Telecommunications Industry is Evolving with Artificial Intelligence

The telecom industry is no longer limited to providing primary phone and internet service. It is at the epicentre of technological growth, led by mobile and broadcast services in the internet of things (IoT) era. This growth is expected to continue, with Technavio estimating that the global telecom IoT market will post an impressive CAGR of over 42% by 2020. The driver of this growth is artificial intelligence (AI).

AI has helped the telecom sector redefine customer experience, bringing new opportunities but also complicating business models. Here are some ways that AI is contributing to the telecom industry.

AI for Network Optimisation

Artificial intelligence applications in the telecommunications industry help CSPs create self-optimisation networks to improve customer satisfaction and prevent outages. As AI can help networks adapt and reconfigure as per customer needs, they can offer consistent service more proactively.

AI for Predictive Maintenance

AI-powered predictive analytics is helping telecom industry provide better services by utilising data, sophisticated algorithms and machine learning (ML) techniques to speculate future results based on historical data. It means operators can use data-driven insights to monitor the state of equipment, anticipate failure based on patterns. It also can proactively fix problems with communications hardware like cell towers, power lines, data centre servers, and even set-top boxes in customers' homes.

In the short term, network automation and intelligence will enable better root because of the analysis and prediction of issues. These technologies will underpin more strategic goals, such as creating new customer experiences and dealing efficiently with emerging business requirements in the long run.

Identifying Fraudulent Activities

AI also makes use of advanced algorithms to identify and predict any network anomalies. In the context of cybersecurity, it means giving businesses the ability to detect cyberattack in advance. Additionally, the cutting-edge technologies considerably minimise response time, enabling telecom businesses to thwart the threat before it exploits internal information systems.

Many organisations store client's financial information away from the network, so user information is not compromised in case of a cyberattack. Around 61% of enterprises say that it is impossible to identify breaching attempts without AI technologies, wherein 48% say that the allocation of their annual budget toward AI in cybersecurity has increased by an average of 29% in 2020.

RPA for Telecommunications

CSPs have immense numbers of customers engaged in millions of daily transaction, each susceptible to human error. Robotic Process Automation (RPA) is a form of business process automation technology based on AI. It can bring greater efficiency to telecom functions by allowing them to more easily manage their back-office operations and large volumes of repetitive and rules-based actions. RPA frees up CSP staff for higher value-add work by streamlining the execution of complex, labour-intensive and time-consuming processes such as billing, data entry, and workforce management and order fulfilment.

A survey by Deloitte reveals that nearly 40% of telecom, media and tech executives say they have garnered substantial benefits from cognitive technologies, with 25% having invested USD 10 million or more. Over three-quarters expect cognitive computing to transform their companies within the next three years substantially.

The Future of AI in Telecom

AI applications in the telecommunications industry are increasingly helping CSPs manage, optimise and maintain not only infrastructure but also customer support operations. Network optimisations, predictive maintenance, and RPA are all examples of use cases where AI has influenced the telecommunications industry, delivering enhanced CX and added value for enterprises.