PegaWorld 2025: A Fireside Chat - U.S. Bank's Operations Transformation Journey: Customer Service with Pega Voice AI

PegaWorld 2025: A Fireside Chat – U.S. Bankʼs Operations Transformation Journey: Customer Service with Pega Voice AI

What I want to do is I want to start off with, we've got Jeriann and we've got Jason here. I'm going to have them run through a few background and introductory slides so they can talk about who they are and what they do. And I'm going to pass over to Jeriann to kick it off. So let's make sure we got the right slide. This is the three of us pretty pictures. Here we go. U.S. Bank corp. Yeah. So welcome. My name is Jeri Anne Larck.

I have the joy and privilege of working for US Bank, and I'm a senior vice president leading our platforms organization that is really focused on all things transformation between our operational services business lines and our technologists and engineers. So really working to bring those experiences to life for both our customers and our internal employees. So really important to know U.S. Bank as a company, great company to to work for.

As you can see, some of the metrics, they're really both regional, national and international coverage focused kind of across upwards of over 2100 branches. You'll see, you know, six, 678 billion in assets and really founded have a real strong heritage founded in in 1863. So a highly effective, highly ethical, really grounded bank. And super excited to be here and talk to you not just about how we keep those Guideposts, but also about how we're innovating in the technology space as well.

A really key fact here is, and we're going to talk a lot about this today. We are funding and really focused in on employee experiences. So when you think about that right now we have over 70,000 employees. And those employees are really focused not just on direct customer engagement. They're also focused in on our shareholder experiences as well as deeply serving our communities in every area that we're present in.

And so Voice AI becomes just one component of how we help bring that human experience to life. What sets us apart from the rest? We'll say we've got a strong dedication to customer, strong dedication to human interaction, focusing in on our our people, enriching both their lives and the lives of our customers. We are also highly innovative in focusing on the future. So both current path ahead versus looking at five, ten, 20 years out.

And again, we believe that much of the discussion we're going to have on Voice AI hits on a lot of those key components. It is about helping our customers just as much as it is about helping our internal employees and really focusing in on regulatory adherence and financial discipline with a strong background in in ethics. Awesome. Jason, let's talk about your role. Hello, everybody. I'm Jason Ouimette. I am the director of customer service conversational AI.

So we'll talk about Voice AI as one of the products that I manage. It'll be funny because if any of you attend my session later, I also manage a product where agentic self-service. So I have a product that cannibalizes the other one. Um, but, uh, you know it to. When I joined Pega, we started with Voice AI. And you know, when you look here, we talk about transforming the Asian experience. And here I am saying the bad word.

We're not allowed to say Asian anymore because agents are now automated robots. We transform the employee experience, uh, the, you know, our goal and I came in to join Pega was really to make sure that we created the best experience possible for the for every CSR using our application. And so when we use Voice AI, we're, we're trying to guide the CSRs to the right part of the interaction. What are the right case types? What do they need to do? You see the last bullet point here.

The focus point with that application is to make every CSR the best CSR.

And more importantly, what when we look at the technology and you see the new things that come out, like if you watched our Innovation Hub demo last year versus what you see this year, you'll see a lot of things that were introduced because we can adapt and we can put in more items and we can take a CSR that might be two weeks into their job, but make them just as competent and just as capable as someone that's been on the job for ten years.

And that's what we're really focused on with the toolset to make them available. We want everything in that desktop to really drive them towards success. Dan, we did literally change the slides yesterday and had to take the word agent out in a couple spots because it's now confusing people in terms of this whole what's an agent versus what's a live person conversation. It's definitely a terminology shift that's been a little bit challenging.

But when we when we say CSR or representative, just know that's indicative of what you typically would call a contact center agent in a contact center, that's what we're referring to. Yep. So when you look at the we'll say conversational AI capabilities, these these things that we have here work regardless of the channel that you're using on Pega Customer Service or any of the enterprise applications that are built on top of Pega Customer Service. The first is case suggestions.

We are it's always listening. It's taking the conversation data, and it's directing the CSR to the appropriate workflow so they know what they need to do. They don't need to guess if you're you have a brand new CSR and you're like, well, what am I supposed to do? What is the step? This technology listens to the conversation. It makes that suggestion. And you'll see a slider here that kind of talks through that. The other piece of knowledge suggestions.

So you know, last I'm sure you've heard Knowledge Buddy. If you haven't I'd be shocked. But we have this great knowledge tool called Knowledge Buddy. But we also have a great knowledge product called Knowledge Management. We can suggest specific articles if you don't have Knowledge Buddy or if you do have Knowledge Buddy.

