NICE Ltd. ($NICE)

Good morning, everyone. I'm Ryan Gilligan, Vice President of Investor Relations at NiCE. Welcome to NiCE's 2026 Investor Day here at NiCE World. Before we begin, I must show you this disclaimer slide. Please note that today's presentation contains forward-looking statements as well as non-GAAP financial measures. Okay. Now we can start -- we can talk about the agenda. In just a moment, we'll start with our CEO, Scott Russell, Scott will then hand it over to Jeff Comstock, our President of CX Product and Technology. After that, we'll hear from TripAdvisor. Next, Arun Chandra, our COO, will be joined on stage by Accenture. And then finally, Beth Gaspich, our CFO, will wrap up our prepared remarks. Following our presentations, we'll take a 15-minute break. For those of you that are in the room, feel free to grab lunch just outside those doors. And for those of you that are on the webcast, you will have an opportunity to submit questions. We do ask that everyone save their questions until Q&A. And also if you could silence your cell phones, that would be much appreciated. With that, I will turn it over to Scott Russell.

Good morning, everyone, and welcome to Investor Day. For those of you who are online, I apologize. I'm going to make a few references to what happened in our keynote this morning here at NiCE World. But for those of you who are here with us, thank you for joining us at this event. It's obviously a really important customer event, but also, it's an opportunity for us to share the innovation and the capabilities that not only that we've built and that we've delivered with our customers, but we're also what we're innovating and creating for the next year of CX in AI. So a few data points that I've just got off stage. So I'm still in the buzz of being in that theater room, but it is a great event. NiCE World, we've got about 20% increase year-on-year. So we continue to get more and more customers. And what's really interesting is the proportion of non-CX customers that are interested in the journey. Even last night, I had connected with 5 different customers that were in the exploratory phase and they didn't know whether they were going to start with their on-prem to CCaas move, whether they're AI move, whether they want to do it all. So the journey was part of the conversation, not just the destination, and often, that's why customers come to an event like this is because they're trying to discover, they've already made the decision to come to NiCE, but how to get there, the journey that they're on, what are the right steps is often. And the most valuable part is talking to other customers because talking to other customers getting insights about how to best work with our organization, but also how to maybe tread the path in a more careful way and a more predictable way than those before them. And so today, very much is a representation of where we are, but the opportunity of what we're going to be. So let me start there. I want to start with the market that we're in. And I think this constantly gets analyzed in different forms. You can analyze our market in traditional terms, how much of the on-prem market is out there? What's the CAGR of that market, the total addressable? But you think about a few different scenarios that I would encourage you to consider the market that we are expanding and operating in. The first is, as Phil Heltevig mentioned on stage, and it's the personal agents. Personal agents are expanding this market dramatically, and we're already seeing it. The way that you interact with the brand might have been through our website before, now you're going to interact with an agent and an agent is going to hit a CX platform who has to respond to it. It's going to be AI to AI or AI to human, and it's going to proliferate. I know personally, I have 5 different agents, PA agents, workforce. I do think it's the productivity tools. It's easy to build and deploy. I don't do it much in a professional context yet, but that's coming. But on a personal side, it's already there. And you're seeing companies on the personal compute space are already offering that. It's also expanding. So what does that mean for us? It's expanding interactions. The metrics that we use to guide our business over decades, the number of human agents that sat in enterprise has actually been quite static for a long period of time. as an increase, but it also hasn't decreased much either. And whether that decrease happens as we all predicted potentially well with the human -- less humans in the contact center, the volume of interactions far outweighs it. It's growing and it's expanding. So that expansion means a proliferation of enterprise AI agents. It means that the digital volume and the interaction that we receive is expanding. And of course, the thing that we know for sure is that the the on-prem base is still far from done. Again, those customers that I spoke to last night of the 5, 3 were still on-prem, on-prem on legacy platforms that are trying to figure out how do I move to not only to the cloud, but to a cloud AI platform that can deliver and enable what they need in the future, not what they did in the past. So we've got a considerable growing, expanding market. And that's exciting because we're not trying to only take market share. Yes, we've got direct competition in each of the different segments that we operate, but in totality, we've got an ability to be able to grow and expand in a growing and expanding market. It also means that when we take leadership, it allows us to move across. I know many of our investors who have been with us for a period of time think in world of or AI or in CCaaS or in workforce management. That's not the way we view it. We are in enterprise CX. It is a seamless platform and it's interoperable, not because our competition can do that because they can't. They don't have those platforms. They have to compete in the isolated segments they're in through the acquisition of Cognigy through our home built capabilities in workforce management and in the CCaas space, we've already got the ability, and we've already done that integration. So not only is the market large and expanding, it creates a differentiated opportunity for us. Let me be as bold as I can in this statement. Many companies are evaluating their AI technology in a proof-of-concept pilot. They're in discovery mode. They're trying to figure out if it can work, and if it can work in their environment, but they're very quickly now making decisions that are different, can it work at scale? Can it work with the same operational complexity that the contact centers have to live in, the trust, the security, the scalability, the always on, the accuracy. They are not going to let the AI platform be less accurate, less scalable. It's no good if your first contact is an AI agent, but because 1,000 other customers has hit you at the same time that it doesn't work. That just leads to poor customer experience. It wasn't the first evaluation criteria when companies were looking at AI, but I can assure you it is now. They're now buying it in enterprise AI. They're thinking about the world of CX with AI infused rather than AI separate, and that's what differentiates us. We've already got the market