Embracing AI across Service Platforms to Tackle Disruptive Technologies in Telecom

By Telecom Tech Outlook | Tuesday, May 12, 2020

Artificial Intelligence (AI) and Machine Learning (ML) have penetrated the mainstream of communication services. Highly customized over-the-top applications, superior connectivity modes such as 4G LTE and 5G, and the Internet of Things (IoT) have transformed the telecom landscape from top to toe

Fremont, CA: The telecom industry has always been directly affected by technological innovation and digital disruption. Over the last ten years, the telecom sector has undergone a very challenging period in terms of keeping up with disruptive technologies. The emergence of cloud computing and, more recently, edge computing has left telecom service providers with no choice but to rapidly revamp their infrastructure to keep up with the changing times.

Artificial Intelligence (AI) and Machine Learning (ML) have penetrated the mainstream of communication services. Highly customized over the top (OTT) applications, superior connectivity modes such as 4G LTE and 5G, and the Internet of Things (IoT) have entirely transformed the telecom landscape. With the emergence of this new technology, competition in the market has also risen significantly. Amidst the hyper-personalized, customer-centric, and often free OTT options, Communication Service Providers (CSP) also face the growing pressure of declining Average Revenues per User (ARPU), a key growth metric measured by industry analysts.

A recent study by Juniper Research study reveals that the total network operator investments on AI solutions are expected to reach USD 15 billion by 2024, five times more than the investment of USD 3 billion in 2020. Analysts at Juniper have identified network optimization and fraud mitigation solutions as the most highly sought-after AI-based services over the next four years. These solutions are also useful for automated network functionalities, including routing, traffic management, and predictive maintenance.

By 2024, North America and Europe are expected to account for over 40 percent of AI expenditure, even though they account for only less than 20 percent of global subscribers. The ever growing demand for operational efficiencies will become the key driving factor for network operators in these regions to increase their overall investment in AI over the next four years.

Rather than applying separate AI strategies for individual cases, network operators need to embrace a more holistic approach to AI integration across various service platforms. CSPs must leverage AI to unify internal data resources and encourage cross-functional insight sharing into network efficiencies to maximize the benefits of collaboration across internal teams.

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