We really have a transformative integration in the sense that we can detect the questions that were asked in the conversation and then present that to the CSR so they can make the decision of whether or not they want to click it, or if you've got new CSRs that aren't very skilled, you know that they're they're not very knowledgeable in a specific topic. Perhaps there's a new policy or a new item.

You can have it automatically fetch the answer and present it to them so they don't even have to go to click to get it. It's all available within the application. Um, the other piece is form fill. Um, you'll, you'll see a slide of this where there's fields that are automatically filled in. It's a cool technology. Um, hopefully I'm at liberty to say that U.S. Bank is leveraging it, and it's not one that will save a significant amount of time in interaction.

It's not one of those things that gives you this big average handle time savings. But what it does give you is this transformative employee experience when I helped roll this out at other contact centers and I do employee surveys, right. I want to see how they're interacting with this application. The thing that was amazing to me was that just that filling of data that they felt it was magical.

And the most important thing was they got this impression that the company was investing in technology to support them, not replace them. So that little piece right there, it's it's cool. It's great. It's not the item that's going to make all the impact in your contact center, but it will make an impact on employee retention and employee satisfaction. It's a big piece there. Well, and it also helps. This is the thing I always liked about it. They're not worried about the typing element.

They can actually be listening and engaging with the customer and and more in touch with the customer instead of worrying about form filling. Yeah, but the next bullet point is really, really the bullet point for that, that I would say. I mean, there's many technologies out there. Almost all the contact center technologies and other pieces cases have an interaction summary. We feel like we have a little bit of a leg up because it's tied into the workflow. They can edit it.

It's not something that comes at the end, but this particular piece is one of those items that just did what you just mentioned, right? When you have interaction summary, I can't tell you how many contact centers. And if there's anybody out here that says that your your CSRs aren't capturing notes on their calls, I would I would be very surprised. Right. You see, all these CSRs are capturing notes. They're having to put it in place.

And what they're doing that they're not focusing on their interaction. They're focusing on taking notes. And the beauty with the interaction summary is we're taking all that conversational data, and we're generating a summary at the end so they can do what's important. They can focus on the conversation. They can handle that interaction in the most effective and efficient way possible. And that's a big drive with that in that particular piece.

And then last thing is an item that you'll see is what we call conversational analytics. We use generative AI and we have some out of the box problems. But you can go ahead and configure it any way you want. We have some out-of-the-box metrics but we have an opportunity to provide scores. So like a 1 to 10 level. How professional were they or what is the likelihood that this this interaction is led to no more interactions calling it's a resolution score.

Or you can ask boolean questions like the one that we ship out of the boxes. Did the CSR use profanity on the call? Right. I mean, that's a pretty important factor. Um, you know, you want you want to know that. And if that flags. Yes. Okay. Well, that's one we need to listen to. We check for sentiment. Right. What's the sentiment score. And then the other piece that you can build in when you talk about the analytics is coaching.

Um, we can give one of the out of the box items we give is professionalism coaching. And it will give a short snippet to the CSR as to how they can improve or what they should be cognizant of in their next interaction. On top of that, we provide reasoning. So there's a little info icon that you can see, and it gives them a little bit of confidence in the score about what they're working through. So these these key bullet points here are just they're a big element.

And if we go to the next slide you'll kind of see an outline of it. So, you know, at the top we have dialogs that can be used for what we call script compliance. You probably want to focus on consistent brand messaging. Other items you know maybe there's some disclosures that you need to be read. We can we can use script compliance to be able to track that. We have suggested actions in the bottom left, where I talked about guiding the CSRs to the right workflow. That's what we're referring to.

This pops up right at the bottom. The CSRs know where to go to look. It's consistent. Um, some applications I've seen can have up to like 70 different case types. Can you imagine being a new CSR, logging into an application and have to pick from 70 different things of what you got to work through? It's be really challenging. This helps guide them to the right place. That form fill. You see those little purple yes no question options.

That's data that was automatically collected on a form that they can then click yes, this is the right data Voice AI or messaging. I heard this or detected that information correctly. Let's fill it in. And then to the right is that question detection. In this case we have an auto answered question. We identified the question and fetched the answer and present it to the CSR immediately. Here's a quick snapshot of our wrap up screen. You can see the interaction summary on the right.

That's that piece that helps you save so your CSRs aren't capturing notes, aren't putting all those pieces. And then here is the feedback item that we're referring to where you have a number of items that have scores. You have that boolean question. Did they did they use any profanity. Um, and then sentiment. And as well as at the bottom piece you can see that professionalism coaching. And again those are the out of the box ones. Those are the ones we shipped with.

But we knew that could be effective for almost any contact center. They can you can disable it. You don't have to show those. The other beauty to this is that some of these metrics are can be exposed for real live interactions, and others can be exposed for what we'll talk about.

