Artificial Intelligence

How AI Is Changing The Call Centre Landscape

Changing times require the flexibility to adapt. This is what happened to call centres when COVID-19 hit the global business market. Customer support services were moved to home offices as social distancing was implemented by many governments through lockdowns. 

As a result, many businesses found it a challenge to adapt to the new normal. However, many call centres turned to artificial intelligence (AI) to help meet the surge of customer support needs.  

Uses of artificial intelligence 

Your company can benefit from artificial intelligence in the following areas: 

  • Improve routing and scheduling using your business customer relationship management (CRM) data. 
  • Give personalized customer services anywhere. 
  • Get real-time insights from all your customer contact channels. 
  • Increase agent wait times, availability, and opportunities to deliver proactive services. 
  • Implement chatbots that enhance automated workflows. 
  • Automatically improve and classify customer cases according to sensitivity and domain through predictive analytics. 
  • Help your field agents provide services according to CRM data.  


Artificial intelligence might take over the bulk of customer support processes in the United Kingdom (UK). To revamp your contact centre in the UK using artificial intelligence, you need appropriate software to facilitate automated tasks. 

This article focuses on the transformation that AI has brought to the call centre landscape. These areas of change are: 

Predictive behavioural routing 

Predictive behavioural routing (PBR) was launched in 2014. This technology approach combines analytics and AI to match your customers with certain personality models, which helps to route customer calls to the agents that are suited to handling that kind of personality type. The beauty of this is that it transforms random encounters into a personalized customer service experience.  

Recently, in the year 2018, PBR was integrated with advanced Interaction Analytics, which is owned by NICE Nexidia and is regarded to possess the biggest database of customer behavioural profiles that help business brands gain comprehensive knowledge of customer persona and journey. (2)

PBR software can detect the natural predispositions and habits of the caller and available agents to make a good match that will bring out a positive and natural interaction. Moreover, PBR can be integrated with other software such as CRM, interactive voice response (IVR), and skills-based routing to provide the agent relevant data to make the interaction efficient for a good customer experience.  

Interactive Voice Response (IVR)  

If you’ve ever called the customer support of your mobile phone service provider, you’ve experienced this kind of service. For instance, you might have heard, ‘To speak with the billing department, press 1; to speak with a sales representative, press 2,’ and so forth. 

The introduction of IVR saved customer service agents plenty of time. This kind of service has seen growth through the inclusion of machine learning and AI. IBM developed a natural language understanding (NLU) software using AI-enabled knowledge that can give real answers to the questions your customers ask.  

AI utilizes big data

Over the last decades, entrepreneurs had challenges in collecting enough information concerning their customers. This data is key when it comes to making sound decisions regarding customer service and marketing. You need to be aware of your target audience demographics, how and when they’re likely to convert, and if they prefer using a mobile phone or computer to search for your products.  

Previously, collecting this information was a difficult task and took a lot of time to analyse. The extra time could have been used in other business processes such as product creation, website development, or marketing. However, with the introduction of AI, collecting and analysing this data has been easy. 

This is because artificial intelligence is efficient in analysing large quantities of data, such as CRM data, and provides reports for easy visualization. Data visualization helps managers and business owners understand their target audience. 

Data generated through AI is considered more reliable than the one collected, processed, and analysed by humans. As a result, you can use your time to make relevant business decisions instead of wasting it figuring out what your data means.  

Chatbot conversations 

Unlike human agents, chatbots can answer several questions from several customers. This helps call centres reduce wait times and fatigue. A human agent only comes in when the question being asked is difficult and complex to the chatbot. 

Using PBR, a chatbot can identify the appropriate customer agent to handle the questions of a customer. It also provides a background about the customer for effective handling of the client by the agent.  

Chatbots can be integrated with your customer’s account information and provide a personalised customer experience. AI chatbots are in implementation on social media platforms, such as Facebook Messenger, Slack, WhatsApp, and others to improve communication. 

For instance, Facebook Messenger’s AI can display pop-ups that suggest certain actions to you, like sharing your location, sending someone a sticker, or suggesting friends to someone who has joined Facebook. Thus, using chatbots, customers can communicate efficiently without the need for human intervention.  


Artificial intelligence is generally expected to perform most of the processes in customer support with the integration of other technologies like machine learning and natural language understanding. If you haven’t incorporated AI in your call centre, this might be an area to consider venturing into in the future as a way of improving your customer’s interactions with your brand.  


  1. “Rise of the Chatbots: How AI Changed Customer Service,” Source: 
  2. “NICE Announces Closing of Mattersight Acquisition, Introducing a New Generation of Customer Analytics,” Source: