Call centre automation with AI

Gayathri Venkataraman

Have you had the experience of waiting over a phone, in a customer call centre queue, where the people keep bouncing you over and over from one person to another? I am sure we all know the pain of explaining our issues, order number or problems to one person after another before we find a solution for the same. There is a common unsettling feeling with the thought of going through the painful process of having to resolve complaints through a call centre customer service. When the process of handling customer issues over the phone started, the initial pain point was to get through the line and register a complaint. With the advancement in technology, we were able to create call centres all over the world, therefore now reaching the customer service has been much easier than before. Customer call centres have been a pioneer in adopting the latest technologies to help the customer with their issues therefore paving a way for brand loyalty and customer retention and satisfaction. With the advent of Artificial Intelligence, the call centre business has gained more traction and automation has made the industry more efficient and quicker in helping customers.

Call centres have always been performance-driven, starting from how the customer calls are handled, how to maximise the problem resolution in the first call and reduce call times. AI-driven call centres have provided the much-needed breakthrough in handling scalability and problem resolution in a very efficient and fast manner. It is creating a massive transformation in the industry by providing real-time feedback on customer calls, prediction on customer problem resolution and intervention and detailed analysis of the call for customer sentiments and overall performance.

With machine learning and artificial intelligence, the customer service agents are getting insight into the customer’s feelings, sentiments and their dissatisfaction by analysing their calls, their pauses, their tones and their ability to communicate. They are able to serve multilingual customers and analyse their sentiments as well due to the algorithm in AI which will help them translate and convey. The beauty behind using AI is, it can provide real-time feedback on the calls for the customer agent. It can give alerts or pointers on whether the agent is being too long or too curt in their communication. It can also indicate the level of stress on the customer’s side and can start certain mitigation strategies on behalf of the customer agent. This helps the customer agent to service the client better and try to resolve their problems in a customer-friendly manner.


The call centre industry can analyse their performance and work on customer problems by analysing their calls. The length of the call, the tone of the call and whether the problem was resolved in one call can actually convey whether the customer service agent has been productive or not. Also, locating and marking calls where the customer was extremely angry or dissatisfied can help the call centre industry to bring about a faster resolution for them by escalating their problem quicker. The sentiment analysis on these calls also gives a measure of the product or the brand feedback from the customer’s side. They can analyse where the maximum problem lies and try to provide a solution thereby reducing the number of complaint calls. With AI behind your industry, it is easier to track customers and their issues by tracking their ID or order number and their problem so that the customer does not have to keep repeating their issues from one agent to another. Such practices make a customer feel more satisfied and create brand loyalty. Effective communication and services from the call centres make a customer feel very satisfied and valued and they, in turn, spread the word to people whom they know to use the brand or the product, thereby creating a base of the product.

Another aspect of AI-supported call centres is that it can train their agents by analysing the calls and teaching them how to respond. Locating distress calls, locating calls which were handled better can motivate the agents and help them learn. Real-time analysis of the calls through AI can also help re-route the calls to agents who can handle them better thereby creating a problem-free channel for the customer. If the customer agent to whom the problem is routed to is skilful in handling such issues then more time is saved on solving the problem and the customer is satisfied. Overall we are trying to reduce the time spent on calls for both the agent and customer and at the same time try to satisfy the customer by resolving his problems quicker and more efficiently.


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