Hopefully we'll have a little time at the end here about our customer simulator, where when you start to onboard a new employees, you can have metrics that are specific just for them, because they might have a different item that they're being scored on versus your your CSRs that are live on the floor. Okay. Great. Thanks, Jason. So Jeriann, let's talk about the contact center, the actual location.

Give me give the audience a little bit of background in terms of where the customer service and the Voice AI is actually running right now. Yeah. So really us stateside and we're talking multilocation. So, um, the portfolio that we're directly using this with right now is our credit card portfolio. Um, so locations, various locations across the US, um, both on site and virtual, where this is being used.

Um, our primary focus of this was really to look at employee experience improvement and customer experience improvement. As Jason mentioned. Yes, there are key attributes that come with that in terms of efficiency and handle time improvement. That does help the bottom line. But the goal here was all about human interaction and the improvement of that human interaction within our contact center. Platform we we are looking at just upwards of about 1200 CSRs in our our goal by the end of Q3.

So right now we're running about 2 to 300 and we'll continue to scale that. I will tell you, it is it has been an iterative journey to really be able to say, we're starting in this space, and then we're going to learn and grow and iterate our way through the experience as it relates to, again, that human connection. Because again, this is we're always dealing in two humans is what I like to say. In contact Center, you have an employee and you have a customer.

So you have a two human touch on every interaction you're having. Yep. Well, and I think it's important to understand, based on what you talked about the 12 ultimately rolling out to 1200 people. So the Pega Pega is providing the customer service desktop. We've been partners with U.S. Bank 20, 25 years maybe a little bit longer. 26. Wow. Wow. See? And Jason didn't even even know that. Didn't even know that. Right.

And and Jason worked very closely with them from the product perspective to make sure, as we're rolling this out, that we were in lockstep together with U.S. Bank as we went through that particular process. And we're not because we're the entire desktop, obviously, we're doing all customer service things, but we're doing more than just customer service at US Bank. What are some other use cases that we have going on in your shop? Yeah.

So we've got a strong partnership strategic partnership with Pega. So not only is our contact center kind of core system of record on Pega, we also have a very large and vast claim process, which is our fraud and dispute processing that kind of sits across two platforms. And then we're also in the space of our complaints management. So again, kind of more of that complaint identification through into case management of the complaint and resolution.

And then last but not least, we also have some of our collection servicing on a Pega platform as well, right? Yep. So broad use case, broad adoption again. Long term partnership. You know, this was the perfect marriage in terms of being actually the first bank to roll Voice AI out. So super exciting. Yeah. You guys are blazing the trail from that perspective. It was helpful.

I mean, when Jerry and I, when we worked together and some of the members that are at US bank team members that were out here, it was enlightening because there were items that when we went to roll it out, we identified, hey, there are tweaks that we can make in the application that will make this adapt a lot easier, right? That'll make it a better workflow for the CSRs.

And it was it was great to have that partnership to work through that iterative process to to find out where we can build even more efficiency and make an even better solution. Yeah, great side by side work on both on both pieces. So all right, so we're rolling out in pilot mode right. This wasn't a big bang. Started ramping up. Talk about what you were looking to achieve really with the pilot.

Why did you go why did you go to Voice AI in the first place? What were you looking for? What did you find out as you actually rolled this out? So I think the biggest thing we were looking for is again, back to that. How do we improve, you know, human experience. And I think the more and more we take what I call simple workflows and build them out in a do it yourself space, right? So we give customers a ton of opportunity to digitally interact or interact with an automated voice response system.

But then what does that leave you with in a contact center? It leaves you with more complex and sometimes more emotionally driven customer interactions. And so if you can give agents my apologies, CSR. You're allowed. To say I'm not sorry. Yeah, we're all going. To have to break that habit. That's going to be a tough one. Break the cycle. But if you can give them tools that again are additive.

These aren't tools that are in replacement of they are additive to the CSR to be able to help guide that conversation. So if I'm talking about a complex situation and a customer is emotionally driven right. Let's take maybe a situation of fraud. The customers lost their card. They need it replaced. They have transactions on their account. Someone has changed their address. It's been a full on identity theft situation.

We could actually then begin to guide that that CSR through that experience, through case suggestion, through also offering them in a highly regulated environment, some coaching around scripted appearance. So you increase efficiency even in quality and control. And then you move into things like knowledge. Suggestion.

The auto form fill has been really powerful to most of our humans, and probably the most magical that they would tell you, because that first instance, you're having a conversation. Instead of me trying to take notes and listen to what Jason's telling me, I'm actually focused in on what's going on with the customer, not taking notes about the address. They just, you know, shout it out to me in five seconds, along with replace the card. And my card was lost. On January 5th. And on and on they go.

