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Booking an opticians appointment; rescheduling hotel check-in dates; even finding out how to replace your dishwasher filter.

All completed in seamless – dare we say enjoyable? – experiences.

This is the world we envision for customer services. And it’s currently in creation, with the help of Large Language Models (LLMs).

Before we get into this topic, it’s important to define what we’re talking about when it comes to LLMs.
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What are Large Language Models (LLMs)?‍

LLMs are advanced AI systems (also known as Conversational AI) designed to understand, interpret, and generate human language in a way that reflects natural conversation. This is the technology that powers chatbots like ChatGPT and Microsoft Copilot. If you’re familiar with these, you’ll know they’re not just programmed to respond with pre-set answers but are capable of learning and adapting their responses based on the context of the interaction. This makes them incredibly versatile and powerful tools for enhancing customer service experiences.

At their core, LLMs are built upon vast amounts of text data, enabling them to grasp the nuances of language, culture, and even emotion. They can engage in conversations, answer questions, solve problems, and provide information with an unprecedented level of sophistication and scale.
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Revolutionising Customer Services

The root of most customer service calls, texts, messages and chats revolve around poor experiences: long response times, unsatisfactory communication, and misunderstanding the key issue. The core problems behind these? Complex systems with agents unable to access the information they need. And this is where LLMs and conversational AI come in.

AI Driven Systems are poised to change the way we interact with brands and services — in particular through customer services channels. Regardless of whether a company primarily uses phone systems (IVR), chatbots, or platforms like social media, LLMs are already transforming the outputs on both sides:

1. Customers get to a solution quicker and easier
2. Companies use fewer resources, achieve higher satisfaction scores, and ultimately have a healthier bottom line.

It’s time to put your customers’ needs first and think about going that extra mile to make their lives a little easier each day.
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‍Two applications of LLMs in Customer Services

Companies are awakening to the potential of these AI-driven systems in various ways, and in two main categories.

Firstly: brands are launching new channels. Platforms like Alexa provide customers with more accessible and convenient support options - in a hands free way.

Secondly: rebuilding – or tweaking – current channels. For example, integrating LLMs (the technology that powers tools like ChatGPT) into existing IVR (interactive voice response) systems to create dynamic agents that can adapt to customers in real-time, providing more personalised and efficient support.
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The Power of LLMs for Customer Services

Characteristics of large language models make them an obvious choice for deploying in customer service processes.

Let’s look at three of these powerful qualities:

Scalability – LLM usage can easily increase to meet the growing or seasonal demands of a business, meaning your brand can expand operations as and when they are needed - without having to add more customer agents.

Efficiency – AI-driven systems are built on large volumes of data, so handle large volumes of queries with ease, reducing wait times and providing faster resolutions.

Personalisable – LLMs can understand and respond to customer inquiries with greater context, resulting in more personalised interactions.
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What to keep in mind when using LLMs in Customer Services

As we embrace the potential of any new technology, including conversational AI, in customer services, it’s essential to build with data privacy and ethical AI practices at the core.

No interaction will feel satisfactory to a customer if they don’t believe their information is being taken seriously. 

“Privacy in exchange for utility is the history of the internet. When a customer trusts that their privacy will be protected, they will be willing to adapt to new technologygo with you if the utility being given back is worth it” - James Poulter, Head of AI and Innovation at House 337

Ensuring that these systems are developed and implemented responsibly will be critical in creating a future where customer interactions are more enjoyable and efficient than ever before.
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Real-world example of LLMs in Customer Services

For the companies who have already embraced LLMs and Conversational AI, the benefits have been staggering: 

Klarna

In 2024, Klarna launched an AI assistant powered by Open AI to support customer services. In just one month, they saw resolution time drop from 11 minutes to just 2 minutes, and a 25% reduction in repeat queries. It’s estimated that the AI-powered chatbot will lead to $40 million USD profit improvement in 2024.

Chipotle Mexican Grill

In the kitchen, AI is helping Chipotle Mexican Grill staff manage busy restaurants, while prioritising freshness and minimising food waste. Leveraging AI and machine learning, the kitchen management system monitors ingredient levels in real time and notifies the crew how much to prep, cook and when to start cooking. Reducing manual tasks gives the crew the time to concentrate on delivering exceptional guest experiences.
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What next?

The future of customer service is one in which LLMs have transformed the way we interact with brands and services.

By leveraging the power of conversational AI, we can create a world where never pressing 1 again becomes a reality – and customer experiences are more seamless, personalised, and enjoyable.

Is your business ready to embrace the transformation? Get in touch today using the contact form below.