Hey there,

The AI revolution has come with a whole new language to learn. It seems like the moment we think we’re beginning to understand AI and its impact on customer service, we’re bowled over by another wave of jargon.

Which leads us to the question: Do we really need to understand the deepest intricacies of AI to take advantage of its benefits? The answer is absolutely not. Most customer service professionals are not there for complex technical jargon – they only want to know what’s needed to understand and prepare for AI’s impact on themselves, their teams, and their customers.

So, here are the basic terms you need to know to understand the trends and implications of AI in customer support, and how they will impact you:

Large language model (LLM)
Behind every AI chatbot you’re hearing about is an LLM. LLMs are a type of AI algorithm that can generate text similar to text written by humans. They’re typically trained on massive datasets of billions of words from books, articles, web pages, etc., to understand the patterns and relationships between words so they can generate or predict new content. You’ll have heard of ChatGPT and GPT-4 – those are LLMs.

What do LLMs have to do with CS? Those massive datasets allow them to pull information to answer questions in a more human way than we’ve ever seen. Just watch out for…

Hallucinations
Hallucinations are the name given to the plausible-looking answers that AI chatbots can confidently deliver, but which which are actually incorrect or nonsensical because of limitations in its training data and architecture.

By now, your CS alarm bells will be blaring – there’s no way you can take the risk of customers getting totally inaccurate information from a chatbot. This was our number one problem to overcome when we first started working on Fin, our AI chatbot. We solved it by constraining Fin’s dataset to the information in our customers’ support centers, meaning their customers get the right answer every time, delivered in…

Natural language
When people talk about natural language in AI, they mean that the AI system responds in the way a human would: conversationally rather than robotically. Natural language processing (NLP) is a branch of AI that focuses on the interaction between human language and computers, and aims to enable computers to process, understand, and generate human language.

You can check out our AI glossary to learn more about AI terms and concepts – but the main thing to understand is that it's now possible to easily implement an AI chatbot that uses only your support center to answer up to 50% of your customers’ questions in a personable, natural, and trustworthy way. Put that way, the hype makes a lot of sense.

What’s been happening

To AI or not to AI? The support leader’s dilemma →

Intercom's VP of Customer Support Declan Ivory has worked in the industry for more than 35 years, and he's never been more excited about the evolution of customer service. Here, he lays out the major considerations for support leaders during this one-in-a-generation shift.

AI educator Kavita Ganesan on uncovering AI opportunities in your business →

With more than 15 years of experience working on natural language processing, search technologies, and machine learning, Kavita Ganesan has a wealth of insights and advice to help you seize the right opportunities and seamlessly transition to the age of AI.

Two AI chatbots walk into a bar: TV writer Joe Toplyn on teaching chatbots to crack jokes →

Humor has long been considered challenging for AI systems because of its reliance on contextual factors and cultural and social nuances. But that's changing; comedy writer Joe Toplyn takes us on a journey through his latest project: teaching chatbots the art of comedy.

Meanwhile, on TikTok...

At Intercom, we understand that the week of a customer service professional can be amazingly varied. That's why we make sure to offer all sorts of content on the Intercom TikTok channel; from useful tips, to interview clips, to customer service quips that have been proven to make at least one person laugh (so what if that person is on our Content team?) Follow us for a flow of customer service content that promises something for everyone.

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What's going on in customer service?

Being nice isn't enough: Can you win back unhappy customers? Is it possible to turn a bad experience into a good one? CX expert Dave Klimek weighs in on proactive vs reactive support, in conversation with CMSWire.
Creating an amazing customer experience on a budget: In Forbes, CX expert and past Intercom podcast guest Shep Hyken lays out the most important thing to consider when cutting costs: how your choices will affect your customer experience.
3 ways to reenergize your team when morale is low: In HBR, Amy C. Edmondson and Tomas Chamorro-Premuzic offer some simple things you can do as a leader to reduce the risk of low motivation and burnout among your team.