You've got a transcript that helps keep that. You have a case suggestion queuing up work that says you need to do a card replacement. You need to do a manage address. Um, so our intent was really making the life of our employees that much easier. And we knew that would drive customer improvement as well. Um, ultimately it is starting to drive some efficiency gain in handle time improvement as well. Um, and our goal was to really pilot that because. Right.

It is using, uh, you know, what is for some a scary thing called AI. Yeah. Um, we'll talk a little bit scary. That's not scary. Well, it's funny that you say that too. I mean, you know, with with the implementation that's in place right now at U.S. Bank, they're not using generative AI, but yet they're still able to get these gains, you know, and I'm glad that you touched base on it because, you know, shame on me.

I pointed out, you know, that we all know that if you have happy CSRs, happy representatives, they're more than likely going to give you a much better customer experience. They're going to they're going to represent your company in a way that you want it to to. And, you know, I'm glad to hear that.

It's having, you know, that we're seeing that effectiveness because that was one of the goals, right? If you make them happier, they have a better experience than they're able to put their focus into getting what they need to do. And when we talk about the AP, sorry if I'm jumping ahead here, it's just we haven't gone for the big gains. You know, we're, uh, we're they're they're not utilizing Generative AI yet.

We hope to be able to use a lot of these cool things that we just showed on these slides here. And when they do, I mean, it will be a big transformation change for them and the the gains that they'll be able to gain out of it. I think a key that I would ask all of you to pick up on that is this isn't an all or nothing. So to those points, there are components of the I itself versus Generative AI that you can use.

So in the spirit of could we pick up and use things like auto form fill or case suggestion or script adherence. Yes. Um, we even learned from many of our employees, and we rolled out with a little bit of a larger audience and found there's a ton of emotional and human connection and coaching needed as you roll this out. And so the ability to actually engage with those people in an informative coaching type of way was really important. And so we started to throttle and learned quickly.

We needed to be supporting more on the people change management side and really caring for how the people were dealing with the change. And so that caused us to pause a little bit. Again, we were learning, willing to kind of learn as we go. We paused a little bit, did some surveying with those those employees, and really found what was giving them improvement, but also found things that were area of concern for them.

Um, we had some employees who were almost trying to prove the AI eye wrong, for lack of a better way of saying, I never imagined that, that there would be employees going, well, I'm going to prove this wrong. It's not going to fill the address right for me. It just can't do it. So we had some of that that was occurring as well. That kind of caused us to say, let's let's rethink how we're handling the people management side of this.

Um, another key factor I would say is really, as you're identifying some of your pilot participants use, you know, use some surveys to understand who's passionate about AI, who's interested, but also use those surveys to find out there is a population of people who is afraid, who are afraid. Deathly. Afraid. Deathly. Afraid. Yes. And so that doesn't mean then, that you don't roll out to those humans.

Instead, what it means is how you roll out to them and how you care for them in that process is going to be different and needs to be more tailored. Yeah. Well, and we said this, I think at the beginning, this is additive. This is not intended necessarily to replace people. This is intended to make the job easier for the CSR. Got to get the right term there, the CSR, the representative, but also really kind of to your point. And I used to run contact center roundtables with with banks years ago.

And we talked about this concept of we are taking all the easy stuff off the table. The things that roll into the contact center are, in fact, the tough, emotionally charged elements that are there. And if you've got somebody who just came out of training, maybe has only been on the phone for two weeks, you really do want that experience for your end customer to be almost as good as that ten year employee? Yeah. You don't want them to know that there's a difference.

You don't want them to know there's a difference. You want to provide that great service experience. But I think your the surprising comment you made to me as we were preparing for this was not only is it additive, not only are you paying attention, but one of the surprise outcomes of this was in fact employee retention. Do you want to talk about that? Yeah, 100%. So we've had a great set of retention within our credit card portfolio. Frankly, we've not had a hiring class in almost over a year.

So when you start to think about additive tools, you can give your employees, right, who again were focused in on them. We are investing in them. We're giving them a sense of their own employee satisfaction and ability to again meet them where they are. We're all diverse human beings, so we're trying to meet them where they are. Again, if you're a more tenured agent, I'm not going to present all of these things to you.

But if I'm new and off the street versus been here for six months, we have the ability to to kind of throttle up and throttle down what is needed to support those, those employees. And that's not just through Voice AI. That's one component, but open openly. It's within our customer service framework as well. So we use quite a bit of I would say there's a lot of tentacles that are out there relative to how we are actually engaging with automated workflow, how we are using rules based processing.

We're driving automated UI Voice AI. All of those things are being stitched together, along with various integrations with other strategic partnerships, to really invest in our employee experiences. And the more we're investing in those employee experiences, the more satisfied those employees are and the more they want to stay with us. Bank. So I'm ashamed to say I had no idea that it actually improved.