leadership. We are the market leader in CCaaS. We are the market leader, at least by industry analysts, in AI for the CX space, and we've combined it together for end-to-end orchestration. And the other point that I would make is there are many AI tools that have got cross-purpose. Many companies are saying, "Oh, I can do different tasks with my AI agents." That is true because you can build it with the same underlying foundational technology. But the building constructs, the scaffolding that you put over the top needs to be specialized. We have specialized on CX. That is the space that we exclusively operate, but CX is not service. CX is all of the engagement with customers, inbound, outbound, proactive, reactive, synchronous, asynchronous, voice, AI, digital, it can cover go step into places where you think about sales and marketing and revenue. There's no limitation within that space because we understand what customers need. We understand their intent. We know how to operate it. We know how to deliver it at scale. And we're infusing the AI capabilities to provide a compounding advantage. I had a customer yesterday tell me that the idea that an interaction that they had with a human would automatically allow the AI agent to learn from that interaction to make the AI agent even smarter on the next connection, they were blown away. I mean if you think about it, it's fantastic. AI agents learning what the human has done and then figuring out how to do it better in real time. That is orchestrating intelligence. That's what we've got within the platform. So it's not just using the data and the historical data, but it's applying it in real time, and Jeff can talk a little bit more about that. The other thing that I would highlight, and I guess building upon what I had mentioned before is AI and CX, we believe, is reaching an inflection point. The market is -- we're just scratching the surface of the opportunity. The AI market is huge. You think about the volume of interactions, 3% to 5% of the volume of interactions today are hitting the AI platform. But most of it is pointed at single tasks. And if you had the -- for those in the room, you might have been intrigued by one of the examples by our customer at Fabletics, Jack Roberts. And what Jack spoke about was he spoke about choosing meaningful tasks, items that matter. It is very easy to do simple automation on an AI tool that sits at the front of your CX stack, but it provides very little value. The value comes when you're doing the more complex things. And whether you start simple and then move to the complex or do what Fabletics did and they started with the complex and then they rounded it out with the more simple, the platform is built to provide that value. And when you're going from simple automation to really embedded complex capabilities that can handle the scale, well, you're going to buy differently. You look at the technology differently because it has to work, it has to -- so the historical adoption of patents is full enterprise CX stack, we're already seeing it. What are our proof points? 100% of our deals in and CCaaS over the last 3 quarters, I think maybe since I've been at least in the last 3 quarters since we acquired Cognigy, 100% of them have included AI. Companies are not buying their on-prem to cloud move without the AI platform. In fact, the other way around. They're starting with the AI capability, and then they're figuring out how the overall CX platform delivers their enduring needs, the human management, the AI agency, human agents and how that operates together. And that's exciting. Why? Because the more complex it gets, the better it is for our competitive differentiation. What's the choice for a customer? Well, I'm going to have to either use a CCaaS platform and then go an AI platform and maybe multiple AI platforms, and I'm going to have to figure out how to integrate it, and it's got to work at missing-critical scale. When that Lufthansa flight cancellation and you get 20 million interactions within the 1 week, it doesn't work. When you're buying for that scale and you're buying for that interoperability, what we've already built, that delivers the scale that the market needs, and we know it because that's what happens in CCaaS today. The only difference is, in the CCaaS world, it's only human agents, but it has the same expectations from companies, big brands. They need a platform that will be able to work to that. And so we made a choice. We didn't have to integrate Cognigy into CXone straight away. We could have kept it bolted on, and we would have been able to offer that as a really value-adding offering to the market. We bolted , we integrate it because we knew where the market was going not necessarily how that we're always buying today, but how the market is going to need that capability in the future. And so that's where CX is providing -- in enterprise AI is where CX proves at its scale. We have high volume. I think everybody would recognize that the CX market is 1 of, I would consider the 2 clearly proven grounds for AI in the enterprise space. Software engineering. There is no doubt companies like ours, we use Claude and other available tools in our engineering, and it helps us drive incredible productivity. The CX space is the other one. Why? It's high volume of data. It has to operate within tremendous complexity in real time, every channel, every department, it's got to be accurate. So whether it be the scenarios like Citi where you've got high stakes complaints that you want accuracy that Mia spoke about this morning. But benches going on to human scenarios, and then she's going to go into different scenarios. You've got -- it's got to always work. It's got to always deliver the accuracy that the customers expect because let's face it, if it's not accurate for a financial institution, that means not only loss of customer, that means potential fines and other things from the regulators. And then last but not least, it's obviously a high consequence, revenue, loyalty, cost. This isn't a cost play for many businesses now. They look at this platform and say, "Well, if I've got this great interaction, how can I create revenue? How can I drive more value-added offerings onto the same interaction rather than just responding and containing a request." So it is our view that most AI agents, most point solutions out there only solve part of the problem. We compete on this basis every day, and we are very, very confident with our win rates when we're able to offer our combined NiCE Cognigy CX AI platform. Agents without that full context are conversations, but they're not experiences. They don't have the full context. Agents without that orchestration, they're doing tasks and they're doing very contained tasks, but they're not doing the full business outcome, the full journey. Agents without the governance, and there's a lot of AI platforms out there, if you ask for them about their auditability and their release management and their security framework, things that we take for granted that you must have, they are found wanting. And what it means is it's a risk when it comes to the enterprise AI space. And last but not least, is I haven't yet met a customer -- sorry, this is not true. I have met a customer who's