Telecom companies leverage AI across a variety of use cases to improve operations, enhance customer experience, and develop new services. Understanding the role of AI in improving profitability and consumer satisfaction will be a key component of any successful Telco in the future.

Customer-Facing AI Use Cases

Let’s look at some customer-facing ways that will change the way subscribers interact with their service providers.

Customer Contact Intelligence – most companies, including telcos, can benefit from AI-led chatbots that either provide a self-serve point for customer service or assist live agents in helping customers. In addition to gathering information and finding solutions, AI can aid in language translation and post-call analysis.

In-Store Sales Assistance – by making sales staff less dependent on training, and more dependent on AI, they will be able to provide better solutions and offers to customers through centralized sales intelligence and product knowledge. This will also reduce the training time for sales staff, and make the entire sales process more efficient.

Technical Support – Support representatives assisted by AI will be able to offer better and faster solutions when customers experience problems. Getting customers back onto their devices and using services faster increases overall satisfaction and gets service usage back on track quickly when a subscriber has a problem.

Improving Internal Telco Processes through AI

Now that we’ve reviewed some customer-facing AI use cases, it’s important to look at how Telco’s can implement AI in internal processes to help innovate faster, become more efficient and provide improved customer service.

1) Develop Apps and Services Faster

Telcos have large teams of developers to build multiple in-house services and applications. By optimizing developer efficiency, tasks can be completed faster so that AI can output more lines of code suggestions and lines of code. This can translate into faster time to market and/or the ability to create new products without hiring additional coders.

2) Faster and Smarter Network Planning

Using geographical information, population density and existing infrastructure, AI can streamline the network planning process. This allows the telco to plan infrastructure and network capacity accordingly.

AI can also assist in identifying the best location for new cell tower construction based on population growth trajectories, terrain and signal coverage analysis.

3) Network Optimization
AI can analyze network traffic patterns and reroute data to less congested paths. This traffic optimization ensures smoother network performance and minimizes latency. Monitoring signal strength and coverage across cell towers can assist in identifying areas requiring optimization. With an eye of reducing operational expenses, AI can identify areas where network resources can be optimized and automatically adjust.

In addition to network optimization, AI can also help in other areas of the business. By analyzing customer data, a more personalized experience can be presented to customers by recommending services based on the customer’s usage patterns. AI can also identify customers who are at risk of leaving and take proactive, predefined steps to retain them. And finally, AI can review customer feedback for sentiment analysis which could lead to identification of areas for improvement.

4) Deployment Automation
AI algorithms can analyze how data flows within the network and automatically configure devices like routers and switches minimizing manual work. With AI’s assistance, many processes can be streamlined such as provisioning new services and service activation/configuration.

AI can also allocate network resources based on the type of use needed. For example, video streaming and gaming need high bandwidth with low latency. Known as network slicing, AI can dynamically optimize the network’s performance based on identified service requirements.

5) Observability and Anomaly Detection
AI can be used in tools to monitor network metrics like latency, packet loss and bandwidth usage. By analyzing cell tower signal strength data, AI can optimize cell tower settings to improve coverage and signal quality in specific areas. It can also be used to detect anomalies that are indicators of a potential problem.

Predictive maintenance is a large area where AI excels. Using historical data, AI can predict when network equipment is likely to fail so that proactive maintenance can be performed.

On existing networks, AI can predict future traffic demand in specific areas based on historical data. AI can also identify congestion points in real time and reroute traffic to reduce latency and improve network performance.

6) Diagnosis and Troubleshooting
AI can also quickly analyze multiple data sets from various networks to isolate the root cause of an issue. This can drastically reduce troubleshooting time. Analyzing sensor data from network devices can predict potential hardware failures. Those same data sets, along with customer feedback data, performance metrics and network devices can provide a holistic view of the network’s health.

7) Actuation and Healing
Once AI has detected an issue, it can also help in resolving it. AI can automatically issue alerts based on detected anomalies and even start pre-defined actions – such as restarting faulty devices – which minimizes human intervention and resolves issues faster. For example, AI can intelligently distribute network traffic across multiple servers to prevent overloading and to maintain an optimal level of network performance.

Choosing the Right Partners & Strategy

When implementing AI in telecommunications, it is important to note that AI training models are only as good as the data it ingests. High-quality network data is a must. It is also necessary to ensure that AI models are adapting to changing conditions which means the monitoring of network performance must be continual with feedback loops.

I would be remiss if I didn’t mention the importance of network security and data privacy. Implementing robust security measures is needed to protect sensitive network data and customer data from unauthorized access.

Today’s telcos are now applying their AI-led technology in areas that transform them from being mere telcos to technology companies. Many telcos are involved in smart cities, smart stadiums and doing so by providing their own compute power.

ECOBLOX has deep expertise in assisting telcos with high-performance computing power. Our data center projects bring low latency, high-performance computing power to locations where telcos need them. Our AI-led monitoring systems also assist telcos in optimizing computing performance – a goal of every telco.