I didn't want to bring it up the retention because, you know, when they told me about what their attrition rate is, I almost want to stand up and clap. I've been in the contact center space since I was a 17 year old kid, and I mean to not have a training class in a year. It's incredible. And the. Fact that you're still improving. 50% turnover. Right. And I'm bringing this up because I didn't.

One of the biggest things that you will see with, with the conversational AI technologies is the retention gains that you get from it. Um, you know, it's one of those value adds that we don't think about, you know, you'll hear a little bit about with customer simulation, but, you know, if you can keep some of we have some customers that have had attrition rates as high over 100%, which means they're they don't all their employees don't even make it a year in most case. Right.

They're continually rehiring multiple times in a year. Um, you know, if they're able to keep their employees for just two more months or three more months, what does that mean to their organization? It could make a huge difference, right? Um, but the fact that you are able to still see a benefit, despite how good your attrition rate is and how well performing, it's incredible. I didn't know that. I'm actually really excited to hear that you were still able to see it there.

That was news to me here. Yeah, we had some of our our CSRs who were also right. We've got a very, um, very well groomed and maintained customer service Platform. And so even as we rolled out Voice AI, they were like, really, can this help improve things? I have so much guided workflow already.

What can this really do for me? Well, it can really allow you to focus on the customer, not on your notes and your scripting and your double checking what disclosures you have to read in the banking environment, regulatory environment today. So it really does focus you back on the customer, which again is just powerful on far too many levels. And you all obviously are in financial services and probably in contact centers. So I believe that probably resonates really well with you as well.

Definitely. And you can't just turn it loose. You know, it's got to and it ties back to everything we're talking about where the process really is at the center. And this is supporting and sitting outside of that. All right. So let's talk about what's what's your ongoing cadence looking like as as you're continuing to roll this out. What else are we rolling in from the product perspective. Because we didn't, you know, roll everything into the first round.

So what what did the next couple of things look like coming down the pike. Yeah I mean I would start first with saying we are actually also concurrently. And I share this because I think many might be in the same situation. We are going through an upgrade process. And so what we could have done is easily just said, wait till the upgrade is done, then we'll consider Voice AI we didn't. We said the path was we need to start.

And if we start and start slowly right and grow within that product set, we can start to see some of the benefits of that while still doing all of that routine upgrade and maintenance and the goodness that you still need to do across any of your Platform health. And so what that meant is, in all the bells and whistles Jason showed you, we we were picky about what we were going to do. So we picked 2 or 3 things. We started there. We didn't launch with, again every every service advisor or CSR.

We chose a smaller subset. And again we're sitting at about 200. Um, what we did do as well is we began to tailor how we were coaching those employees, and we began to iterate on where would auto fill be used. So auto fill wasn't used across all of our contact center. We call them service intents. Many of you probably do as well. We were picky. We said, let's use it in payments. I make a payment flow. You're doing that almost daily in the credit card industry, right? So make a payment.

We're going to use that and manage address. We're going to use it and request a card. So you can do something as simple as say get started, get started with one of the use cases and get started with one of your highest call volumes. Just start there and see where that takes you. Yeah. And then I will say, uh, my experience with your group when I've got to give them kudos for it. When we started to look at the intents that we wanted to service, we went through an exercise. Okay.

So what are the things that could be stated and not be stated? And their group came up with this brilliant idea. I mean, it was it was astounding. They they basically put up a PowerPoint presentation on a team session and I called it The Hollywood Squares. I'm sorry, that shows my age. But you know, and, you know, okay. What things that that would be said, things that wouldn't be said.

And we collected it all out and we created this, this very efficient form of deriving what we should be looking for to make these suggestions and put it in place and, and had that training all well established. And it was, it was really, uh, creative and efficient process of getting that place. And we were able to put the focus on the areas that we thought would be most impactful. It was it was extremely efficient. I thought it was a great way to go about it.

And, you know, um, you know, I hope I, we provided Voice AI on a version that technically we don't truly support, but. Yeah, for Voice AI, but, uh, we but in the partnership, we were able to make it work. And as a result, you know, we put it in there were, you know, we, um, we had a couple of things that we had to adapt to make it work for that solution, but we were able to do so successfully. I mean, it was it was a little challenging in the beginning.

We had some items that we had to work through. Um, but we were able to get that in place. And, and, you know, it has been great to see. I think a lot of that for me comes back to the power of of product connection, right? So Pega product, U.S. Bank product, really working together to say this is all about the customer, right? This is all about the employee. So how are we going to make that right. How are we going to be accountable to each other. Right. Jason. Just as much as my team.