tried, but not been successful. No customer that I speak to are thinking about no human in the loop. They want human in the loop even if it's simply to guide what the AI agent is doing. You'll see some technology if you get to the show floor for those who are here at NiCE World, you can see how our humans can actually be watching what an AI is doing at the time, and it will actually trigger the AI agent may not be sure. Do I give a credit in this circumstance? It might not be a clear decision 1 way or another. So it sends an alert to a human agent or a supervisor, what do I do in this case? They give the feedback. It learns. Next time, it will make that decision proactively. This is the capability we've already got out of the box that allows a human engagement and an AI engagement all embedded in one flow, one experience. You as a customer won't know it, but it will be a much more seamless experience. So I guess, end to end, that means that we see ourselves as very different At NiCE, we don't believe that we need to compete head-to-head with an AI player on a stand-alone basis. We can and we do and we win. I need to reiterate, go to any of the Gartner or Forrester industry analysts and look at the #1 conversational AI player with customer service or customer experience. You'll see Cognigy, top right-hand corner. Some of the other point players that you hear and talk about out there, they're not even on the chart. And if they are, they're nowhere near. The richness, the capability of this platform as a stand-alone AI platform in its own right is fantastic, and we try to compete and win on that. But our value is so much broader. We've built an orchestrated platform that no one else can offer. There is simply no one. Others are going to fast follow. There's no doubt about it. We know that others are following our lead with what we've done with Cognigy and integrating it into the full suite, but that takes a lot of work. And we've already got the market leader already in place which means our platform is way richer than what some of those others can potentially offer. So we're very comfortable that as we go into this AI era, when we're competing with point or fragmented AI platforms that we stand strong, orchestrated outcomes, running AI across the CX operation, every interaction in compounding in its intelligence, whether a human or an AI spoke about it, that is NiCE's advantage. We've got the ability to be able to take all forms of intelligence. The market gets so wound up on artificial intelligence. Yes, it's really important, but it's not the only intelligence that matters. When you go to a CX site, and you go to a contact center, it's really amazing. You go on the ground and you talk to them and you watch what a human agent does. The amount of decision-making, the complex decision-making they need to make real-time under pressure. The clock is watching, supervisors are watching, leaders are watching and they're making real-time decisions on behalf of their company that has financial consequence, that has brand consequence. This is real, difficult work, and we have the knowledge, that embedded knowledge that is infused in our AI platform that others, they're doing bolt-on tools, they try to copy all the data and they try to figure it out on their own. It's AI on CX not in CX. So our agentic intelligence, our human intelligence, our operational intelligence, the things that we've had to do for decades to deliver customer service in a human contact in a contact center, we're now applying that in the AI world, and it gives us opportunities to automate where we never could before, but it also gives us the ability to learn from those different so that they provide a compounding advantage on both ways. That's why AI is so exciting to us. It's not just the unique market opportunity that it presents for NiCE. It presents us an opportunity to differentiate and expand upon what we were already best-in-class at. And it makes that element even stronger. So if you're running a contact center and you're thinking about how to manage the workforce, you're doing what Mia at Citi talked about. You're thinking about how you can improve retention, burn out, challenges around attrition. You're using the data, the knowledge in a way, and then that's also informing the AI agents to perform better as well. These are not disconnected platforms, not with NiCE. If companies choose to go with separate solutions, they're going to have to integrate that together and you know we're near going to get the seamless experience. So I guess I'm rounding all of this up to say is that we are growing rapidly in an expanding market. Our bookings have been at the record levels for the last 3 quarters. Our backlog is growing, our AI is flying, and that is in a market that is in very early days of what the market's demand on the AI side. But where it goes, which is buying at enterprise scale, in operational complexity, in orchestration, in true orchestration in the contact centers and in the workforce management. That's where the market is going. We've already built it. We are ready and able to then scale that, which is why big organizations such as you might have read about HMRC that announced an 8-digit deal or a 9-digit TCV deal with us a couple of weeks ago, why did they choose NiCE because it's that platform. Everything that I've just spoken about, the CX AI platform operating with over 30,000 agents, operating at scale, that's why they chose NiCE. So let me move forward quicker. I'll move quickly. We've got an expanded role. We were moving to a bigger category. We're going to bigger buyers. I have been really pleased. It's been interesting the amount of CEO meetings that I've had over the last 12 months has increased because the importance, not only in terms of spend, but in terms of the importance of this platform is to the overall business. We've got an executive engagement track. We had such demand from C-suite customers here at NiCE World, we set up for the first time to have an executive track today purely for that cohort because they're so interested in what we're building and how they can apply it within their organization. And clearly, they're interested in the value that it brings in the ROI. So hopefully, that gives some context of not only where we are, why we're so excited about the opportunity, but where we're going and what we've built, what we've integrated. The technical integration of Cognigy into CXone was not just a task to be done, it was an embedded platform that we can now go and compete on differentiated terms. And we're already seeing the fruits of that. We're already seeing the benefits with our win rates, with our bookings rates and with our renewals as well. Customers are buying into that vision, and to give a little bit more detail about the day and then go into more details about the technology, I'm going to ask Jeff who's going to talk about the technology platform. Arun and our TripAdvisor team are going to talk about delivering real outcomes in real customer scenarios. Arun, sorry, will cover the scaling outcomes with John from our Accenture team, and then Beth will wrap it up in a monetization of how it all looks from the monetization of the platform. So with that, Jeff, I'm going to hand over to you.

