The transformative role of AI in telecommunications

AI has emerged as a transformative force across various industries, and the field of telecommunications is no exception. 

Field and service operations account for about 60 to 70% of most telcos’ operating budgets, according to a report by McKinsey. On top of increasing costs, operators are faced with complex demands from customers and unprecedented data traffic. To stay ahead, operators need to invest in technology to optimise processes and increase customer satisfaction, such as AI tools. 

Intelligent process optimisation

AI enables network operators to optimise their infrastructure by automating various tasks such as network planning, resource allocation and performance monitoring. Machine learning algorithms analyse vast amounts of data to identify patterns, predict network traffic, and dynamically allocate resources, leading to enhanced network efficiency and reduced downtime.

Similarly, AI-powered chatbots and virtual assistants can be used to automate customer service in telecoms. Natural language processing algorithms allow chatbots to understand and respond to customer queries effectively. These virtual assistants can handle routine customer support tasks, such as billing inquiries, service troubleshooting and plan recommendations, freeing up human agents to focus on more complex issues.

For example, the popular ChatGPT can be employed by operators to provide personalised responses to customers and translate text in different languages in no time. On top of it, ChatGPT can boost marketing efforts by analysing customer behaviour and generating preference-based leads. The tool can further assist telcos in forecasting sales and identifying growth opportunities by providing insights into future demand. 

Predictive Maintenance

On top of improving customer service, AI can also help telco companies schedule required maintenance. AI-based predictive maintenance models utilise data from sensors, network logs, and historical maintenance records to predict equipment failures before they occur. By proactively identifying potential issues, operators can schedule maintenance activities, minimising downtime and improving service reliability.

Data-drive insights can help proactively fix problems with communications hardware, such as mobile masts, power lines and even set-top boxes in customers’ homes. In data centres, AI-based solutions can analyse temperature data from network equipment to predict when a device is overheating and likely to fail. 

Network security

Telecom is one of the most vulnerable industries when it comes to fraud, and suffers high financial losses due to breaches in cybersecurity systems. According to TechSee, 90% of operators are targeted by scammers daily, accounting to billions in losses every year.  Conventional telecom security solutions only identify commonly occurring issues but fail in detecting or forecasting potential future threats.

Machine learning algorithms help analyse network traffic patterns, detect anomalies, and identify malicious activities, enabling operators to respond swiftly to security breaches. AI-powered security systems continuously learn from new data, improving their ability to detect and prevent emerging threats.

The integration of AI into the telecommunications industry has opened up new avenues for network operators and data centre owners to improve their operations and deliver superior services. From intelligent network management to predictive maintenance and enhanced customer service, AI offers a range of applications that optimise efficiency, improve network performance, and reduce costs. As the telecommunications landscape continues to evolve, AI will play an increasingly vital role in shaping the industry's future.

Marcin Bała is CEO of telecommunications networks specialist Salumanus, which focuses on fibre optic networks. Customers include big network operators, data centres, public utilities and system integrators.