AI in Telecommunication

The past several years have been tough for telecom operators: although mobile data consumption has increased massively, revenues and cash flows have dropped. This is because operators had to invest massively into their wireless networks while the growth of their customer base slowed down. While monetising the required communications infrastructure for telco operators is becoming harder, over-the-top content (OTT) such as music and video streaming brings gigantic turnovers to its distributors.

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Telecommunication Performance Drivers

Here are our top-6 performance drivers for applying AI & analytics in Telecommunication.

Call Centre Routing

Telcos can automatically route customers to the best service personnel available. This will reduce call centre costs massively and increase customer satisfaction as customer service will be faster and better adjusted to the customer’s needs.

Predictive Issue Identification

Telcos can identify potential issues and their root causes in the network or at customers’ access points to avoid long problem identification processes with service personnel. The service staff can focus on solving the customer’s problem instead of spending time finding the root cause.

Predictive Maintenance

Telcos can identify problems and outages before they occur. As a result, they can avoid long outage periods for their customers by predicting failures and sending service staff to fix the issues.


Telcos can identify likely churners and offers that will convince them to stay.

Customer Segmentation

Telcos can improve their customer understanding by identifying homogenous customer segments. This enables providers to adjust tactical and strategic decisions toward their customers' needs.

Store Segmentation

Telcos get transparency on their stores, identifying different types of stores with a similar profile. This will help them to derive a specific strategy for each sales location.


Telcos can optimise their pricing strategy by identifying their customers’ willingness to pay. Also, telcos can use competitive intelligence to adjust their prices and leverage local and temporal information to make prices dynamic. ​

Personalized Promotions

Telcos can customise offers to customers based on their needs. By understanding which promotions are meant for a specific customer, telcos can move away from mass communication to personalised interactions with their customers.

Branch Footprint

Telcos can find the ideal location for their next branch or decide which stores to close/merge.

Fraud Detection

Telcos can detect and avoid fraud through customers, such as customers not paying their bills.

Network Footprint Optimization

Telcos can find the ideal location for their next cell towers, making their massive investments most impactful.

How to identify Machine Learning Opportunities in your Telecommunication organization?

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The Telecommunication Challenge

Major advances in data analytics, artificial intelligence, and other technologies are changing the game in the industry. Mobile operators can achieve breakthrough cost savings and capital intensity while maintaining or even increasing their scale using new data opportunities. Digital technology can help them to streamline business functions and please customers, reducing costs and raising sales.

But digitization is not just a threat; it also offers telecom companies an opportunity to rebuild their market positions, reimagine their business systems, and create innovative offerings for customers. AI might indeed be able to transform the industry—but telcos will need to spark that revolution. Predictive maintenance, for example, can identify potential failures, enabling fixes before systems—and the services that customers depend on—fail. Machine learning allows telcos to identify patterns in a user’s browsing and purchasing histories and then suggest what’s known as the next best offer—the next product that is most likely to resonate with that customer.

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