All right. Good morning, everyone. So I'll walk you through how we orchestrate intelligence across customer experience. I thought I would start with a view of what contact centers basically have today. So before they onboard the CXone, what do they really look like from a conceptual perspective? And here's that view. They have voice. They have the voice channel. They have the all-important voice routing. This is kind of where it all got started. And this is still a critical channel in the contact center. They have all the workforce management, right, managing their human workforce. They have forecasting, scheduling, quality. There's a whole bunch of capabilities and applications in that space. And of course, they have some basic analytics to go manage the voice and the human workflow -- the workforce, right? As technology has advanced, they add more and more capabilities, right? So on voice, they've added IVRs, digital channels, live chat came out, social messaging channels. They added those. They added sort of the first-generation crappy bots that [indiscernible] had forced upon us, virtual agents. And of course, now today with the emerging very powerful agentic agents. So they've assembled all these capabilities to run a basic customer experience function. But here's the problem with how all that got built out. Historically, no single vendor had even the majority of these capabilities. So they've had to go add each one of these, they've had to bolt it on ad hoc over many, many years. And that means different vendor solutions, lots of different vendors in this landscape, lots of siloed technologies that they do have to care and feed for and lots of pockets of data, disconnected data that don't talk to each other. And they've got to manage these fragile integrations between these systems, right? So for these enterprise contact centers, that represents tremendous cost and complexity. They're spending a lot of resources on this and they always have, but that's coming at the cost of focusing and delivering incredible customer experiences. That's what they really want to be focused on. And this is why the platform approach is so valuable. And that, of course, is the path we've taken with CXone, right? CXone spans spans all -- like the big 3 categories of customer engagement. We call it agentic for front end, agentic systems, engagement for all the channels of engagement and then, of course, workforce empowerment, which is managing that human workforce, but also now that AI agent workforce. And CXone is that industrial strength, enterprise-grade platform that can handle those mission-critical high-volume communications. That is CXone. That's our heritage coming from voice. And that platform powers seamless experiences across all channels of engagement. Yes, voice, but also digital channels and also from self-service to human-assisted service. So all on one platform, it's all in one place, powered by CXone. And this is really important today that all that data, all those capabilities are in one place in a coherent fashion, and that's critical for agentic AI. That AI needs those capabilities, all that data so we can reason over it and use that data to drive outcomes. And across all 3 areas of customer engagement, we lead. NiCE is in a leadership position in every single category. And you don't have to take our word for it, we've got all the leading analyst firms across the space that give us that external validation as well. And I'll tell you, no other vendor can say this. They just simply don't have all the components, let alone the third-party vendor validation. So we are leading in the CX platform space, full stop. And we built this platform for adoption flexibility. So as customers start with CXone, what they don't have to do is rip and replace. They have this fragmented landscape. They can start wherever they have the most urgent need. Any one of those product capabilities they can get started with, those components come with a whole host of third-party adopters. So we easily slide into that fragmented landscape and customers can get going. And then from there, they can expand, right? So as they expand, they get 2 big benefits. Number one, of course, they can start retiring all of these different tech stacks, but at the same time, they start getting the platform benefits that we can uniquely deliver, and I'll talk to you about a few of those. And Arun will talk to you how -- talk you through how we leverage this platform advantage from an architectural perspective in our land and expand delivery motion. Okay. And in each one of these categories, we also have incredible depth and breadth. This view does not even scratch the surface. And for big enterprises, we truly are a one-stop shop. This is why the HMRCs of the world, the Citis, this is why they choose us. Let's see. So this is -- and by the way, all these capabilities are sitting on the same CXone platform, that same enterprise-grade, high-volume, mission-critical platform. But it also supports the very long list of security, privacy certifications that the most heavily regulated organizations on planet earth require. We cover that. And of course, the latest addition to this platform is Cognigy, as Scott mentioned. Cognigy is now native to CXone. In our last Investor Day, I think it was November of last year, shortly after acquisition, I came up here and told you how we were going to go integrate CXone deeply in the platform while retaining the ability for customers to purchase and deploy NiCE Cognigy separately, independently. And I'm happy to stand here and say, we are well ahead of our own ambitious plan there. It is baked in. It is done. It's the foundational conversational AI agentic AI layer for CXone. That means it's 1 application experience, 1 shared data layer, 1 set of communication channels, voice and all the digital capabilities that we have. And coming by the end of the year, we have a few more things to do. We're doing the engineering work and certification work to make Cognigy FedRAMP compliant. We'll have that done by the end of the year. And we have a few more sovereign clouds to deploy. But other than that, it is baked in at the core level. We've already got lots of innovations I'll talk to you about, and we're just getting started in that direction. So Cognigy is now native and that means it's already the conversational and agentic AI capability. So from our self-service, on the left-hand side here, you see it is our self-service AI agents for all channels of engagement. For role specific Copilots in our existing products, those are now completely replumbed for -- with Cognigy. That means they even have more tool use, more agentic capabilities, so our existing customers with existing products now have more value, making those products more value for them, even stickier from that perspective. And -- let's see. Now that it is on the same platform, Cognigy does allow us to do so much more. This is where we can really break out. It allows us to build learning loops within the CXone platform. And we're launching those this week. We talked about it at Scott's session. Hopefully, you can make it to the show floor. We've got lots of examples of where we're building and delivering these learning loops. I'm going to walk you through an example of what this means. This is one of our broad learning groups. So as we all know, Cognigy, stand-alone product, very successful product. Customers are achieving 60%, 70%, 90% resolution rates depending, of course, on the intent. But what happens to that 20%? It gets escalated to humans, right? But now that we're on the same platform, we can see what's happening with that 20%. What are humans doing? What tools are they using? What sequence are they doing doing? How do they get it resolved? And we have all that multimodal data, the voice stream, we've got the screen recording. We've been in regulated industries forever. We've got all this technology. So we have all this deep data that now we can apply very sophisticated multimodal AI on to get insights in terms of how to go close that final 20%. So basically, it's a goal-seeking loop that is goal seeking to just get more and more automation done past that 80%. Okay. With every -- so basically, at the end of the day, with every engagement, the system is just getting smarter and smarter. And customers are choosing us for these types of platform advantages. And of course, in just a little bit, you'll hear from our friends at TripAdvisor, and they'll share with you some of the reasons they came over to the platform. Okay. So that was the platform advantage. Now that Cognigy is native, I'm going to talk to you a little bit about some of the highlights. I'm going to touch on just a few of the innovations we're launching this week just to give you a flavor of where we're at. So a key theme in addition to agentic AI throughout is how we're advancing the entire platform and all of our applications for the hybrid workforce, humans and AI agents. Agents working alongside human agents, humans supervising fleets of AI agents, and of course, agents assisting humans in the flow of their work. So one of these launches that we have this week is called the engagement -- the agentic engagement plan. So just think of this as an enabling layer that puts AI agents on the same level playing field as humans. And I'll just give you an example to give you a sense of what this enables. But I will tell you, this is a game changer. AI agents are so powerful today, this engagement plan just sort of unleashes that. Today, when an AI agent has trouble, right? It doesn't have quite the confidence to close the issue, what happens, gets escalated to a human. With this new plan, the AI agent can now just raise his virtual hand and say, "Hey, I don't have quite the confidence to give this -- sort of this return to the customer. I'm not going to go hand it off to the human, I'm going to raise my hand." Human supervisors, just like they do today, they manage in real time the human workforce. And this is what they do. Now they can do that for AI agents. An AI agent has their handheld, they can go -- the human supervisor can go into that conversation, see the whole scenario, the conversation instantly, look at the scenario and say, go ahead and give that return voucher, go ahead and okay it. And then the AI agent can go continue the conversation and close and automate that whole transaction. So I mean just think about that for a little bit. A human spends 10, 12 seconds reviewing, approving, moves on, helps the next human or AI agent that needs help. The AI agent continues the conversation. And by the way, there's a learning loop. So next time there's a scenario just like that, it knows that it can go ahead and give the return. So this is a good example, I think, of how we're really changing the game in terms of the hybrid workforce, and it is very, very powerful. The AI-first desktop. We're obviously reimagining what it is for humans to engage with customers. We now have AI infused throughout. It's also that surface area where humans supervise that -- those fleets of AI agents. So next, workforce empowerment. Across workforce empowerment, we're redefining what it means to manage this workforce with humans working alongside AI agents. So we're extending the operating model from planning, scheduling, quality, cost and performance across the board. There's a lot of capabilities in this space. They're all being updated in a big way to manage that AI and human workforce. And we're delivering very targeted optimization loops there, right? There's a lot of -- for quality and performance of engagements, there's a lot of tools that we've developed over many years. Now we apply that equally across AI engagements as well as human engagement. And finally, agent experience automation. In this space, think of this as we're just advancing our leadership in the AI agent space, right, across the board. One of them is agentic analytics. So this is where we built a fleet of highly specific domain expert AI that goes in and goes through the entire data set that we have across the platform and it's looking for more opportunities to automate. It's also looking for -- it's also looking at existing automation and how it can improve those automations. Agent Forge, it's already very easy to create AI agents with Cognigy. With Agent Forge, we're making it even easier, of course, from our own platform, but also we can take just about any artifact that you can think of, whether it's a specification, a document of any kind, we can pull that into the platform and generate an AI agent in minutes. A human has -- we basically bootstrap that entire process. Okay. Let's see. That was a quick round. I'll just maybe touch on one more, Guardian AI. AI agents are proliferating. It's really important for customers to have a control plane in terms of keeping those AI agents on brand, in compliance. And so we have a set of tools for observations and just managing this at massive scale. So Guardian AI is another key development from -- that we're launching this week. Okay. That was a quick round of highlights. From first engagement to final resolution, this is how we're orchestrating intelligence, and this is how we are expanding our platform advantage. All right. So I'm happy to welcome up from TripAdvisor, John Hanley and Dave Fox.

