3 Key Contact Centre AI Predictions for 2024

AI (Artificial Intelligence) concept with brain made of light connections

As we move into 2024, momentum around deploying contact centre AI is accelerating. Gartner predicts that by 2025, 80% of customer service and support organizations will be applying generative AI.

Moving beyond the hype, companies are now looking at exactly how they implement AI in the contact centre. This includes shifting from first-generation uses such as chatbots to embrace new opportunities.

At the same time, there are more Large Language Models (LLMs) coming out, often trained on more specialized datasets than ChatGPT. These can be more useful for specific applications, such as in the contact centre.

While globally there’s a lot of concern about AI replacing jobs, in the contact centre I believe it will deliver maximum value when used to augment agents.

It will help them to work more efficiently, improve the levels of service that they deliver and make their roles more interesting.

Based on this, Steve Nattress at Enghouse predicts that the biggest impact of contact centre AI in 2024 will be in three key areas.

1. Conversational Insights

Contact centres handle hundreds or even thousands of interactions every day. All of these conversations provide invaluable insight into customer, business and agent needs.

However, the sheer volume of interactions traditionally makes it hard to analyze each one manually.

This means that companies get a partial picture. They only have a snapshot of what customers are saying, and how agents are responding.

AI completely changes this. It can automatically analyze every interaction for sentiment, meaning and context. This helps businesses in three ways:

Firstly, it transforms Voice of the Customer programs, giving the ability to drill down into the details of conversations.

Companies can automate the analysis of every interaction. This enables them to uncover new actionable insights to improve CX.

Secondly, it provides immediate, automatic summaries of conversations. Normally, agents create these summaries at the end of every call.

However, this approach adds significantly to their workload. They can also inadvertently miss important details.

Switching to AI-driven summarization ensures consistency. Businesses can analyze all conversations and use the results to improve customer service processes.

Finally, conversational insights provide contact centre supervisors with a much more comprehensive view of agent performance. They can analyze every interaction that takes place, not just a small selection.

This removes any concerns about bias or variation in how different supervisors analyze or judge conversations. Insights uncover areas where agents require additional coaching, as well as highlighting best practice.

2. Hyper-Personalization of Knowledge

Whether through web self-service, chatbots or agent knowledge bases, AI-based search already understands the context of a question.

This means it provides faster, more relevant answers than keyword search. Generative AI takes this a step further.

It creates an exact, tailored response to the actual question asked, rather than providing a generic knowledge base answer.

This provides a hyper-personalized reply, focused on the actual query itself, and designed to meet the specific requirements of the audience, removing any information from the knowledge base answer that hasn’t been specifically asked for.

This improves the overall experience. It removes the need for customers or agents to scan through longer answers to find the information that is only relevant to their query.

3. Extending Multilingual Abilities

Companies increasingly want to offer customers the chance to communicate in their language of choice. However, this can be difficult and potentially expensive when it comes to supporting non-native languages.

We’ve already seen how global companies are using real-time chat translation to enable agents and customers to have a conversation, even if they don’t share a common language.

Applying Large Language Models (LLMs) and generative AI can extend this to cover a much wider range of languages, improving the experience for all customers without increasing costs for the contact centre.

AI also enables translation to move beyond digital channels to cover voice conversations, allowing agents and customers to each speak in their own language while still understanding each other.

2023 showed us the possibilities that AI, particularly generative AI, offered the contact centre. Building on this, 2024 will see companies moving beyond pilot projects to scale how they use AI within customer service to boost the experience and transform productivity.

It promises to be an exciting year as we move towards truly augmented agents that bring together the best of AI and human skills to deliver on customer needs.

This blog post has been re-published by kind permission of Enghouse Interactive – View the Original Article

For more information about Enghouse Interactive - visit the Enghouse Interactive Website

About Enghouse Interactive

Enghouse Interactive Enghouse Interactive delivers technology and expertise to help bring your customers closer to your business through its wide range of customer contact solutions.

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Call Centre Helper is not responsible for the content of these guest blog posts. The opinions expressed in this article are those of the author, and do not necessarily reflect those of Call Centre Helper.

Author: Enghouse Interactive

Published On: 30th Jan 2024
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