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BlogPost 97307162396 Use of AI and NLP in IVR systems For CX experience | Unifonic//
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Using AI and NLP in IVR systems to improve the customer experience

Artificial intelligence is a branch of technology that’s on everyone’s lips at the moment. It’s being used to significant effect across a huge variety of industries. From healthcare to construction, this field of technology is transforming the way many businesses are run and call centers around the world are no exception. They are seeing some impressive results in terms of efficiency and customer satisfaction through the application of AI. One important and expanding application of AI in call centers is through the enhancement of Interactive Voice Response (IVR) systems, which allows customers to interact with businesses through the use of voice and phone keypad tones. Technologies such as natural language processing (NLP) which is a field of artificial intelligence that focuses on the interaction between computers and humans through the use of natural language is being used in IVR systems to improve the customer experience. Allowing the system to understand and respond to caller requests in a more human-like manner.

So how exactly does the use of AI and NLP help in a call center?

Improving Voice Recognition

Traditional IVR systems often required callers to speak specific phrases or select options from a predetermined list. However, AI-powered IVR systems can use NLP to understand and interpret more natural language spoken by the caller, allowing them to request specific information or complete a transaction without following a predetermined script. This can help to improve the customer experience by making the IVR system more intuitive and easier to use.

More Efficient Call Routing

Another way in which AI is being used to improve IVR systems is by enhancing the ability of the system to understand and respond to caller requests. With traditional IVR systems, if a caller's request is not recognized or cannot be completed, the caller often has to repeat their request, try a different way of wording the request, or has to wait to be transferred to a live agent. However, AI-powered IVR systems can use NLP to understand the intent of the caller's request more accurately and provide a more appropriate response. This can help to reduce frustration and improve the overall customer experience.

Personalizing the Customer Experience

In addition to improving voice recognition and the ability to understand and respond to caller requests, AI-powered IVR systems can also be used to personalize the customer experience. For example, an IVR system could use information about the caller's previous interactions with the company to provide customized information or recommendations. This can help to make the IVR system more relevant and helpful to the caller, improving their overall experience.

Making improvements in these three areas has been the goal of call centers around the world for decades so it’s clear that with careful application, AI and NLP have the potential to significantly improve the customer experience in IVR systems. It is vital, however, to carefully design and implement these systems to ensure that they are effective. This may involve testing the IVR system thoroughly, using metrics such as call completion rates, abandonment rates, and customer satisfaction scores to monitor and analyze performance, and making any necessary adjustments to improve the system.


AI is being used in IVR systems around the world in industries as diverse as healthcare and e-commerce to improve the accuracy of voice recognition, the ability of systems to understand and respond to caller requests, and the personalization of the customer experience. By carefully designing and implementing these systems, call centers can make the most of this emerging and important technology by providing a better experience for their customers and making their call centers run more efficiently.

To speak to one of Unifonic’s experts on how to implement these improvements in your call center, contact us today.

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