Thank you for the intro. Well, thank you all for inviting us here today to talk about our journey into the world of AI. I recently joined TripAdvisor around 8 months ago. I am Head of Customer Operations. I'm responsible for defining the strategy. My colleague...

So I'm Dave Fox. I've been at TripAdvisor for rather longer about 8 years now, and they look after telecoms across the TripAdvisor Group. My task is to manage the tools that allow us to talk to each other and our customers.

Thanks, Dave. So when I joined, I totally changed our strategy. We were a human assistance first organization, 100% using, obviously, outsourcing. Hopefully, you all know who TripAdvisor are. It's one of the oldest brands in travel. But the most exciting part of TripAdvisor is via to our experiences. And this is our growth engine. And this is what gives me and customer service is a big issue. How do we service this hugely vast part of growth of our CX with this human assistance team. So it's quite clear to me from day 1 when I joined last year, we need to have AI, not AI necessarily enabling human agents because when customers come to us, I actually proved last year that actually humans are slowing down the conversion rate. It's slowing down the decision making. Why? Well, because we have part of the data, our suppliers are part of the data, our 2 guys have part the data. And [indiscernible] human being, as much as we can give them some amazing turning, they really slowed down that conversation. So we knew we had to go into AI and fast. So I set a very tough demand of my team, how do we, in 90 days, figure out our strategy, our investment and go live. And of course, everyone said, you're joke in John, you're crazy. This can't be done. Well I think it can be done. And in those probably 2 or 3 months, we saw so many RFPs from other bidders on the world of AI. I mean, every week, I almost got a big coming in. But for me, the problem wasn't about core volume. And I think when I was talking with different suppliers, they didn't understand our strategy. It's customer first. We really care about solving the issue. We want to talk to customers. We don't want to deflect. In my 15-year 25-year history of CS, I have spent so many hours and so much money trying to deflect customers, try to hide the phone number, knowledge bases and chat bots, right? IVRs with 75 options. I think we have 15 actually. I hate it, I despite it. And for me, 15 years ago, I was really passionate about enabling the customer first. So for us, we had to find a technology that enabled this solution and not just affect our customers. So Dave, you had 90 days to implement. Tell me, how do you do that?

