AI is Streamlining the Telecom Industry in 3 Ways

By CIOReview | Tuesday, July 23, 2019

Telcos are leveraging AI to process and analyze massive volumes of data to gain actionable insights and offer better customer experience.

FREMONT, CA: The Telecom industry is heavily deploying artificial intelligence (AI) to optimize its workflow and processes. The industry is at the center of technological growth, driven by mobile and broadband services in the internet of things (IoT) devices. The rise is expected to continue as Technavio has estimated that the global telecom market will touch an impressive CAGR of greater than 42 percent by 2020 with the help of artificial intelligence (AI).

AI Provides Added Values to Telecom

Currently, communications service providers (CSPs) are encountering higher demands for better service qualities and better customer services (CX). Telcos are matching up with these demands with the help of vast sets of data collected over the years through their massive customer bases. The data is extracted from devices, mobile applications, networks, geolocation, and detailed customer profiles.

Telcos are also leveraging AI to process and analyze massive volumes of Big Data to gain actionable insights and offer better customer experience. AI is also becoming crucial for streamline operations and increase revenue through new services and products.

Future-centric CSPs have dedicated their AI investments on the following main regions:

Network Optimization

AI plays a vital role in building self-optimizing networks (SONs) that provides the operators with the capability to automatically optimize network quality as per the traffic information by time zone and region. AI application in telecom industry also employs advanced algorithms that search for patterns within the data sets. It enables the telcos to identify and predict network anomalies and allows them to deal with issues even before the consumers are affected proactively.

Check Out : Top Telecom Analytics Companies

Predictive Maintenance

Operators can use data-driven insights to observe the state of equipment, identify failure based on patterns, and proactively fix them with the help of AI-driven predictive analysis. It also leverages historical data for the deduction of future results. In other words, network automation and intelligence allow better root cause analysis and estimation of situations. In the longer run, the technology will support more strategic goals such as dealing efficiency with emergency business needs and creating new customer experiences.