AI is finally, really, actually here. And it's going to reshape society in ways I doubt we can imagine. It's clear that some areas of the economy are already primed for epic levels of disruption and customer service is one of these. AI will deliver the holy grail of customer service.
Instant, consistent, excellent support for every single customer 24 -7. This is... not just some abstract future we're building towards, it's actually happening today. We have customers who are having over 70% of their inbound support requests answered by our AI agent, Fin, and that's all while maintaining their historical levels of customer satisfaction. Over the past year, as we've built out our AI platform, we're seeing there's a fundamentally new way of doing customer service. We call it...
AI First Customer Service, and this is the future. Paul Adams at Intercom, who's been building out much of these ideas in this second episode of Off Script, is going to lay this out for us in the way that only Paul can. Enjoy. Technology only moves in one direction.
Once you go through these before - after moments, you never go back. Oftentimes, there is some breakthrough moment early in a technology cycle everyone can connect with. So for example, the iPhone came out, and it just changed everyone's perception of what's possible. It was just like before -after moment. With AI, ChatGPT came out. And people could use it.
It was easy to use. Anyone can use it. It's like using Google. And when you go through these kind of before -after moments, you don't go backwards. People who got iPhones didn't go back to BlackBerry's.
BlackBerry went out of business. Once you've gone through that door, you never go back. Today, we're here to talk about AI for customer service.
But to really understand that, you've got to zoom way out and look at waves of technological change. This is like a well -studied thing. And it's not complicated to understand. Technology develops in these waves. So in the start of the wave, it's early, and it's kind of like not a lot of people are using the thing.
Some people are cynical or skeptical of it. Then it's like mass adoption. And then the kind of invention innovation era kind of ends. And a new wave starts. And this is like, throughout history, this is, you know, industrial revolution, things like electricity, more recently the internet, mobile phones, all these things reshape society. You know, prior to the industrial revolution, like, things were manufactured by hand.
And suddenly, you could mass produce things, which led to factories. And that changed how people worked, changed how people live, and that just totally changed the economics of what was possible. You know, if you go back 100 years, people were literally riding around on horses. Then the car showed up. And people then didn't really think that much about it.
People were cynical and skeptical of the car. But it took over and it led to suburbia. It led to Walmart. It led to like McDonald's.
And you can debate whether suburbia and McDonald's are good or bad for humanity. But it totally changed. Like if you look at Earth from space, the car totally changed what the planet looks like. AI is going to do the same. You can go back as far in history if you want. The pattern is the same every single time.
The question is how big will it be? And it's certainly as big as the smartphone. I think it's certainly as big as the internet. And I think there's a very good chance it's as big as the Industrial Revolution.
We speak to customer service leaders every day of the week. And we try and understand them, learn what they really care about. And all sorts of things come up here. They care about things like operational efficiency, and they care about the happiness and retention of their team, staff turnover is a problem if it's too big, and so on. But the thing they care most about, by far, is the customer experience, the experience of their customers.
And it's incredibly hard to deliver a really good customer experience. at any kind of scale. If you've got thousands of customers, tens of thousands, millions of customers, actually giving them a great experience consistently every single day is kind of this Nirvana, Holy Grail type steak that no one really ever achieves.
So this idea that customer service can be instant, accurate, vast, engaging, it's a night and day difference to anything we've experienced before. And so... there's an incredible opportunity for companies to change how people think about them through incredible customer service. The interactions people have with businesses, like they're not many most of the time. You know, they're like, with customer service, it's typically when you have a problem, not when you're delighted with the business, you know? And so actually customer service becomes this really important, critical brand building opportunity.
Intercom is a technology company. We're 12, 13 years old. And so you think that a lot of our customers are modern technology companies too.
We have customers who are 100 years old. Banks, utility companies, some of our most pioneering customers, some of the customers of ours who are leaning most into AI, the company is 100 years old. And so suddenly customer service can totally change how you think about a company. You go on to a utility company, you... you pay your electricity bill or something like that. It's not really something people get excited about.
They don't wake up and think about paying their electricity bill. But then they do it or they have a question and suddenly they're interacting with this cutting edge next generation AI and it changes how they think about the company. Suddenly they're thinking like, wow, this company is incredible. Not only are they at the forefront of this, they're also 100 years old.
They're 100 years old and they're at the forefront. How did they even manage to do that? So like... It's a huge opportunity for businesses to literally change how people think about them.
A lot of people say that customer service will be one of the first industries to be impacted by AI. We think that's true, and it's mainly because AI happens to be, just happens to be, incredibly good at the things customer service agents do. AI can already do things that many knowledge workers can do.
It's really good at doing things like retrieving information, analyzing information, generating insights, answering customer questions, pulling data from the customer record, conversing back and forth, troubleshooting, disambiguating questions. It can do this conversationally and it can do it incredibly accurately already. These big technology waves take anywhere between five, 10, 20, 30 years. We're like one year in. It's already doing incredible things and it's just going to get better. It's going to be able to do more and more things.
