How AI Is Revolutionising Network CX for Telcos

When we think about customer experience (CX) in telecom, it often boils down to this: "Does the network work well when I need it most?" While CX spans many aspects, the network experience is undeniably at its core. Enter AI—telecom’s secret weapon to make networks smarter, faster, and more reliable.

In this article, I’ll give my thoughts on how AI is reshaping network management and enhancing CX, making telco services more seamless for everyone.

Let’s start though with a general comment on CX.

Differentiating CX Drivers in Telcos

While there are many facets to CX in telecom, network performance and commercial value are two critical components that AI can directly address.

When Network Performance is Good, but CX is Poor : If the network is stable but customers are still dissatisfied, the issue likely lies in commercial factors, such as pricing or perceived value. Addressing this requires a strategic response, like enhanced value offers or promotions.

When CX Suffers Due to Poor Network Performance : Discounts or free devices won’t resolve frustrations if the network fails to deliver. Instead, telcos must invest in optimizing the network experience to retain customers and ensure satisfaction.

AI-powered tools allow telcos to navigate these scenarios more effectively by leveraging data-driven insights and automation.

What AI Brings to the Table

Fixing Problems Automatically : Closed-Loop Automation

Imagine if your network could fix itself. That’s exactly what closed-loop automation does. Closed-loop automation, where AI systems can identify and resolve issues without human intervention, is a game-changer for network reliability

For example, Deutsche Telekom uses AI systems to monitor network health in real time. If a spike in data usage or a faulty connection is detected, traffic is rerouted, and the issue is fixed automatically. This ensures a smooth experience, even during high-demand events.

Planning Ahead with Predictive Insights

AI is like a crystal ball for network capacity planning. It analyses usage patterns and predicts where the next big demand will arise, helping telcos prepare in advance.

Take Vodafone, which uses predictive models to allocate bandwidth during peak periods. By identifying potential bottlenecks before they happen, they avoid congestion and keep users happy—even when everyone’s streaming their favourite shows at the same time.

Dynamic Network Adjustments

Networks don’t have to be static. AI enables them to adapt to shifting demands. For instance, China Mobile uses AI to adjust its 5G base stations based on user density. This means better connectivity when people gather at hotspots, like concerts or sports events, without wasting resources during quieter times.

Going Deeper : AI for Granular Analysis

One of AI’s superpowers is its ability to zoom in and out. It can analyse network performance from a city-wide level (macro) down to individual towers or devices (micro). This level of granularity allows telcos to identify issues with pinpoint accuracy. You cannot do this currently with the resources that you have without AI.

For example, SK Telecom uses AI to diagnose problems at specific sites. If one tower shows a dip in performance, the system investigates equipment faults or interference, ensuring issues are fixed quickly.

Root Cause Analysis : Finding the Needle in the Haystack

In operations, an important component is solving the problems that surface and then putting in measures which prevent it from re-occurring. This means, finding out the root cause.

As we all know, it’s not easy to find the answer to the final ‘why’. AI has changed that. With advanced root cause analysis (RCA), AI sifts through heaps of data to figure out what went wrong. Traditional methods often falter due to the scale and complexity of modern telco networks, where countless variables - hardware, software, and external interference interact simultaneously

AT&T uses AI-powered RCA tools to identify recurring issues; like misconfigured equipment or software bugs—by analysing patterns in network data. This means faster fixes and fewer disruptions for customers.

Making Networks Greener

Today, most businesses place emphasis on sustainability. As such, they want to reduce their carbon footprint. Telcos operate enormous networks, which consume a lot of energy. AI is helping make these networks more sustainable. For example, Orange uses AI to power down underutilized equipment during off-peak hours. This not only reduces electricity bills but also helps telcos lower their carbon footprint.

Conclusion

AI is transforming how telcos manage their networks, making them smarter, more efficient, and better at delivering a great customer experience. Whether it’s fixing issues on the fly, planning for future demand, or improving sustainability, the possibilities are endless. By integrating AI, telcos are not only improving operational efficiency and sustainability but also ensuring a more satisfying and reliable experience for their customers.