Adapting to the AI revolution in CS: Discussing our 2023 AI report
AI and automation are revolutionizing the landscape of customer service.
Recent developments in the field of AI have taken the world by storm, with huge implications for the customer service landscape. We decided to survey more than 1,000 global support leaders and practitioners to ask them how they’re feeling about the rapid evolution of AI and automation and how they’re adapting their strategies for the changes ahead.
The result is The State of AI in Customer Service: 2023 report, where we dive into the top five trends transforming customer service. This moment is ripe with opportunities – the sooner you adopt AI for your customer service strategy, the greater chance to win a competitive edge. And that’s why today, we’ve invited three experienced customer service leaders to join us on the podcast to share some insights on navigating this new AI landscape and successfully integrating it into your own support strategy:
- Samuel Miller, Customer Support Operations at Dental Intelligence
- Ruth O’Brien, Director of Customer Support at Intercom
- John O’Hara, Director of Customer Experience at Logikcull
They’ll talk about the current state of AI and automation in customer service, real-world examples of successful adoption, and strategies for reaping its benefits and overcoming challenges.
Short on time? Here are a few key takeaways:
- While AI’s initial adoption has been slow due to competing priorities or tech that overpromised and underdelivered, companies now know that investing in AI is a competitive advantage.
- AI can be leveraged to alleviate simple queries for CS teams, enable 24/7 support, improve response time and efficiency, save on training costs, and make data-driven decisions.
- When adopting AI in small CS teams, begin by dedicating time for research or even allocating project time for reps to lay the groundwork for implementation.
- To help your teams overcome fears of being replaced by AI, involve them in the process, create new career development opportunities, and approach it as a complement to human support.
- You can mitigate implementation risks by setting up guardrails, creating clear exits to reach human reps, and setting the right expectations about the bot.
If you enjoy our discussion, check out more episodes of our podcast. You can follow on Apple Podcasts, Spotify, YouTube or grab the RSS feed in your player of choice. What follows is a lightly edited transcript of the episode.
AI investment race
Liam Geraghty: We surveyed over 1,000 global customer service professionals to find out how they’re adapting to AI, how they plan to leverage AI and automation, what opportunities they hope it will bring, and their concerns. We then compiled that into our 2023 report. The report is full of additional insights and actionable tips, so make sure you give it a download. We’re going to be covering the top five trends from the report, so let’s get into it.
The first trend, AI investment, is accelerating at a blistering pace, and there’s a huge opportunity for early adopters. We found in our data that there is an investment gap. An overwhelming majority of support leaders plan to invest more in AI this year, but only 38% have actually invested in AI. This means those moving faster can gain a competitive edge while others play catch up. Ruth, if I can come to you first, why was the initial investment in AI so slow?
“They understand that if they get going with this, they’re going to have a competitive advantage over some of their competitors”
Ruth O’Brien: Honestly, I think it’s because some of the technology in the past wasn’t amazing, so people weren’t convinced. It also takes time and effort to build a strategy around AI and automation. It doesn’t quite just work out of the box, so there needs to be a plan around it. And in a world where customer support is very reactive, and many support teams are often running to keep up with SLAs and backlogs and long customer wait times, taking the time away from dealing with that and dealing with the immediate firefighting can be tricky, and taking space to build a proactive future in terms of AI can be hard for different teams.
Liam: And so what changed?
Ruth: What changed? Well, for one thing, the technology is getting better and better, especially over the course of the last maybe eight months or so. Big changes have come in the world of AI. More and more teams are either speaking with peers in the industry or interacting with good chatbots, whereas before, I think people would’ve been interacting with not-so-great chatbots. The world is changing, people are trying to keep up with it, and they understand that if they get going with this, they’re going to have a competitive advantage over some of their competitors.
“What motivates us to focus on AI as a benefit is bandwidth. We’ve got a very small team – eight US-based reps providing 24/7 support to a global audience”
Liam: Totally. In our survey, in the top applications CS leaders identified for AI to make a big impact, you see faster responses, more consistent responses, saving money on training, and summarizing conversations. Where do you see the biggest value add for AI, John?