Um, you know, and I'll give a shout out. We've got a few in the room. Nate Fineman and Piyush. Wave your hands, please, if you want to talk to some really intelligent people on Voice AI and what we did at US bank. Stick around and see both of those gentlemen. They did a phenomenal job. And again, it was more, how do we iterate and learn from this process? Because it was not it was not perfection.

Um, and I fear right now in our society, there are times where it's I need the perfect, I need the big bang, I need you don't you just need to get started? All it's going to take is one use case. And for you to commit and devote your time to that use case. Amazing things will happen. And while you call, you know, you point out Nate and I mean, it speaks to the partnership that we had so far. I mean, it was true.

I mean, uh, you know, the US bank team pulled me into their roadmap discussions and said, hey, here's what we're thinking about doing. What would you recommend? And it was it was very I think it was very impactful for your team.

And I think it was impactful for us because I was able to get insights into their approach and their ways of thinking and find out different ways of delivery that I can communicate with our partners, with our consulting teams, and other ways of how we can make this a little bit more successful.

And as well as just identify where their pain points are so we can build a more compelling and easier to use. Because it ultimately impacted the way you looked at product development on the Pega. Side.

Of course, all the way across, I mean, it was a it was the best thing a product owner could ever have is having those types of discussions, because it really is enlightening as to what you can learn. Yeah. So I know we're still early days and we're still rolling out and pilot and going. Any results? Verbatims what you know, anything you can talk about that's. You've. Seen been beneficial impactful. Yeah.

So again with the CSRs that are currently on in using Voice AI and again, some of the subcomponents of Voice AI, we are seeing an average of about eight seconds in handle time reduction across the board. So that's pretty pretty big in terms of seeing that improvement. We're also starting to see some customer satisfaction improvements. So about about a two point improvement in customer SAT. We're not seeing any major impact is in terms of transfer rates.

So at least good there as well that the product itself isn't driving misinformation. That ends up ultimately in a transfer, which ends in a poor customer experience. So transfer rates have been extremely stable. Again, the small set of agents that we've been working with, when we made that decision to roll and we made that decision, uh, a little bit around the holiday period, which we learned a whole lot from, uh, by the way. Uh, but we pulled back from a few of our employees.

And here was the crazy part. They all said, absolutely not. I want to keep that. Why are you taking that away? Right. So anyway, a lot of the verbatims that we've been getting are more about, thank you for giving me a tool that does allow me to focus on the customer. Um, so some of the key things as well that I would say some of our agents, um, you know, so, so cool to see U.S. B

ank investing in agent tools, something so innovative really excites me and makes me want to come back to, to work every day. Uh, the coaching that was given to me in terms of what is AI and that helped calmed me was extremely important. And now I'm able to trust the tool. This allowed me to focus on conversations versus remembering what customers were saying and trying to deal with those those details at a later point in time. Wow. The bank is really investing in me as a human.

So those are just a few of the comments that we're getting from some of our recent CSRs that have have received the Voice AI I pilot. Any learnings surprises in this rollout? I mean that those are all great things, but everybody always if I don't ask this question, it's going to be asked here, which is, okay, what do they need to know that you didn't know at the beginning of the product that you learned that they need to know before they get started? Yeah.

Number one is this is a big change for people. So investing the time in what what the diversity of those people, those humans need to be effective in using AI is really important. And again you're going to find different populations of those people. So be diverse in how you approach them. It is not going to be a one size fits all. I also think from a strategic business perspective, really focusing in on, um, this is additive to employees. I can't say that enough. This isn't about replacement.

That takes some of that fear out of the employee conversation and just being really upfront with that, right? It's an additive tool to help you. So bringing that experience to life for them in that way, again, was something that I would just encourage everyone to take a look at. Um, the other I'm going to just say is be open and real with yourself about a learning process.

Uh, if you're going to start and start somewhere, it's not going to be perfect, right? The the AI is actually going to learn with you and with your customers. And so you can't expect perfection. But what you can do is set some reasonable and achievable outcomes and become fluent in how you're measuring those outcomes and ensuring they're constantly improving. Um, not degrading. So those are just a few things. I would say.

You know, to reiterate on what you found is that we knew that training was impactful of like setting expectations for their representatives about what was going to come. But what I think we found on a lot of our conversations wasn't just the representatives, it was their supervisors. Right. The people that they're interacting with. So, you know, as you start to roll out these technologies, it it's great.

It's helpful, it's supportive, but you do want to give them guidance as to what's there and what's available because we did it in the small, iterative process. There were some expectations that weren't necessarily being met because they thought, okay, well, if I'm filling in the address, it should be filling in these fields and these other 17 intents that we would expect. But it wasn't or, you know, it suggested these other intents, but it didn't suggest these.

