Mobile network operators (MNOs) are increasingly relying on artificial intelligence (AI) to underpin their business models. Clever AI algorithms can design networks, improve customer service, streamline and automate business processes, and optimize network infrastructure.
AI-based applications will be a key driver of innovation in the telecommunications industry, particularly as it transitions to virtualized 5G networks. Along with fiber-optic infrastructure, 5G is set to accelerate the digitization of industrial services and processes, enabling rapid expansion of Internet of Things (IoT).
According to IDC, 63.5% of telcos are actively implementing AI to improve network operations. Moreover, by making it easier for operators to optimize and direct traffic in their networks, AI algorithms can help bolster cybersecurity defenses. Traffic can be redirected automatically using AI-assisted monitoring systems.
The ability to predict anomalies in the network also allows ops teams to perform predictive maintenance - solving problems before they occur. AI applications prevent device and system failures by predicting the future based on historical data. Investing in AI-based solutions to monitor wear and tear – and predict potential points of failure – has clear financial benefits.
AI and NLP (neuro-linguistic programming) programming can also be applied to analyze messages sent by customers to the call center, and notes made by call center agents, to improve quality of customer service.
Boosting network energy efficiency is another AI benefit. According to a study by Nokia and GSMA Intelligence, the vast majority of telcos see energy efficiency as the main driver of grid transformation. Survey respondents admitted, however, that they were still at an early stage of planning and testing AI in the field of energy efficiency. Even so, about half of survey participants said they expected energy savings of 10-20% in the next 2 years, when AI energy solutions become more widely available.
AI apps in telecommunications – at a glance
-
preventing failures of devices and systems before they occur (predictive maintenance);
-
optimization of network design and operation;
-
personalized digital interaction with the customer;
-
service development;
-
virtual assistants and chatbots;
-
mobile data analysis;
-
improvement of billing systems;
-
better resource allocation;
-
B2B sales optimization;
-
improving cybersecurity, including cyber fraud detection and prevention;
-
improvement of energy efficiency;
-
business process automation; and
-
robotic process automation).
No plain sailing
AI in telecommunications is not without its challenges. Unstructured and incomplete data is one difficulty, as is the need for additional technical knowledge and hiring AI specialist. Technical integration of AI projects is another challenge.
There are also some risks. AI relies on large amounts of data, often of individuals. It is important that AI algorithms are used in a responsible manner and protects fundamental human rights.
With this in mind, a group of MNOs in cooperation with the GSMA Association created the "The AI Ethics Playbook", which defines the principles of ethical use of AI. The GSMA and the European Telecommunications Network Operators' Association (ETNO) also welcomed the European Commission's initiative to propose AI regulation.
The rapid development of AI in the telecommunications market reflects the growing importance of this technology in the industry. Network operators who choose not to use AI mechanisms may have problems with efficient information processing and real-time data analysis, as well as large-scale business and technical decision making in virtualized next-generation digital networks.
