3 Applications of AI and Machine Learning in the Telecom Industry

Machine learning and AI have proven to be the next disruptive force that every business needs and the telecommunication industry is not getting left behind. Telcos are at the forefront of the tech revolution and digital transformation to widen their services while improving consumers’ quality. 

In a world where consumers increasingly demand top-quality products and services, communication service providers turn to artificial intelligence and machine learning to help the companies deliver and fulfill their customers’ expectations. 

Here are the three main ways that machine learning and AI are revolutionizing the telecom sector: 

Customer Service and Operational Support 

Customer support has always been the Achilles of telecom companies. Companies often make it difficult for users to access customer support platforms like online chat, phone numbers, and contact forms to reduce user complaints. 

If the customer is lucky and connects with a customer care representative, they don’t get the answers or assistance they seek. 

Customer support challenges start with having a limited number of people operating the phones and chats compared to the influx of customer complaints and requirements. 

Using machine learning-based chatbots, telcos can comprehensively solve this serial problem. Chatbots are available 24/7 and can help customers quickly access the information they require using a ticketing system. 

NLP-based chatbots can take customer service further by interpreting the meaning behind the customer’s words. For example, using the customer’s tone and word choice, the bot can determine if the customer is frustrated or angry. 

Modern chatbots can also use machine learning algorithms and NLP to analyze historical information, networking logs, server ticketing data, and real-time customer input to deliver an amazing customer experience by effectively solving the customer’s problems. 

Chatbots can also play a role in on-site maintenance, reducing the need for technical visits while cutting back on business costs. 

Network Automation and Optimization 

Modern communication networks are complicated and challenging to manage. With the 5G network’s introduction, these two parameters are bound to get even more difficult. However, the deployment of ML technologies and others like SDN can help operators leverage advanced automation in their network operations to optimize network architecture and improve management and control. 

ML and AI systems can predict and identify possible network-related issues and apply fixes that optimize reliability using the network and device data. 

AI, NLP, and ML can use various data parameters collected from the customer and their devices like requests, complaints, and service logs and analyze them to help telecoms uncover trends and performance issues in different demographics, time zones, devices, and locations. 

Predictive Maintenance 

Predictive maintenance is another top area where AI and machine learning could help telecommunications companies improve service quality and reliability. Using sophisticated algorithms and machine learning ability, the companies can forecast future results by building historical data. AI systems can then use various data-driven techniques to monitor the current equipment condition and predict possible failure based on previous patterns. 

Using this information, telecoms can proactively fix various issues, including data center services, cell devices, and even devices placed in their customers’ homes. 

Telecoms can use AI and machine learning to use these capabilities across hardware, cloud, open-source frameworks, and neural networks. Ultimately, that means providing customers with a more reliable and stable network that guarantees improved customer experience and retention. 

As machine learning and AI develops in the telecom sector, their applications and benefits will broaden. 

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