John O’Hara: That’s a great question. I’m looking at these numbers and thinking that my team is already doing really well with speed and consistency, and we have great partnerships with customer success and training. What motivates us to focus on AI as a benefit is bandwidth. We’ve got a very small team – eight US-based reps providing 24/7 support to a global audience. AI represents effective case deflection for those simple break/fix questions where people just need information about how the app works. That’s a whole tranche of conversations that can be taken off of my team’s plate so they can focus on more consultative work. That’s probably the biggest driver for us.
Liam: And Sam, what about you? What’s the biggest value add for you?
Samuel Miller: For us, it’s really about saving money on training because we don’t have to train them on every single thing. We can just train them on the major issues they have to do, and not so much on the day-to-day things that customers can find, the knowledge articles, and stuff like that. It allows us to go deeper in the training quicker.
Liam: And Ruth, what about you? What can we expect in the near future?
Ruth: Honestly, faster responses have been a huge piece of efficiency for the wider team. Some teams see AI and are thinking about headcount reductions, but if you try to not do this thing where you do more with fewer heads because AI is taking care of more work for you, how do you use the resources you have right now to go above and beyond? They’re answering customers immediately and taking care of some of the less complex queries, and that, in turn, is speeding up the humans to get through the queues and deal with the more complex queries. We’re seeing great results in applying this technology to efficiency and response times in customer support.
“Those two hours a week keep us in line to make sure we’re still moving forward without making too many changes for our customers to feel overwhelmed”
Liam: That’s brilliant. While leaders are excited about the opportunities that investing in AI will bring, more than half are concerned about balancing investment in AI with investment in existing support resources. Sam, I’d love to know how you’re planning to balance the implementation of new AI tech with your existing plans and resources.
Samuel: Yeah, it’s tricky, especially when you’re a small support team, and not many people have the time or ability to really go in and work on these. I dedicate at least two hours a week to researching trends that the other companies are using – literally going into other companies and going through their chat flow and seeing how they do it and how I can recreate it. Those two hours a week keep us in line to make sure we’re still moving forward without making too many changes for our customers to feel overwhelmed or our team to keep up with things.
Liam: That’s great. And Ruth, what about you?
Ruth: I am in a very luxurious position in many ways – our company builds tools using AI technology or powered by AI technology. We’re early adopters because we have to be, which is amazing because we’re getting going with this exciting technology right away. But it does come with a lot of pressure to show off the technology and make sure it looks great for our customers. If we are doing a bad job, it’s not exactly going to be a great thing for our customers to want to buy it. We’re under some pressure to show it off and move forward with it, but it’s good pressure because it makes you do it right.
Liam: And John, what about you?
John: Yeah, we’ve found success in providing or allocating project time for my frontline reps. They’ve got customer-facing work, but they also allocate an hour or two a day to focus on laying the groundwork for AI. We haven’t plugged Fin in yet. We’re still working through some compliance concerns, but we have been doing a big overhaul of our customer-facing articles and macros because we want to train the trainer. And that’s really been effective. It helps people who have developed their careers and are looking for the next steps to seize new opportunities, take on more responsibility, and show their skill set in more interesting ways.
The rise of the augmented workforce
Liam: Brilliant. Let’s move on to our second trend. The big question on everyone’s mind is, is AI going to steal my job? From what we saw in our survey, the general consensus is that the role of humans is evolving, not diminishing. That doesn’t change the fact that CS teams are still concerned about this. Ruth, how do you see AI and automation tying into the human component of customer support?
Ruth: I briefly touched on it when we were chatting a few minutes ago, but I’m hoping we can move away from this world of fear and build it more with excitement. Something we’ve done at Intercom is bring our team along on the journey and have them involved in the rollout and implementation of this technology. It’s not happening to the teams; it’s happening for them. It’s helping them become more efficient and faster and deal with more complex queries. It’s more exciting work and not the boring, repetitive stuff they might have been doing.
A huge piece of it is helping build that excitement. And then, actually practicing what you preach in terms of not viewing this purely as a cost-cutting measure – seeing it as a way that can complement human support, allowing humans to spend more time building relationships with customers, and letting the bots take care of the stuff that was slowing humans down.