And that's because it wasn't enabled for every single intent.

So when, when it was very enlightening is not just informing the CSRs, but making sure that their management knew as well as to what are the expectations that you should have of this application, what are the things that are happening, and then having a communication process in place so that as they made more iterative changes, made more enhancements that they can, you know, have that communication go down to their representatives and their supervisors. So they knew what was coming next. Okay.

I'll ask each of you what's what's coming up next. So what's coming up in the way that you're continuing to roll out things for Pega and Jason? What's coming up next from the product perspective? So Jeriann. Yeah, so I think relative to hitting on Voice AI, um, we're at a state where we are working to just continuously ramp. So ramp in terms of both, uh, you know, experiences or intents that are available, uh, so putting that across all of our footprint.

So all of the servicing and maintenance types of requests versus what we call kind of more of the top five. So looking to continue to grow that. And also as I mentioned, looking to really our goal this year is to ramp to 1200 employees by the end of Q3. So pretty steady state in terms of week over week ramp. And again, trying to keep a very close watch on some of those things relative to customer experience sentiment.

Um, again, seeing what this will do with a larger audience in terms of that handle time improvement. So that's really our focus right now.

Uh, you know, concurrent to that, as I mentioned, we've got a really large book of work that we're focusing in on relative to case management, which does tie to contact center as well, because if you can't do something and more of that one and done environment, you do have to move into more case management where you're living in kind of breathing in a in a guided workflow. So those are some of our primary areas that we're continuing to hone in on.

I think you mentioned you're doing some work in disputes and complaints in that regard. We are. And actually a really cool fact that we're looking at with Voice AI is it could be a great, a great use case for complaint identification. So picking up on words, the customer's uttered sentiment of the customer.

Was the actual intent resolved or did that really turn into a complaint? So that's probably one of the most innovative right now use cases we're playing around with is how could we use this for complaint identification? Because today that's a highly manual or judgmental process that many of our contact center advisors are working through, so we want to be able to speed that up, build that into more of an automated flow. So that's probably one of our bigger use cases. Like you cued me up.

So if you if you head down to the Innovation Hub and you watch the demonstration we have of the solution with the customer service desktop, you'll actually get to see that what we can do with complaints, where we can identify the complaint. And then another piece which we didn't really talk about in the core functionality, but we have an element that we loosely call in case summarization.

And so if you watch this demo, you'll see a complaint pop up the the the customer will complain about the situation that happened in one of our retail store. And then as the case is opened, it's already summarized. It's already filled in everything they said. So typically in a complaint cases there's a type with the problem was what was the resolution, what are they looking for. And they speak it all. And then the CSR has to go retype it all.

We can use that conversation data to go fill it all in. Yeah we didn't really touch on that as we go through. But even in some of the work that I do in other areas. I think that's maybe one of the underappreciated features of using Agentic is the customer is going to just blurt something out. They don't know what your process is, and the fact that they just provided an a ten step process, um, items two, eight and seven in reverse order.

And the agent now has to reorder them down, quote unquote, your path. Whereas Voice AI. Or worse or worse, ask. Them the questions. Again and again that. They. Already did. And now now they don't have to go through. That. Because they forgot. They forgot that the customer provided them that piece of information at the beginning, because the Voice AI now has already held all of that information and can put it into the right spot, even though that may not match what's going on.

And again, better customer experience in the end, because the customer doesn't have to repeat information, they feel like they've been heard. And it's a natural, flowing conversation as opposed to being kind of rough and stilted. Interrogated. Interrogated? Yes, exactly. Okay, so we want to make sure people have an opportunity to ask some questions. So I'm going to kind of wrap up with the big, you know, end question here. Top 1 or 2 takeaways for each of you from this process.

You know, if you were to summarize or you're having lunch with somebody and you're like, hey, we did this. And you know, these are the two things I want you to 1 or 2 things I want you to walk away with. And I know we've talked a lot about this, but I want to kind of drop it back in again as we kind of do the wrap here. I don't want to steal Johanna Sundberg. I think she articulated we might have the same answers.

Don't be afraid to to start small, iterate, find the areas that can be the most impactful. You know, our partners, our Pega partners, Pega consulting myself. When we engage on this product, we really will partner with you to figure that out, to find out where you can get the most impact. We always want to do highest value. Lowest investment, right? What are we going to be able to do that. And, um, you know, just make sure that you communicate with your staff about what's coming.

You know, so that they're not surprised that all of a sudden there's this box that says yes, no on when the, you know, with the data magically entered. Right. You want to make sure that they know. Absolutely. I think we've been probably reiterating that a few times throughout this presentation. But yeah, just get started.

