How AI and Unified Platforms Are Transforming Customer Service | Atlassian Team 25 EU Barcelona

Hey folks, we're back at Atlassian Europe and we're here with my friend Shameek and we're gonna have a little chat about services and service collection in their portfolio. Shameek, welcome to the show. Thank you for Having me.

One of the things you guys just announced at this show is that the customer service app is now generally available, but I wanted to ask you, is customer service and IT operations help desk, is all that starting to converge now on a single kind of platform? 'cause historically we always kind of had two different things, right? Yeah.

But I, you know, across all kinds of service teams inside the company, we are seeing a lot more cohesion. Um, so often, for example, when your customer service request comes in, the support desk is in, out, it is, is in its own silo. With the existing tools, they're able to reach back out into other teams inside the company to be able to get the answers that they need to get back to their customers.

So by having it part of the service collection, the customer service management app now is able to pull data from a common teamwork graph that we have and get the answer quickly and get the best answer back to the customer fast. So having a part of the same collection allows us to pull all of that information together in a much better way. So it sounds like the primary mission is to not have the customer service person say, we'll get back to you.

Exactly. Right. And that's so frustrating for the end customer because when they get back, you have to again, talk to somebody else, and then there's a whole cycle of repeating yourselves that we want to avoid.

Yeah. How is that whole service experience gonna change in the age of ai? Because for as long as I can remember, it was, you know, somebody logs a ticket, somebody reviewed the ticket, we see if we escalated it and then we close the ticket and rinse and repeat.

Yeah. Is that gonna be a different experience with all these AI agents running around? Yeah, Absolutely.

Um, so firstly, there's a lot of, uh, queries that the AI agent can resolve automatically, right? And the second thing it can do is that it can actually ask you clarifying questions that you don't have to repeat yourself every time. And it can put all of that information and connect it with the other information it already knows about the company to ask just the precise question that it needs, rather than having, uh, that rather than kind of circling around the question and again and again like you used to with human agents, right?

So all of that is great, but the most interesting thing is that it keeps learning from both you, this particular interaction that it has with the customer, but also from its interactions with all other customers. So it keeps getting better over time, right? So all of the training that it's getting, it's not just in one agent's head, it's now in that common robo customer service agent, so that it's learning from all the agent tech information that's coming in, all the customer support requests that are coming in, and it keeps getting better over time.

Will that create a perception of memory among in the service desk? And I'm asking this question in this regard. Every time I call into some company somewhere, they, they never remember my last interactions.

I mean, it's in there somewhere. Yeah. But generally speaking, you know, it's a whole new experience and it's a whole different interaction.

So will customer service have some level of, I guess we'll call it persistence, where they actually know me Yeah. And they know my last interactions and they have a better sense of my preferences? Absolutely.

So part of the reason why every customer interaction, um, today seems like it's disparate and no, the customers have the, the service has completely forgotten about you is not because the information is not there. It's just that it's so cumbersome for the customer support agent to pull all of that information back out in just the time to be able to respond to you quickly. Right?

But with ro o and with AI, that becomes so much more automated and fast, right? So the RO customer service agent is able to pull together all your past history, summarize it in just the right way, whether it's resolving the problem or whether a human agent is actually resolving the problem, it knows and brings all of that data together in just the right personalized way to be able to service you in a much better way. Mm-hmm.

Um, what does it take to put all this together? Because some folks would say, well, we're heavily invested in all these other platforms. So if I was gonna migrate, what would that look like?

And how big a how big is the lift? Yeah, I mean it's, uh, usually most customers have a customer service management system where they have all their customer records. So what you can do to get started is just point our customer service management app to your set of customer records and your set of order, um, picking systems and entitlement systems without replacing what you already have.

You could say that, Hey, these kinds of queries are coming into our customer service management app, and thereby start incrementally, right? And then as you see it performing better and as it learns more and more about you, you can start expanding the number of queries that it gets to and the categories of queries that it's responding to. So I think we have designed it in a way that you can actually get started small and then expand over time, right?

So it's a, it's a pretty easy lift in terms of how you get started over time. Of course, you can start migrating more and more systems and customer support categories over into the CSM app, and the more you move in there, the more context it has, the better queries it can answer. In the age of ai, will we wind up restructuring many of these teams?

'cause right now I think that, you know, if there's level one, two, and three escalation, and it's like a pyramid at the bottom is mostly level one and then it gets smaller and smaller, but will a lot of the level one stuff be handled by an AI agent now and then I can reallocate my resources accordingly? Yeah, Absolutely. Um, there's a whole bunch of tedious queries that come in, right, which are mostly about just informational gathering and about, you know, where's my order, what happened to my, um, payment that got stuck and so on where the information is already there in the system, and then that just needs to be pulled out and given back to the customer, right?