Well, I'll start off by wearing a bit. I must confess. But -- and consider many things, but the answer is always going to be you build from the ground up. If the customers are going to contact you and you want to make it easy, like John described, you need to have a front door through which they can easily walk in and you can help them. So before we started this project, everything would go, as John said, to the human agent, we would say, "Hi, we'd find out what someone wants it." We then have to go and find out. Is that really you because we can't just let anyone change somebody's booking, we're going to find the book a mid, find the detail. And after all that, we can get on with actually trying to fix the issue that they've called us in about. That first little bit, the first 4 boxes on that slide typically takes a couple of minutes, not very long in the scheme of our lifetimes, perhaps. It's an awful long time when you've got someone tied up for it that could be doing something else. And at 2 minutes was the first place we had to look. So John, if you can just skip on, please? And to do this, we built [indiscernible]. Not my choice of name, it's [indiscernible], I'm growing to it. This is our AI assistant, which helps us to understand, to verify, to retrieve. And eventually, if it can't resolve the thing itself, it can hand off to a human colleague. The idea is to make it seamless. John makes the really important point, we are here to make the customer have a good time not to make them leap through flaming hoops, jump up and down on a Pogo stick and then only then can we help them. It's to make it a nice smooth instance. And the only way we could do that is not to have some bot, which we bought on to the site. We transfer across like you forwarding you call your voice mail, we need those calls to be a voice inside of our architecture and something that becomes part of a seamless journey. [indiscernible].

Yes. And I think just a quick color on there, Dev, I think on the session this morning, which was awesome, by the way, the key word that I heard was we were going to invest in AI, don't do the easy thing, do the right thing. And so many people, even as of last week with St John, [indiscernible] is the easiest thing to do for AI. Absolutely. But you know what, for our customers, we sell the emotional product. When you go on vacation with your family and friends, you don't want to be [indiscernible]. You want to call somebody, okay? So we knew voice was absolutely place to start. And Unfortunately, what Dave told me was, is also the hardest.

Absolutely. And I'll go to my grave same voice is the hardest of the telecoms engineer. I do valuable work, John, take that back to HR, but every -- not only do we have to the calls. And from an engineering perspective and none of you guys need to hear about the engineering of it, it's way more complex, just the simple mouth to wear delay in a global environment, the speed of light gets a bit slow. But also it's a big black hole what we talk classically to customers about because with chats, you have a transcript, with e-mails you've got a mail trial, with calls, there is a conversation which we might record. We might transcribe and someone's got to go through the thing is the traditional way. So there was this huge black hole historically of information, which we couldn't see. And for us, that was an untapped resource, an untapped opportunity. The guys through the presentation has took loads about the value of insights, the value of context. We need to understand what those conversations are so we can understand where the friction is. Is it a bad process in supporting a customer has got an issue? Is it actually an issue which we could fix by moving the big blue buttons a couple of inches to the right on our website. So it's really important for us to be able to take those contacts to have the insight and then we can start fixing the issue. Can you just step on, please, John?

Yes. And I think 1 thing I had a problem with was it sounds good. And I think the technology is there I thought to myself, but actually, well, our customers accept voice. I'm on vacation, I'm with my family and my friends and sign the to bus doesn't turn up, like am I going to accept some kind of chat kind of talk to me. So the big bet, the big investment wasn't necessarily the risk that we go with because I think we picked someone fantastic. Proof of concept that we did actually was, will, our customers actually voice. That was the unquestioned that we had at the beginning.

Absolutely. So why did we choose NiCE? Now we're a long-standing nice customer. We've been a customer -- 1 customer for many years. He's done a great job for us. So they are always someone who're going to talk about this stuff. But Scott from everything you said you'd be quite pleased that some of my reason in here. But more than anything else, it was the ability to provide everything in a single solution on a global scale for us. The complexity that the guys have been describing to where we've got different sources of data where we've got loads of different tools, we've got a complex agent workspace makes it more and more difficult for me as an engineer to build and manage that thing. Every time someone does a dot change on one of their platforms, I have to go and redo all the integration. That I haven't got time for when this blogs asking me to deploy bots in 90 days.

30 days.

You changed the old post. It's terrible. We wanted something that would give us that scalability, that manageability and let us be future ready. It goes without saying as you've all heard during the day, there's AI capabilities baked into the very heart of what NiCE does. The acquisition of Cognigy, though was a game changer. That gives us the front end, which can be more like the experience we want our customers that particularly on the calls, which, again, I'll say it because I like saying it, voice is more difficult than chat. It's certainly a lot harder to have a persona that gives you a human-like conversation than it is to do something where you're allowed a couple of seconds delighted to think about it. The fact that it's throughout the platform means things are joined up, and we can have a coherent experience. The final reason we chose NiCE was, as I said, we worked with them a long while, [indiscernible]. We're trust and I see them again, it was mentioned in the keynote as something of an extension of my technical team. I'm sure, John, you see it as an extension of your customer service and operations team. It's something we could feel we could trust. If we're going to do something difficult, we need people that we can rely on to be there with us.

