In a market bursting with disruptive new technologies, an increasing number of digitally native consumers and rising customer expectations, CX is king. There is a strong correlation between customer experience and retention — with recent findings from McKinsey indicating that there’s an overlap as high as 80 to 90 per cent in some markets.

A happy customer is a loyal one, but maintaining that satisfaction can be challenging. Customers who must chase down resolutions, face a difficult CX or are shuffled between agents are unlikely to stay loyal for long. In fact, one European telco that McKinsey spoke to discovered that customers who had to make two or more phone calls to resolve issues were almost twice as likely to walk away at the end of their contract.

Getting personal

Could AI by the resolution to telecom’s CX challenges? There are several potential use cases that could enhance customers’ experience with their network provider. We’re seeing increasing use of next-best-action (NBA) models that predict customer needs based on real-time data analysis, providing personalised recommendations across multiple channels.

By anticipating behaviours — like increased data usage or upcoming travel — NBA suggests relevant solutions, such as plan upgrades or new offers. Similarly, a provider could use an NBA model to offer plan adjustments based on usage patterns, providing customers with options better tailored to their needs. This proactive approach helps ensure customers are always on the best plan for their consumption, reducing plan wastage and enhancing overall satisfaction while increasing loyalty and retention.

NBA models have been available for many years; however, the integration of AI brings another level of efficiency in processing data and, most importantly, in interacting with customers. Historically, NBA solutions have struggled with delivering seamless, real-time engagement and contextual understanding during customer interactions. AI bridges this gap, enabling hyper-personalised, conversational experiences that drive deeper engagement and greater satisfaction. This evolution represents a game-changer in leveraging NBA models to deliver unparalleled customer experiences in the telecom sector

Problem solving

Offering new or upgraded services is certainly an encouraging AI use case — but it’s not going to improve CX alone. If a consumer is experiencing unresolved issues with their network, they won’t stay no matter what’s being offered.

Here, an NBA approach can work again. This time, AI-driven insights could detect potential problems before they turn into a complaint. For instance, if a customer checks their service speed and notices a slowdown, AI can instantly recognise this behaviour and trigger an automated response with troubleshooting tips or diagnostic tools. If network congestion is the cause, AI could notify the customer of temporary network issues and provide a timeline for resolution, reducing frustration and the need to contact customer support.

Similarly, AI can enhance the experience for a user-facing multiple failed or dropped calls. For example, if the system detects a pattern of call failures, it could automatically notify the customer, acknowledge the inconvenience, and provide an explanation for the disruption. To go a step further, AI could proactively offer compensation, such as a refund or credit for the dropped calls, restoring trust and showing a commitment to service quality. This kind of responsive and empathetic interaction helps transform frustrating experiences into opportunities to build loyalty and demonstrate care for the customer.

Optimising performance

However, to truly deliver excellent CX, improvement should not only be in reaction to customer activity. Telcos can also use AI to overcome issues behind the scenes, before they become visible to customers. Here, network congestion offers another interesting use case.

Ericsson’s mobile data traffic outlook reveals that total global mobile data traffic is forecast to grow at a CAGR of around 20 per cent through to 2029. This leaves the industry with a challenge: managing a huge increase in network traffic without compromising performance. AI could provide a promising solution with algorithms used to analyse network traffic in real-time, predicting congestion points and automatically rerouting traffic to ensure optimal performance. This can result in fewer dropped calls, faster internet speeds and a more reliable network.

Operators have already demonstrated that this approach works in practice, with examples including Vodafone’s implementation of AI to enhance network performance across Europe. Vodafone’s AI-based system monitors network traffic in real-time, predicting congestion and rerouting traffic to avoid bottlenecks. The network has claimed this approach increases network optimisation speed by over 45,000 per cent.

AI in telecom represents more than just a passing trend — it’s a transformative force reshaping the industry. By harnessing AI, telecom companies can optimise network performance, enhance customer experiences, streamline operations through automation and maintain a competitive edge. Looking ahead, AI’s role in telecoms will only expand, driving deeper connectivity, efficiency and innovation across the sector.

Want more insights into the developments shaping the telecommunications sector? Mobilise’s podcast speaks with industry experts to offer a go-to source for all things telecoms. Check it out here.