Um, a lot of that is already moving to self-serve as well, so customers can self-serve themselves, but whenever a customer needs a query that's slightly more concept that I would call tier one. That's where I think AI is making a lot of informa, uh, dent right now. And these are tedious tasks that no human really wants to solve because it's just a matter of looking up the data here and then answering it back.

Um, those are areas where AI can do a fantastic job already. Um, and then for the more tier two and tier three category, um, queries there, the AI agent can provide an assistive capability. It can summarize all the information of the past contacts with this customer and provide it to the human agent in a summarized form so that they can take action much more quickly.

Mm-hmm. How do we maintain the personal touch? Because sometimes you worry with AI that, you know, it all just becomes talking to a machine, but, um, is there a way to do this smartly so that people feel like, you know, somebody does still care?

Yeah, So there's two things. Like one, as long as soon as we take all the drudgery out of the task, it aligned frees up the human agents to do all the more, um, the software aspects of the contact, right? So what we wanna do is that when a person, when a customer is actually interacting with our customer service management app, we should be very clear about when are you interacting with our AI agent and when are you acting, interacting with a human?

So the AI agent looks at all the questions that are coming in and knows that this is a particularly very, um, a very tedious kind of an answer that it needed. And there it says, Hey, I'm answering this for you. Do you want some more information?

And if it sees that the human is looking for a more, um, complicated question, then it can easily figure out, or that the question is getting very sensitive, right? Or that, hey, it's going to, it's going to a loop with the human on the other side, then it can, um, escalate the problem to a human and be very clear to the customer that, look, now I'm not able to solve the problem for you. I'm coming over to a human.

And there, the human agent can come in and provide the software, touch the emotional, uh, support that the customer might need in that particular case. But, so this elevates the human agents to do the hard things, right? And it leaves out all the tedious things for the AI agent to be able to solve.

One of the things that is notorious about being in the service field is turnover is really high. Yeah. Do you think that that will become, uh, less of an issue because we won't be maybe burning people out as quickly?

Absolutely. I think that that's a, a pretty important part of this whole journey that this industry is going through, which is that, um, we really want to make sure that all the drudgery of that job is taken away so that the human agents can actually be working on the most, um, rewarding parts of the most value added part of, um, this particular role. Yeah.

So what's your best advice to folks today? You know, what do you see folks who are running service operations doing that makes you shake your head a little bit and go, folks, maybe we might wanna be a little bit smarter than that. Yeah, I mean, I think, um, first of all, adoption of AI is I think here and people need to kind of embrace what's happening and the change that, um, AI is enabling because some of our customers are getting dramatic results by adopting ai, right?

So just being more receptive to understanding what's happening and trying it out is, I think one thing that, you know, I would encourage all customers to do. The second thing is AI is only as good as the knowledge you have in the company. So investing in more knowledge and putting all the information of your company, for example, um, what are my res, how do I respond back to a customer that has a payment failure?

What are my processes for handling, um, a delayed order, right? These kinds of things are often not documented well, and there's no business processes that are well established. The more the companies invest in this, creating this kind of context and knowledge, the better.

Not only do their AI agents become, but also the human agents become much more powerful. I think a lot of folks would be concerned that the customer service agent might hallucinate. So are there guardrails that I can put in place to kind of prevent that from happening?

Yeah, That's a very good question. So two things like, number one, we encourage customers to start with the, the, the easier queries first, right? And to set and keep the settings so that, um, the more complex queries are going to the humans.

And the second thing is that we provide a lot of control mechanisms so you can review all the answers that the AI agent is providing and coach it much like you would coach a new, um, human customer service agent to get better at their job, right? So you can review all their answers and provide feedback on what went well, what didn't go well, and what a better answer would be. Thirdly, we provide what we call an evaluation system where even before you deploy it, you can, we, we provide a whole bunch of test, uh, queries and what are the suggested responses, and then we test the, uh, customer service management agent to see whether it's actually performing well and what the score is, right?

So you would never deploy it unless you vanish to kind of tune it to get to a good score. Very similar to how a human agent comes in and there's a training period, and you wouldn't actually put them solo onto the, um, customer service, uh, task queue until they've actually met a certain threshold. Mm-hmm.

In a lot of cases, people are using their customer service desk to upsell stuff to customers. So would the AI agents be able to do that as well? Eventually?

I think that's, uh, a place where we can get to, um, right now the, the focus of our app, and I think most of the industry has been to resolve the contact queries that are there, but upselling is definitely an area where I think, um, this whole field can get to. One of the other issues that we have too is like a lot of the times people get a call about something, but it's not really their issue or it's related to some other company's thing that is dependent upon my thing and it, they all interact. Can the agents start talking to each other from different companies that are maybe part of the same solution and kind of resolve things?