Yes. I mean I do to take you guys he'll tell you the important things about a single platform, but it's true. I mean my demands are fast not because I'm getting older and grayer. It's because we will let to that in the journey like some of CX organizations. But unquestionably, it's not a speed to finish, it's to speed to start. And I think it wasn't the risk about jumping in, it was the long-term part of things. And I think, for me, when I was talking to other organizations, they try to take my strategy and turn it around to fit their product, which is not what I wanted. What I want was a company that could see the strategy of our group and deliver. And NiCE, honestly, was the only organization that got it. I never talked about cost reduction. It's been the primary focus. It's about solving the issue. So now that we've actually launched [indiscernible], which, by the way, can I just tell you, Igor drinking as guy from the U.K. I don't talk any other [indiscernible]. I actually play Vesper on my phone live. I got to my friend is the call of [indiscernible], they think it is just been awesome, right? We launched in 45 days after we did the contracts, 45 days. It's incredible when I think about it, what we did. Although [indiscernible] Version 1, and now we've internally hired a bunch of people to kind of really grow [indiscernible] into version 2 and version 3. And it's incredible what we can do. This is what excites me. This is why I think I know our partnership is the strongest. It's not about what we've done today, which is build out a reactive inbound customer service. It's the future that I dreamt about 15 years ago. It's about the productive side. How can we figure out customer problems before a customer problem. I heard the call this morning about the German airline, and it just really excites me because how many people want to go on vacation, jump on a plane, get to destination to find out as a problem. Nobody. Standing there with the family and the kid shouting daddy, mommy, I want -- and I'm in customer services, give an hour, there's a 25-minute weight [indiscernible]. [indiscernible] if we could solve the problem for a problem. A nice really understand that journey that we're on, things like what if we have bad weather, and you can't go on the 2 without day. How about we just rebook it for you for the next year when [indiscernible] it's fantastic rather than funding customer services. So this is the part that we're starting on. This is just a tip of the iceberg. In fact, if you talk to my account manager from NiCE, I sent 3 e-mails in the key sleek this morning going, call we, call me, call me because there's so much opportunity. So for us, for [indiscernible] and Chip Adviser, yes, it's all about putting the customer first, and this is really exciting. So[indiscernible]. It's been a great partnership, and we're throwing and joining it. Thank you very much.

Thank you, TripAdvisor team. The TripAdvisor narrative really resonated with me, both in my current role at NiCE and my previous role at Disney. Before joining NiCE as COO 6 months ago, I was at Disney for 4 years, transforming the CX function that served over 180 million customers. Using the NiCE platform that Scott and Jeff spoke about, I modernize the end-to-end CX stack from a digital AI front door to CCaaS, to all other aspects of WAM, which allowed us to deliver exceptional Disney-like experiences at the lowest possible cost to serve. Let me spend a few minutes on how we have a very sharp focus on scaling the outcomes of our customers. To do this, we have built and continue to refine an enterprise-grade methodology to deliver ROI for some of the largest enterprises on the world. We are intensely focused on each stage of the customer journey, not just talking about it, but executing it with rigor and keeping customer success as our North Star. The journey starts with discovery demo and proof-of-concept to define scope and success criteria. Forward deployed pods of engineers and consultants ensure that value is being delivered rapidly even during the solutioning process. In parallel with solutioning, we align on what a full enterprise-grade deployment will look like, covering customer alignment, configurations, integrations to get the customer into production quickly so that they can get the full value of the platform as soon as possible. As deployment progresses, the focus shifts to business outcomes value realization, ROI tracking and building a success road map to ensure that customers are getting value quickly and have a clear path to continued benefits from the platform. Next, we work with customers to identify additional use cases, value capture opportunities, which grows the platform adoption for the customer and feeds back into the sales solutioning cycle. This enables the land and expand strategy that Jeff referred to earlier. While many companies describe a very similar cycle, there's nothing unique about that. The differentiator is the intense operational focus that we have at every stage anticipating customer needs in the future and always keeping our North Star as their success, ensuring that they're getting the business outcomes they need. Next, let me focus on how we are accelerating time to value for our customers. We have built an AI COE that focuses on reusable areas like intent taxonomies, conversational design, hallucination guardrails, fallback protocols, et cetera, all designed to accelerate customer outcomes. We have also built -- we have also prebuilt connectors and APIs to common systems like CRM, workflow automation templates for authentication, routing, escalations, et cetera, and internal AI tooling to speed up every aspect of the customer deployment. These two pillars are now complemented by NICE Labs that was announced earlier today, which will conduct advanced research, rigorous benchmarking and rapid prototyping at the leading edge of agentic customer experience. The third pillar, our partner ecosystem complements, strengthens and expands our ability to accelerate time to value. I will cover more details on the partner ecosystem in the next few slides. These three pillars make up our enterprise-grade deployment strategy to accelerate time to value for our customers, which, in turn, accelerates our revenue recognition. As you have heard previously from Scott and others, we have been investing in our partner ecosystem, and it's bearing strong results. As part of the investment, I hired a Chief Partner Officer when I joined the company. Our partner strategy has four key areas. We work with all of the major GSIs. We have over 200 certified implementation partners, which also accelerate our deployment capabilities. In technology alliances and ISVs, we have over 180 Dev 1 ISV apps for the platform. And we work with over 400 distribution and reseller partners which gives us tremendous breadth and global reach for our platform. Just to share a few data points on the depth of these partnerships. We have over 2,300 certified professionals from our partner group on NICE AI and CX solutions. Over 70 new integrations were created in the past 12 months with our technology partners. And finally, 70% of CX1 new enterprise ACV was partner-led. Taken together, these demonstrate the growing power of our enterprise-grade partner ecosystem. Let me turn to a little bit more detail on the GSI relationships. We are working with all of them and the relationships are becoming stronger with each passing quarter. Why are the top GSIs investing with NICE. One, our fully integrated CX AI platform; two, best-in-class components from agentic AI, orchestration, workforce empowerment, we can start anywhere and customers and partners can scale as needs grow. And third, the opportunity to win 7, 8 and even 9-figure deals. The outcome has been that over the past 12 months, our ACV with GSIs has grown by 3.6x over the previous year. This growth has come from winning marquee customers from a top U.S. bank, perhaps the one we heard about this morning, two of the largest U.S. health care providers, the largest U.S. pharmacy retailer, massive governmental wins such as HMRC in the U.K. and a similar one in Australia. Beyond that, we have won customers together in every major vertical from financial services, insurance, energy, utilities, telecommunications, government, you name it, the entire spectrum. Next, let me focus on Accenture specifically, who is one of our top GSI partners. As a leading SI, Accenture has a unique point of view into where the enterprise AI CX market is going. They are growing and investing in our partnership for the reasons I already articulated, but also for the ability and opportunity for them to drive large-scale CX transformations for their clients. But rather than me speak to it, let's hear directly from Accenture. Joining me on stage is John Bolds, Accenture's Senior Managing Director for CX Solutions and ecosystem. Okay. So Welcome, John. Thanks for joining us.