“We have to figure out very cautiously how to clearly disclaim that our customers are interacting with the bot, where that information is going, and make them responsible for opt-in”
Liam: John, what’s your feeling on this?
John: Logikcull is a legal technology solution – our customer base is very skeptical, cautious, conservative-thinking attorneys. The first question we’re working through is, “Okay, what is shared with the subprocessor? What data is shared with OpenAI?” We have to figure out very cautiously how to clearly disclaim that our customers are interacting with the bot, where that information is going, and make them responsible for opt-in and be aware of the fact that when they plug in a search string that contains potentially explosive keywords, that doesn’t live in a bubble. It gets shipped out, even temporarily, to a third-party processor. As long as we’re clear and making sure that we’re exercising due diligence there, I think it’s not going to be an issue, but we have to be very aware of who our customers are and address those concerns carefully.
Liam: I think a lot of people are thinking like that. Sam, what about you?
Samuel: I think Ruth really hit it on the head. We don’t need to look at this as a cost-cutting opportunity. We need to use this to enhance the customer experience. I don’t really talk money with my CCO. I say, “Gey, this is what we’re going to get out of it.” She doesn’t necessarily love it every time because she has to go to the CEO with numbers. But as far as the customer experience, as long as we’re driving it to enhance their experience with our product and make sure they’re getting the answers they need when they need them, I think it’s a great opportunity.
We also found success with our tier-one agents coming in and trying to get their foot in the door in the SaaS industry. A lot of times, that starts in support. And so, we’ve taken this opportunity to help them map their career and say, “Hey, you’re starting here, but now that we have automation and AI, we can provide you certain hours a week to work towards where you actually want to go in the company.” And that helps build a better roadmap for them to grow with us.
“We recently hired a conversation designer. We also have a health center manager to help build out our content to feed the machine”
Liam: That’s great. As you can see here, 78% of support leaders say they expect AI to transform customer support careers in the next five years, and that includes the creation of totally new CS jobs. Ruth, I know we’ve started to see these kinds of roles at Intercom. Could you elaborate a bit on that?
Ruth: My job is leading our EMEA frontline team, but I also have a second team of self-serve and automation specialists. It’s amazing to be at the forefront of this. We recently hired a conversation designer. We also have a health center manager to help build out our content to feed the machine. Because obviously, AI is only as good as the information you feed it. So, we’re seeing a lot of movement in this space.
Something else I’ve been discussing with my leadership team is how we can start to enable the frontline team to take more time away from frontline work because we’re able to get faster and more efficient and develop skills in this space so they can start taking on these types of roles more and more into the future. Can you allow somebody to spend part of their week building help center content or understanding bot strategies and building bot flows? It’s a really cool time to be part of this, and the earlier people get going, the more they’re going to be able to hopefully take on these roles.
“If we can trust Fin or AI to handle the knowledge gap, that positions our team really effectively to consult on how to train people to do the work themselves”
Liam: Absolutely. Is that something that you’re thinking about, John?
John: A hundred percent. This new emerging technology fits in very nicely with an existing roadmap that we have for our team. We’ve been asking the question: How do we create a more delightful support user experience and create faster on-ramps for our human experts?
We provide a solution that is crowded with vendor services. A lot of our customers are asking to outsource this stuff, and our solution is marketed as a do-it-yourself solution, so there are basically two gaps. There’s a knowledge gap of, “Okay, how do I use the tools to accomplish my objectives?” But there’s also a skills gap where customers say, “I don’t know how to do this even if I know how the tool works.” So, if we can trust Fin or AI to handle the knowledge gap, that positions our team really effectively to consult on how to train people to do the work themselves. And that’s something that AI – today, at least – isn’t going to be able to accomplish very effectively. It positions our team to be expert consultants and trainers for our users who need to become experts in this electronic discovery solution.
Liam: I’m guessing that resonates with you as well, Sam.
