The telecom industry is no longer restricted to the provision of basic phone and internet services. Led by mobile and broadband services in the Internet of Things (IoT) era, it is now at the epicentre of the digital revolution.
The Need For AI and ML in Telecom
Faced by the fast-changing consumer needs for quality services and better customer experiences (CX), communication service providers (CSPs) are harnessing vast amounts of data. This data has been collected over the years through devices, networks, mobile applications, geolocations, detailed customer profiles, services usage and billing data. Telecom giants are using this data through AI in four main areas: Network Optimization, Preventive Maintenance, Virtual Assistants and Robotic Process Automation (RPA).
As per a study by Gartner, connected devices will grow to 20.4 billion worldwide from 2020. This is leading more CSPs into jumping on the bandwagon to deliver tangible business results in the telecommunications industry at lower costs through AI & ML.
Benefits of AI and ML For the Telecom Sector
Multi-dimensional insights: Telecom companies can build high-granular insights into potential consumer margins by combining big data with enterprise resource planning, operations support system and business support systems.
Network Optimization: AI applications can find patterns within the data through advanced algorithms. They help telecoms detect and predict network anomalies and also allow the operators to proactively fix problems before they impact their customers. Neural networks and ML can also detect malicious codes and other cyber threats in the telecom traffic.
Predictive Maintenance: Telecoms can use sophisticated algorithms and ML to monitor the state of equipment, predict failure based on data patterns and fix problems with communications hardware, such as cell towers, power lines, data centre servers, etc. Telecom giant, AT&T has deployed AI to support its maintenance procedures.
Maintenance of Mobile Towers: CSPs have to periodically inspect their on-site infrastructure and equipment. CSPs may plant surveillance cameras powered by AI for video analysis. It can also be used to predict and alert events such as fire, intrusion, etc. in real time. The combination of ML algorithms and IoT sensors at the towers can be used to analyze the data and provide 360-degree monitoring analysis. This can also help the service providers deploy necessary systems for repair of spare parts and materials, inspections, or maintenance.
The Way Ahead
AI and ML can help revolutionize the telecom industry through classification of traffic, anomaly detection and network optimization and utilization. The sector can also gain through self-learning networks which configure themselves to optimum conditions. They pare down costs and also scale up the efficiency of service. However, the biggest challenge that CSPs face is the lack of data and difficulty in accessing it.
In a nutshell, AI and ML are set to disrupt the telecommunication industry. The industry needs to embrace this change and combine the knowledge from electronics and IoT with ML and AI to harness the new age digital transformation.