Is is my best advice to you? Be willing to learn and grow through that and make sure you're supporting your humans in how this is going to be beneficial to them and ultimately beneficial to the customer. So keep that employee and customer front and center in everything you're doing. So what I'm going to say is, because we've had a very full session, first, let's thank them for coming up and talking about customer service and Voice AI.

And if if nobody's going to yank us off the stage, what I'm going to say is we can probably do 1 or 2 questions real quick. So if you've got a question, you want to get it answered live, hit one of the aisle mics. Otherwise, you can certainly talk to any of these folks off stage or after the fact. Or you've got your deep technical folks over here. But we're at the next session is going to come in for a 315 start. So we got to do a flip.

If you want to get a question, you got to jump up and ask it now. Oh there. We go. Got one. She's jumping will offer to Scott's point. Several of us are here and sticking around and again happy to be over in the innovation hub. Um, so we're definitely here and willing to have some of those good conversations more one on one. Okay, here we go. First of all. Uh, not on working out. Yes. Perfect. First of all, thank you so very much for sharing your journey. Uh, all sounds very exciting.

Um, my question is, so when you think about the future of work, right, where now we can leverage AI to do all this work for us. And you mentioned about the agent now being more focused on dealing with customers with more, um, you know, those emotions and handling complaints and all of that. So when it comes up in terms of talent, when you're hiring that talent, I think today it might be very different when you're hiring CSRs the way how we hired maybe ten years ago.

So when you think about leveraging AI and all the great stuff that can supplement and do for the agents, what kind of skill sets you would envision for the agents of the future, if you will? Yeah, I think for me, a couple of things that come to mind is really somebody who is right, um, willing, adaptable to change, willing to write, um, get involved in kind of the next leading technology.

Emotional IQ is a huge one, right? Again, you're getting into customer conversations that are far more complex. So I think it shifts the dynamic a little bit more, definitely in terms of what talent you're hiring. You're hiring for someone who's probably willing to take a few right guided risks as well in that that day job. But somebody who's really passionate about innovation and again, emotional intelligence with customers is going to be key. Thank you. Great. And we'll do one more right here.

And then again feel free to swarm after the fact. But I want to be respectful of the next group coming in. Go ahead. Hi. Thanks for your time First I had like seven questions, but I'll ask one. Um, it's in conversational analytics. Um, I saw the nice skills that you had there. So my question is how how how manageable is it by the business. So can we measure other other type of soft skills like maybe building rapport and stuff that is a little bit more subjective in nature.

And then also on historical trends, how can we consult if our CSRs are improving in a particular skill or not? Or so. All the data that you saw on that interaction screen on the feedback tab, I'm assuming that's what. You're referring to right here. This one right here. Right. It's all tracked in the database so that you can export it out and use it in your own business intelligence tools. You can use our insights dashboard or, or the reporting built in.

If you're using our traditional UI to use the reporting, it's it's all there. So that you can use that to use that for either more of like, are you historically trending up or are you trending down in these metrics? And in terms of the configuration, it's quite simple. There's a simple, easy to use, easy to use UI where you pick the type of metric that you're collecting, give it a description, and it's enabled. You can choose to whether or not it's going to be exposed to CSRs.

I forgot to mention that it can also be restricted, so it can only be exposed to management. So it might be a metric that you're collecting, but you don't want the CSRs looking at the wrap up screen. But you want your management to know that it's occurring. You have the ability to do that with these metrics. And you've seen success measuring those soft skills. More subjectivity like building report. Do you think it's accurate enough for coaching purposes? I do, yes.

And you know, to I would encourage each of you, if you haven't, please go down the Innovation Hub and try out the customer simulator, because, you know, with the question that was asked just earlier about what are the skills that you're using to hire? I think the customer simulator is not only a great tool to help you onboard, it could also be kind of be used as a great tool to help you decide in your hiring process.

You can give them some Interactions that they can work with in your interview process and and have them run through a simulated customer, a very a scenario and see how they interact and how does it score. How do they score versus what you want for your baseline? And then you can make those determinations. You make the determination of whether or not they're a hirable resource or not. So it's another one of those pieces that you can be leveraged.

We're we're mainly focusing on that tool as an onboarding solution. Let me tell you it's cool. It's fun. So if anybody is in here has tried it, they'll probably tell you, I know there's a few in here that have tried it, but you'll also be able to see that you can get those metrics because you'll see it at the end. And I would challenge you if you don't care about the score on there, because we do score you, that you can potentially make it on the top of the leaderboard.

Um, but if you don't care, give it a less than optimal CSR experience and watch how it comes in place. You'll see that it's real. Those numbers are accurate. Thank you. You're welcome. Okay, great. One more time. Let's thank Jeri Anne Larck and Jason. Great..