It's going to be able to start taking actions and doing things for customers. Today it answers questions. It's removing all the repetitive questions that customer service agents have to answer, which by the way is the thing that makes the job not fun.
The AI agents are going to do all of these things. It's going to free up the human customer service agents to do more interesting things. But AI is not just good at answering the questions customers have. It's also actually really good at a lot of the things that support managers have to do.
Support managers have to look at the overall system, look at the performance of their team. Think about things like, are customers getting a good experience? Are they answering questions? The questions being answered accurately by people. So what AI has done is it has given us a new way to do customer service.
And that new way is way better. Right now, there's a lot of AI news, noise, you know, pick your word. And in a lot of cases, what a lot of... businesses are thinking is that they need to add AI to what they do today. And that's not how we think about this at all.
We think this is a complete mindset change. It's not just a product change. It's a big product change. The new types of products that are being built in customer service are unlike anything we've seen before.
It's not just that. It's a mindset change. And the mindset change is one where you need to think about AI first. So the way to think about this isn't that you should adapt and tweak and iterate your existing customer service setup, you should push the old way to one side and embrace a new way of doing it, a completely new mindset. And that new way, we describe it as AI first customer service.
So what that looks like in practice is when a customer shows up and has a question, AI answers first. You've got to set up the system that AI answers first. Why? Because it's typically better. It can answer the question more often than not. It can do it 24 -7. It can do it in any language.
It can do things, it's instant. It can do things that the best human agent team in the world wouldn't be able to do. But not just that. When the AI agent can't answer the customer question, when it does end up with the human team, which will happen, sometimes AI agents can't answer questions, when that happens, the team also must be AI first. And what that means is that they have an AI co -pilot. with them in the inbox.
So when they're answering questions or they're trying to work through tickets that are created out of customer questions, the AI copilot is there all the time helping them. And if you don't have an AI copilot, it means your job's harder. You're like looking up information, you're manually crawling through stuff. Whereas if you give the AI copilot access to all of your internal knowledge, all the external knowledge too, all the data, just connect to all the different sources, the AI Copilot is really good at picking apart all the different pieces. It can do it on a scale that a human just can't do. It can analyze at rates that are just far faster across a much broader set of information and suggest things to the human agents.
So it's not going rogue answering customer questions. It's saying to the human agent, hey, I'm here to help. I'm your copilot. Something that the AI Copilot can do that's incredible is that a lot of the time, It can look at all conversation history and it can look at customer satisfaction across all of those conversations.
So for any individual question, it can pick out the best answer, not just a right answer, but like the very best answer. Like I say, actually when customers get these types of answers to that question, their satisfaction increases, they're happier. You can even look at things like retention, they retain better, they grow more, they use the product more. And for experienced agents, that may not be. that big of a deal. They typically are good at their job.
They typically know the best answers just from experience. Think about like a new human agent. Someone who's just joined the team. And typically the ramp time with new folks is, you know, it can be long. And turnover staff can be high.
A lot of managers spend a lot of time just trying to train new folks. They don't need to anymore. They can train the co -pilot, and the co -pilot will train the new team member.
So the first part of this is that customers have an AI agent answering questions for them instantly 24 -7 in any language, incredible. The second part is that support teams, human agents, have a co -pilot helping them, again, 24 -7 all the time, suggesting the very best answers to questions to help them give great customer experiences. And the managers and the leaders and people who work in support ops, they are the third part of this. They also have AI.
They'll have a buddy. someone who's able to answer all of their questions, any manner of questions around performance, operational performance, team performance, accuracy of answers, are customers happy? And what's incredible about this is that today, if a manager or a support leader wants to understand how good their customer experience is, they rely on things like CSAT. They rely on things like asking customers at the end of a conversation, hey, did you answer your question, and so on and so forth. Very few customers actually ask that.
fill in those surveys. They don't really answer them en masse. So anywhere between 10 % and 20 % typically is what you get, which means that 80 % or 90 % of your customer experience isn't measured at all.
And so what AI can do is actually measure 100%. The AI that runs powering the AI analyst and the AI insights, it can actually read and parse every single customer conversation. And even when customers don't.
reply back and say they were happy or not happy or we did or didn't answer the question. AI can figure that out because it has all of conversation history. It can figure out not just whether the question was answered accurately, but whether people were happy. It can pull out tone, sentiment. It's really, really good at this kind of stuff.
And so for the first time ever, for the first time ever, they'll be able to measure 100 % of that. If you want to do AI first customer service, you must have the three components. You must have the AI agent for customers.
You must have the AI co -pilot for your human support team. And you must have the AI analyst and AI insights for leaders and managers. You must have all three components to properly do AI first customer service. So these three parts all sit on this data and knowledge layer. And this data and knowledge layer is what the AI learns from, basically. And so.
That data knowledge layer needs to be really, really good. You have the data, like customer records, and it can connect into all sorts of different types of places, whether it's your CRM, other types of data sources you use to power customer information, internal systems that you've built. It can connect to all of the data systems. And then on the knowledge side, you have content. It could be externally facing content that's been approved to be accurate, like a Help Center article, for example, things like that.