Yeah, absolutely. Um, there is obviously these, um, innovations that are happening in what's known as the MCP communications between agents, um, and also a to a, which allows agents to communicate with each other. These are areas that are still very relatively new and the, uh, connections between companies are still getting established in this area.

But this is an area that absolutely we expect that if my company's service depends on another company's service downstream, then our agents should be able to talk to each other to resolve those issues. We see that already to some degree in the observability space. Um, but in the field operations, manufacturing, retail, and other spaces, this is still relatively new.

We haven't seen a whole lot of that yet. Yeah. So this sounds a lot better than the robotic AI type of experiences we've had so far with various chat interfaces that people have put together.

Um, as you kinda look down the road a little bit, you know, what are you most excited about? I think there's, uh, two, three things that are really exciting. Number one is, as you mentioned, agents working with other agents, whether it's inside your own company or whether it's outside, um, making that work well would really empower what we can do, because many of the issues are not dependent on what I know, but what other teams are de, you know, are doing as well, right?

So that's one area where I think once we have that whole framework working will be even more powerful. The second thing I think is really happening already, but can go, um, is likely to go even faster, is the quality of the response is getting a lot better. And what I mean by that is it's not just text and chat, which used to happen before, but other forms of media, for example, voice.

Um, so being able to talk to somebody in voice and get back a voice response that is easy to make sense of, there's no hallucinations, the quality is so much better that, um, we are seeing significant improvements in the last year, and I expect that to continue getting even better, right? Mm-hmm. And the third thing is adding video and images to your answers also makes the, the answer so much more real and easier to understand that.

I think that's, um, another area where I expect a lot of innovation happening in the next year. Do you think that people will develop a relationship with the AI customer service agent because they'll perceive it as somebody who's regularly helpful, somebody who remembers them and they'll start to, I don't know, assign personality traits to it? Yeah, I mean, I don't think that, um, I don't know if they'll be assigning personality traits to the customer service agent necessarily, but I do think that the trust and the expectations of what you can get from the, um, customer service agent on the other side is gonna go up significantly as they experience it more and more and they get really high quality instantaneous results back.

Um, they would prefer getting that answer first and only when that fails would they fall back to a human agent. So that trust level, I think inevitably is gonna go up and, uh, thereby their, uh, expectations of what can, what customer service is, goes up significantly over the next few years. Alright.

I want to come back to another point you were making about, um, making sure I have my knowledge bases in order to make the AI work better. What from your perspective do organizations need to do to accomplish that? Because I think, you know, it's hit or miss sometimes in what's in those knowledge bases.

Yeah. So two or three things like, you know, one is being better about documenting your own business process and your policies and your, the, the way you respond to customers. What is the tonality you use?

Just being more explicit about all of that, right? Many companies have their own training manuals, not just for customer service, but even for employee service, right? But sometimes those documents and those policies are scattered, um, they need to be brought together, condensed, cleaned up, and so on.

Having said that, not too many companies are going to go at it from scratch, right? You know, if I have to build all of this knowledge from scratch, many companies are gonna just throw their hands and say, Hey, that's too much work, right? So we can apply AI even to that problem, which is to help suggest to companies, what are the questions that you're coming in from past responses that you have given to customers?

Here's a likely set off answers and knowledge that we can generate for you and suggest for reviewing, right? And then you can, with very little work, you can review it, clean it up, and then say, Hey, this is good to go, right? Because even though many companies don't have knowledge bases, they have a lot of history of past tickets that have come in how you've responded to them.

Some of them might have been good answers, some of them might have been bad answers, but AI can help you summarize all of that, cleans it up, and also categorize into good, bad, you know, what are the right set of answers that I want to keep as, uh, templates for all future answers. There's one school of thought that says every dollar spent on customer service is a dollar that doesn't go to the bottom line. And I guess, can we have a different attitude going forward where we think about investments now because the cost of the service is gonna drop dramatically?

Yeah, Absolutely. I think this actually, um, will encourage customers to actually spend more on customer support, because right now, as you mentioned the beginning, right? Customer support is not just a cost center, but also a place that of, uh, that leads a frustration for customers.

Customers don't have a very good impression of their vendors because they feel like, you know, customer support just doesn't provide them the answers they're looking for, right? So as customer support gets better by this combination of automation and humans, it's going to elevate the value that customer support is providing to every customer that every, uh, organization that has this capability, right? So it's actually gonna help improve your customer satisfaction, reduce your churn, and thereby lead to more revenue, right?

So I, it's, it's not just with ai, even before, companies that have invested highly into providing better customer support have always had better customer satisfaction and therefore better retention rates, right? And this is just, um, gonna improve that even further. All right.

Hey guys, you're heard in here. Customer service is gonna get great soon. Yeah, Absolutely.

Thank you. Thank you. We'll be back in a minute.