harnessing AI-embedded and big data technologies for fraud detection. The organization has put forth a new product – a big-data based anti-fraud system, referred to as Tiandun – which is able to identify fraudulent activity, differentiate it from normal calls and intercept spam texts or calls. 


Vodafone Group is a British multinational telecommunications conglomerate with a client base in excess of 500 million customers. The organization has enhanced customer’s services with the arrival of its virtual assistant app TOBi. TOBi is able to improve client engagement and customize/personalize the sales journey. Being a text bot, TOBi can directly provide solutions to a majority of client questions, address problems, or suggest and provide more appropriate products. 


AI-embedded technologies can be an advantageous tool in the telecommunications industry. Implementation of AI by telecom entities having the outcome of the development of very personalized products, enhanced fulfilment procedures and improved network management, facilitates telecom operators to furnish their clients with more attractive service in addition to enhance client retention. 

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