Samuel: Yeah, a lot of it does. Transformation is a good word for what AI and automation’s doing for support. We had our education department, and they made all the knowledge articles. That’s what they did, just knowledge articles. Now, we’ve transitioned that team into what we call digital customer experience. That’s any automation that’s not native to the product – product walkthroughs, popups, in-app hints, or the knowledge base stuff. We’ve almost made this whole new department to take on how the customer interacts with our company without talking to a human. It’s a new department outside of support, but we work with them because it’s the handoff process. It’s helping people find their niche, what they enjoy, and move towards it more.
Liam: I love that. Even now, I think about myself growing up and working in radio and not ever thinking about my title as an audio content producer making podcasts and things that didn’t exist when I was growing up.
Unlocking efficiency 24/7
Liam: Let’s move on to our third trend. Efficiency is more critical than ever, and AI is the key to unlocking and accelerating that efficiency. Most CS leaders already feel like they’re seeing value from their automation efforts, and they’re optimistic about future efficiencies. Two-thirds of support leaders are excited about leveraging AI and automation to increase the efficiency of their team in the year ahead, and 60% of support leaders are expected to reduce support costs over the next five years by adopting AI.
When we asked explicitly where they see those efficiency gains manifesting today, they said 24/7 support, faster support, overall better customer experiences, and reduced manual tasks. Where do you see efficiency gains coming from? Are these accurate, or do you think they’re other ways we aren’t thinking of yet? Maybe I’ll start with Sam.
Samuel: I think 24/7 support is a big thing. Right now, we’re an 8-to-8 business. But doing 24/7 support, when you have things like Fin going through, it’s not necessarily having humans on there for 24 hours – you have something there giving them customized responses. One of the things we notice is people don’t necessarily like being sent an article every time, but they are really responsive to somebody translating and rewording the article. So, having Fin do that for you allows you to do 24/7 support without increasing anything. That’s where we’re leaning towards.
Liam: John, where are you seeing efficiency gains coming from?
John: I spoke earlier about how my US-based team provides 24/7 support to our global customer base. That’s a huge pain point for us internally, but it’s a great value proposition – our customers love it. I think it won’t be a perfect silver bullet – it’s not going to remove the need for humans. But right now, I have folks working a full shift and then rotating a pager every night and on the weekends. And that’s draining. People need to recharge. The team is awesome, but it definitely doesn’t scale well. So, with a growing global customer base, the promise of case deflection on those very straightforward “how do I do this?” questions is huge. Even if it reduces the number of pages by a small margin, that represents more full nights’ sleep for my US-based team. We’re really looking forward to turning that on.
Liam: That’s always a good thing. Ruth, do you think these are accurate, or are there other ways we aren’t thinking of just yet?
“Even if you don’t have humans on 24/7, if you implement something like Fin to collect information along the way, when the humans do come online, they can get going faster”
Ruth: The titles are definitely accurate to me, but to add onto the first response discussion, there’s the moment when Fin isn’t able to answer something that potentially requires some troubleshooting, and what we’ve been doing is using our workflows feature. We have it set up to collect a bunch of information upfront, so even before it gets to a human, Fin’s gotten things like troubleshooting links or whatever information we need.
For anybody out there moving into that 24/7 support world, even if you don’t have humans on 24/7, if you implement something like Fin and more automation to collect information along the way, when the humans do come online, they can get going faster. And even if that customer is asleep, the human can work on it without waiting for a huge back-and-forth to happen, potentially across time zones. I love that way of using automation on top of AI.
The other piece for our teammates at Intercom is in the inbox. If they’re dealing with a customer and they’re trying to think of a succinct way to say something complex, they can use AI features to reword it, make it a bit more clear, or put it into bullet points. If they can’t think of a way to share news in a certain tone, they can ask AI to do that for them. And that’s massively speeding people up, so they’re not agonizing over every word. We’re seeing a big benefit from that.
Samuel: We’ve recently near-shored some of our support, and they’ve found that rewording is so helpful for them to make it sound more conversational, and it gets over that translation barrier a little bit. So it’s definitely powerful that way too.
Harnessing the potential of AI
Liam: Great. We’re on trend four of five. I think most people will agree that customer experience is now a key differentiator for many businesses, but customer expectations are constantly evolving, and almost 75% of support leaders believe that customers will expect AI-assisted customer service in the next five years. Support teams need to constantly up their game to meet these elevated expectations, especially if they want to maintain a competitive advantage, and AI is now adding a new dimension to this challenge.