But it also can connect to internal knowledge too, like maybe you use a wiki internally. So there's data and there's content that kind of powers the knowledge. And this layer sits below the agent, the copilot, and the analyst. So for example, the AI agent, when it can't answer, hands over to the human team with AI copilot. They then can answer the question, and then that teaches the AI agent what to answer next time. So the copilot.
powered answer delivered via the human agent teaches the AI agent. So the system just gets better and better. There's this beautiful loop. And the manager has the AI analyst and the AI insights, again, to help the system. So it's one seamless system.
So you have to have all three. And they have to have this beautiful feedback loop that just makes it better and better. This is only possible if it's built in the same system. If you have a legacy system and you go and acquire an AI company, and then you have to try and integrate those two things, that's data and knowledge layer that sits in the middle, it is a mess. It's a mess of mangled different data formatting and different data types and even different types of platforms these things have been built on.
So you need everything on one platform. What's amazing about AI systems is that they teach themselves. They teach themselves to get better.
And so if you have everything in one system where it's easy, the data is clean and clear, AI can get better faster. So AI first is the mindset people need to adopt. Think about this question, how good is AI at communicating with humans? You need to look at a scale.
And on one end of the scale is transactional communication. Like literally, I just need information back and forth. And over here is emotion, like I'm angry, or I'm sad, or I want to celebrate.
Human communication spans the whole thing. We don't go around in a highly emotional state all the time. Actually, a lot of the time, humans are very transactional. AI is incredibly good at transactional communication. Even if you think about customer service, our world, most customer service queries are quite transactional.
People are just looking for information. So that's why AI is so good at it. But over here is emotion. And so again, if you tie this to customer service as an example, I think it's a great example, sometimes people are angry.
They feel like a company they love has let them down or... They really needed something and they bought it from this company and it didn't work out. And sometimes people just need to vent. And sometimes you just need an ear. And AI can't be that yet. Now, like, could it be in the future? I think technologically it'll get close.
And then culturally, will people accept that? Who knows? We'll have to wait and see. But certainly AI is moving along this spectrum very, very fast. And it's getting pretty close up here.
And there's companies building in the space, lots of companies, technology companies building in the space of emotionally tuned in AI or whatever. And I think it's possible, you know. A lot of people are looking at the movie Her as being like prescient.
Is that the word? No, I'm mispronouncing that. Prescient, yeah. People are looking at the movie Her where, you know, it's up here. It's under like emotional communication. So who knows? This is like highly speculative. No one knows, but...
AI is definitely moving along this axis and a lot of communication happens down here. So AI is going to be able to do it for us. One side point is when people hear about this idea that AI is going to do more and more work, AI is going to take over a lot of the knowledge work we do today, that can be scary for people. But actually it's incredibly empowering.
It just frees up. all of us to have more time. With more time, we can do more things.
We can be more creative with our time. We can deliver in those like empathy, empathetic situations with more, with higher degrees of empathy. We're not rushed, we can work more time again. So I think a lot of this is incredibly positive. The AI is going to take away a lot of the burden that's kind of been put on us by recent technologies potentially, and actually give us more time at the other end.
So I think it's going to be an incredibly positive thing. People are already starting to see that in different ways. Here's what I think about the timeline.
We've tried to predict how fast this would happen internally before, and it's happening faster than we thought. And we thought we were being ambitious and optimistic and so on. If you just look at Fin, our AI agent, we launched Fin a year ago. And you look at the average resolution rate. We started out in the 20s when we launched it less than a year ago.
And then we started adding things to it. We added things like multilingual Fin. We added the ability for it to disambiguate questions and kind of go back and forth. We added the ability for human agents to help it get better and teach it things when it couldn't answer.
And we've improved our AI engine underneath it all. So we take the LLM, the Large Language Model, and we tune it. We refine it.
We change it. We do a lot of work at that level. So all these different things, just over in the last year, 20s, 30s, we're now in the 40s. We're heading to 50%, like 50%. This is like suddenly a support team using our thin AI agent.
Half of their questions that used to go to people are now being answered accurately, happily by AI. And customer satisfaction hasn't gone down. Actually, at times it's gone up. And this is just the start. Like these are transformational results and we're like a year in.
And so where are we going next? I don't know, but I can... say with a lot of certainty that customer service is going to radically change. I think in three years time, four years time, we will look at the customer service of today, and certainly a year ago, and we'll kind of think it's incredibly old fashioned and archaic. And so I think that it's inevitable that all businesses are going to go AI first.
I think it's inevitable that all customer service teams will be AI first. And it's just a matter of time. So what matters most is that the customers of these businesses are getting great experiences. That's what all this boils down to. And so I would just highly encourage customer service leaders everywhere to get into this world of AI-first and start trying it.
And I think you'll find when you try it that the results are far better than you ever could have expected and the technology is getting better faster than you ever could have hoped for.
2024-05-16