AI-Powered Service Trends Reshaping the Telecom Industry

Telecommunications customers expect fast, personalised, and seamless service. If they don’t get it, they’ll change providers in a heartbeat. It’s that stark reality that has providers scrambling to meet those expectations – while also creating more and more efficiencies with an eye on profitability. Artificial Intelligence (AI) is at the heart of this future of customer service in telecom, made clear in our recent industry-focused analysis of the Sixth State of Service report.

Whether dealing with service interruptions, billing questions, or plan management, today’s customers expect their provider to treat them like a person and not just another number. That not only means quick solutions, but also personalisation across all communication channels so they don’t have to repeat information whether talking to a chatbot or human representative. 

But AI in telecommunications isn’t all that revolutionary; it’s been a thing for some time now. Nearly 60% of telecommunications service organisations have fully implemented AI, according to the report, with 77% planning to increase their investment in the technology over the next year, it’s apparent that it will continue to shape the industry in years to come. There are also still questions left to be answered, including how AI will be used and the extent to which companies have undergone the critical step of integrating their data. The following is a look at the state of service in the industry, how AI is creating better customer experiences to meet rising expectations, the challenges that exist with data integration, and what the future holds (hint: autonomous, purpose-built agents). 

How rising expectations for customer service in telecom are leading to AI solutions

Downtime or service issues can create significant customer frustration – especially when it comes to a lost or slow connection. And when you’re without an internet or phone connection, you want an immediate resolution and a level of personalisation that doesn’t involve being transferred between multiple reps or repeating the same information over and over. As a result, the stakes are high for the industry: 88% of customers say that good customer service increases the likelihood of making repeat purchases, and in telecom, that loyalty is critical. Failing to meet these expectations means customer churn. 

Telecom service reps, however, aren’t always set up to succeed. They are tasked with managing a wide array of products and services, often with a complicated toolkit of systems and processes that may not provide a complete view of the customer. Reps are now also expected to be revenue generators; 61% of industry service organisations are expected to contribute to revenue more this year. This reality has yet to be fully realised. In fact, 68% of telecom reps’ time is still consumed by non-customer-facing activities like administrative tasks and internal meetings. 

Automation of routine, manual tasks frees up service teams to handle more complex and meaningful tasks. To simplify the toolkit of systems and processes, telcos need to unify all customer data for the rep, so they can see usage data, network data and billing data into a single view that makes it easier for them to solve inquiries. For example, when AI-driven chatbots and self-service portals can deflect simple inquiries such as billing questions or service activations, reps can focus on high-value tasks such as resolving unique technical issues or providing personalized customer care. In addition, with AI analysing customer data in real-time, reps can also quickly offer valuable insights, such as product recommendations or upgrades based on previous interactions so reps can generate revenue in addition to resolving an inquiry.

Self-service, autonomous agents offer solutions at scale

The demand for self-service has also grown, and 56% of customer issues in the industry are now resolved through those tools, such as online help centres or AI-driven chatbots, according to the report. However, there are still challenges with self-service, particularly when problems are too unique for automated systems or when instructions are too complex for customers to follow. For example, the report says 70% of customers find some issues too complicated for a chatbot, while 74% of telecom companies report that their self-service materials are sometimes outdated. AI can mitigate these issues by providing intelligent recommendations rooted in the company’s knowledge-base for complicated problems and summarising customer interactions to create new, more up-to-date knowledge articles based on issues brought up during those inquiries. 

To take that a step further, autonomous, purpose-built agents can interact with customers in ways that prompt-driven chatbots cannot. Agents can communicate with a customer with natural language, as opposed to the rules-driven prompt-driven scenarios of a chatbot, analyse user or environmental inputs, identify tasks, and reason through solutions on any number of issues in a personalised and conversational manner. For example, an agent can answer a call from a customer inquiring about a service outage, immediately have a complete view of the issue and either let the customer know when it will be resolved or deploy a tech to the site of the problem all without involving a service rep. These types of interactions can also include anything from answers to billing inquiries to helping customers upgrade services. 

Data integration challenges still exist

Before realising this tremendous potential for transforming customer service in telecom, that success relies heavily on data integration. And there’s still work to be done, the report indicates. Only 40% of industry service professionals are completely confident in the accuracy of their company’s data.

Yet, it’s clear that unified data is critical. Top-performing teams are much more likely to have a complete view of customer interactions: 89% of reps have access to customer sales data, 90% have access to marketing data, and 91% have access to past service interactions. On underperforming teams, those numbers are 76%, 64%, and 67%, respectively. And 89% of service professionals say better access to data from other teams would improve the support they provide. 

Having a high performing, AI-powered service team is intertwined with the quality and trustworthiness of the underlying data. Ensuring that data is accurate and complete is a necessary investment for the payoff of high-quality insights. The work to create a data foundation at the outset is the necessary first step when it comes to any AI initiative.

AI is critical to the future of customer service in telecom

These findings underscore the transformative impact of data and AI on customer service in telecom. To reduce churn and improve service through personalisation, using these technological advancements is critical to ensuring teams remain competitive and responsive to customer needs. Continued investment in AI – especially considering the next level of autonomous agents that can take the customer experience at scale to the next level – is the future of customer service in the industry.