A majority of support leaders believe that AI and automation will have a positive impact on the customer experience within five years, and our research suggests they’re right. 61% of CS leaders are already reporting a generally improved customer experience from AI, 58% reported CSAT improvements, and 66% are achieving KPIs and SLAs thanks to AI and automation. What rewards will people reap down the road? Could we see things like better retention of employees, for example? What do you think, John?
“I think the real benefit is helping people discover information in our help center. AI is like a conversation layer that helps make our content more discoverable”
John: Yeah, I think employee happiness and retention are certainly benefits we’re going to see right off the bat.
I’m thinking about CSAT, and I’d say the majority of the responses we get in CSAT have to do with the human that helped them. Like, “This rep was amazing,” or, “This agent walked me through patiently and helped me understand.” I think the real benefit is helping people discover information in our help center. AI is like a conversation layer that helps make our content more discoverable, and that opens a huge opportunity for humans to do the human stuff and create more delightful support experiences. They’re not just going to sit back and watch the bots work. They’re going to find opportunities to engage with those customers who need human support experience.
Liam: Sam and Ruth, what kinds of rewards are you seeing coming down the track?
Ruth: I’m hoping for more value added. Rather than thinking about reaping the rewards of AI via cost saving, how are we using it to add value to customers and make them more successful with whatever products we’re selling to them? That’s a huge space, and I think we’re going to start moving into more. It’s that piece around allowing the humans to deal with relationship-building or consulting and allowing the bots to take care of the stuff humans don’t want to deal with.
One thing I’m curious about with the report is, if we sent the same questions to end customers rather than support leaders, what would they think of this? Because support leaders are saying, “We’re seeing the rewards; we’re seeing CAST.” But I have an inkling that if you asked some people on the street who aren’t involved in support of using more chatbot technology over the coming years, I don’t know if they’d say yes. I think people have dealt with some pretty poor bot technology in the past. And until they start getting used to some of the excellent stuff that’s coming out now, I wonder if, the minute they meet with a bot, they’re like, “Oh, no.”
“Automation allows you to collect data that your business probably wasn’t collecting before, and it helps you identify pain points in the system that you can then take back to your product teams”
John: Yeah, I couldn’t agree more, Ruth. I think if we asked any of our customers on the street their opinion on chatbots, they’d probably say, “Well, I don’t have time to think about your chatbot; I’m trying to do my job.” Nobody wakes up in the morning and says, “I can’t wait to interact with this company’s support infrastructure.” They just want answers to their problems. And if that’s interacting with Fin, great, but if Fin can’t handle it, then it’s talking to a consultant who can help them across the finish line, whatever it takes.
Samuel: One thing that wasn’t on here was getting better data to make smarter business decisions. Automation allows you to collect data that your business probably wasn’t collecting before, and it helps you identify pain points in the system that you can then take back to your product teams. For example, “People are reaching out about these issues – here’s how we can help smooth that over.” Or, “We’re seeing people have this issue at 90 days,” and taking that to your customer success team to prepare some proactive stuff for it. It really allows you to gather data to make better business decisions without adding extra time to gather that data.
Liam: Brilliant. We asked those CS leaders who were seeing success with AI to share some advice on how they mitigated risks when implementing AI into their customer’s experiences. And these were the three that constantly bubbled to the top: put guardrails in place, route conversations to the right people, and deliver omnichannel customer service. Ruth, as you mentioned, we’ve been rolling out Fin and other AI and automation tactics at Intercom. Do any of these resonate with you?
“Think about a rollout strategy that you can easily pull back from if you realize something hasn’t gone perfectly or if you see that your help content needs more work”
Ruth: Yeah, putting guardrails in place means two things to me. One is how we went about rolling out Fin initially. We were the first internal customer for it. We wanted to start small and iterate it to make sure we were getting the experience right. We would start with one segment of customers, make sure everything was okay, and build on that. I would advise that to any other support leaders out there. Think about a rollout strategy that you can easily pull back from if you realize something hasn’t gone perfectly or if you see that your help content needs more work. You can pause it, come back to it, and if you haven’t sent that out to everybody in one big go, that’s easier to do.
The other piece with guardrails is to allow people to get to a human at some point. Nobody likes being caught in a bot loop. And ultimately, as good as this AI technology is, it’s not perfect. It’s not a human that can answer emotional conversations or super complex troubleshooting. You need to have a way out to a human being at some point. And there’s a debate about this, but I think you should be really honest when a customer is speaking with a bot. I know that on the flip of that, some people think “No, you just call it a teammate now.” And while Fin is one of our teammates, they’re not a human. I think it’s important to be honest and set expectations around that.
“I cannot echo enough – make sure there’s an exit for customers to get to a human. That is the most frustrating thing in the world”
Liam: Sam and John, what are things to consider when figuring out how to introduce AI to your customer’s experience?
Samuel: One thing we really dove into was based on what Ruth was saying – a slow rollout. We identified segments inside our customer base and targeted them. We leaned into it more in the SMB or low monthly revenue businesses. It’s easier to work that way through. And then, you’re still giving your high-value people that white glove experience you’re looking for. But I cannot echo enough – make sure there’s an exit for customers to get to a human. That is the most frustrating thing in the world. We try to limit it to four interactions with a bot before they can reach a human. But again, we plan on working with that through our different customer segments. With our big groups, maybe we need fewer. With the SMBs, maybe we can get away with more.
John: I completely agree with Ruth and Sam. When I think of guardrails, I think of staying aligned with internal stakeholders on the rollout, making sure you’re not making assumptions about how bought-in everybody is with this technology. In fact, that’s something that we’re working through right now. We’re having really helpful pushback from our legal team on how to make sure our customers have opted into Fin. We’re in a position where we can’t try to convince our customers they’re talking to a teammate. They need to know they’re talking to a bot.
And there are certain customers that, based on our agreements with them, can’t interact with the bot in any way. They’ve got to go to a human every time. So guardrails, rollout, and making sure that you’re aligned is super important. And making sure that if a customer needs to speak to someone, that’s not a painful experience. They’re not left having to navigate the UI in order to get somebody’s attention. Those are big concerns for us.
Mind the readiness gap
Liam: Finally, our fifth and final key trend. Support leaders are excited about the possibilities that advanced AI and automation will bring to their customer service offerings, but the actual practitioners are a bit more skeptical. We’re calling this the AI readiness gap. 67% of CS leaders are confident customers are ready to interact with an AI chatbot, compared to only 45% of practitioners. And this is a 22% gap. And that same 22% gap exists when we ask about the excitement of leveraging AI and automation to increase team efficiency in the year ahead. Why do you think this gap exists?
Samuel: There is that general fear of, “This is going to replace me.” That’s definitely out there. And I think it’s on us, as support leaders, to ensure we’re overcoming that. We need to make sure these people that are nervous are not getting replaced: “Here’s where your roadmap is going to go. This is exactly where you’re going to end up.” And work with them to grow past that. A lot of times, these conversations just aren’t happening with your tier-one reps. There needs to be more communication between leaders and the people on the frontline.
“If it’s great, what does that mean for your career trajectory, and how do you continue to add value to the organization?”
John: Sam, I’ve been talking with my team in group meetings or in one-on-ones, and I ask, “What are you excited about? If we turn this on, what worries you?” And I think we’re trying to solve different problems. I’m trying to solve for efficiency and headcount and scale, and my team is worried about the conversation they’re having with an upset customer. What if it sucks? Because if it sucks, they’ve got to figure out how to rescue that conversation. But maybe their greater fear is, “What if it’s great? If it’s great, what does that do to my job?” We’ve had those conversations, and the best thing I can offer is lean in with intellectual curiosity and empathy and make sure that we can talk about those concerns. If it’s great, what does that mean for your career trajectory, and how do you continue to add value to the organization? We’re not just thinking of showing up and doing the same thing every day for the next five years. How do I grow with the technology, and how do I grow with this organization?
Liam: Ruth, I know this is something we think about a lot at Intercom.
Ruth: Yeah, I echo what John and Sam said in terms of dealing with the fears head-on. If you say nothing, that’s worse. Explain your vision for the future. If you genuinely mean that you want to allow support roles to become much more fulfilling, that’s key. Most customer support people want to spend time with customers and not have to quickly move on to the next thing.
“It may take years for customers to become confident working with bots. That’s why I recommend small integrations, tiny things, either segment-wise or just one extra step you have them going through”
I was laughing when I saw this slide because I’m clearly one of the 33% of support leaders who is not completely confident about customers being ready to interact with AI. Our Intercom customers are because they obviously use a customer support software product, and hopefully, they’re using Fin now too. But I’m not sure all customers are ready to interact with it. There’s a difference between being ready and looking forward to it. I don’t know if you’d even look forward to it because something’s obviously gone wrong if you’re reaching out to support.
Samuel: I completely echo what Ruth’s saying. There are definitely target demographics that may not be ready for it. And it’s kind of our responsibility to show them what a good experience can be like. They have that seven-to-one ratio. Every bad interaction requires seven good interactions. And we’ve really got to start working on that. It may take years for customers to become confident working with bots. That’s why I recommend small integrations, tiny things, either segment-wise or just one extra step you have them going through, and then slowly increase that so the customer becomes used to it and doesn’t even realize that the bots took over.
John: I’m thinking about the recent news about the writers’ strike here in the US, and I think there are protections being sought against AI taking over writers’ jobs. It made me think about what kind of future would it be if all content were written by machines and how bland and reductive that experience would be. I think there’s an art to supporting customers, and we’re always going to need humans driving that support experience because it’s a human connection. At the end of the day, people are helping people accomplish work. AI can augment that, but the companies who aggressively cut headcount because they don’t need people and just trust the bot to do it are going to lose out on a big competitive advantage. I think about a future where bots are in control of everything, and gosh, that’s not something I look forward to. I want people to be involved in a meaningful way.
Liam: I think that sums it up perfectly. Just a bit further on that, it’s important for CS leaders to help bridge this gap, and we asked what the best way to do this was. Many suggested having open and honest conversations with their teams about AI and automation, and these are some of the questions to help get that conversation going. We talked about it a bit, but John, what are some of the ways you plan on bringing your team along to bridge that AI readiness gap?
“We have a big responsibility to take care of our teams through this transition. And similarly, we have a responsibility to use this technology really well for our customers”
John: I’m asking these exact questions in my conversation. The first time we broached this topic, individual contributors really wanted to appear to be on board. There wasn’t a lot of rocking the boat. People were like, “Oh yeah, I’m excited about Fin. It’s going to be great. AI is wonderful. Yay, go, team!” But as we continued creating space to ask the question, people slowly began to step into the dark and go, “Well, I have some concerns.” And that’s created some great conversations and points I’d not considered. This is all new, we’re all learning as we go. It’s important to bring the team along for the journey because they’ve got insights that someone not sitting in the individual contributor seat might not even be aware of. I need to hear their concerns.
Liam: And I imagine, with this all being so new, that Sam and Ruth probably feel very similar about this.
Ruth: Yes, absolutely. We have a big responsibility to take care of our teams through this transition. And similarly, we have a responsibility to use this technology really well for our customers. For all the support leaders taking this on, there’s a responsibility that comes with it too.
Samuel: And beyond just your support team. You have sales and customer success and the C-suite, and it’s all new to them as well. It’s our responsibility not to just have these conversations with our support team, but to talk to your salespeople and let them know what benefit this is going to have for customers down the line, or talk to your CEO and let them know, “Hey, this is going to help X, Y, and Z. We’re going to see gains here, here and here, and that’ll lead to these.” You need to talk up and across for all of these.
Liam: Brilliant. That’s about it for today. I want to thank our amazing panelists, John, Ruth, and Sam. Don’t forget to download the full report – there are loads more in it – and sign up for Fin if you haven’t already. Have a great day.
John: Thanks, Liam, this was fun.
Ruth: Thanks, everybody.
Sam: Thanks, everyone.