Absolutely.

John, you often and frequently speak with C-suite and CX leaders at the world's largest enterprises. How are they thinking of evolving their CX function? And how has the conversation changed over the past year?

So for years, CX has been a top priority of our clients. Why not as customer experience matters. I'm going to try and say some things today that are somewhat provocative and one click down on the high level. The big point is the amount of investment is amazing. Secondly, the focus is on service. It used to be 1 of it was customer experience, you had marketing digital and so forth. The laser focused on service is amazing. And secondly, think about over the years, that investment was going on to digital. It was drive self-service, drive self-service, better web, better mobile app experience. But now even with all of that, still voice I agree with your TripAdvisor voice is so hard. There's still so much that goes into voice. It's now that investment is into that channel. And with the promise of AI, what they're seeing with conversational, our clients like the objectives or C suites or segments, some of our leading companies, they want 40% to 60% reduction in the cost to serve. But at the same time, they want to see MPS reduce -- increase by 2 to 3x across the board. So that sounds like the Fed's dual mandate high employment, low inflation.

Bingo

Deliver deliver exceptional experiences at the lowest possible cost to serve.

Yes. There's nothing wrong with that. I know people say it's not cost. It's still a big...

It matters.

It matters.

Okay. Moving on to the next one. You have built a dedicated nice practice with hundreds of people who are technically certified on the NICE platform. What prompted you to invest in NICE? And why are you thinking of investing even further?

Yes. Well, sure. Well, because our customers now want an AI-powered contact center. And remember, contact center, a lot of people think it's the same as call center. It's not. There's a reason it's called contact center. It's omnichannel, and they want an AI-powered one. The other thing is you'll hear Julie Sweet, our CEO say quite a bit, our C-suite is going, when do I get the value from AI? I'm not saying for one else get value, when do I get the value, right? And they're seeing, wow, I have an AI power customer service, I can get there. And so that means, and that Number 1 is they want companies who actually get customer service. NiCE does. It's at your core. Secondly, we have that. It's a nice match. Third, they want a platform. They do want a platform, and NiCE has it all. They really do. They now have the CCaaS, the IVR and routing, the workforce management, the intelligence, I mean you saw a Defcomstock slide. It's a perfect blueprint of all the capabilities. NiCE now has them. But what's super cool about NiCE is that you can start anywhere because our clients are in a different part of the journey. They all are. They have different parts of the components, and you have such a huge installed base. So we'll go in there where you have workforce management and make an impact there. We'll go in there. And for instance, in this big FS company, we did the intent analytics, and it led to us driving an entire AI play. And then finally, we're still doing. I love how you guys said it. CCaaS isn't over. There's still massive CCaaS plays to be made. So we can start anywhere and expand from there with outcomes.

And that resonates. I've spoken to dozens and dozens of customers since I joined NiCE, and I think the smartest, the largest enterprises are looking for that entire play versus one or the other, if you would. So that's great. Let's turn to AI for a moment. I mean, how can we have this conversation or specifically focusing on AI. The market is flooded with point AI solutions, yet Accenture decided to invest meaningfully in Cognigy on the NiCE platform. Why bet on the integrated platform versus one of the point solutions?

Yes. And the reason is because at the end of the day, you point conversational AI solutions are interesting they work, but you have to make it work within the IVR, in the telephony stack, within digital, within all of the different channels. And I think people underplay that. And that's why you're seeing this -- again, I want to give you some provocative points that I found so interesting over my years. This move of having to have people skilled in digital, and all of a sudden, you need to take that digital skills and apply it to the telephony side. And so therefore, we like that Cognigy and then AI has at its core integrated in the platform, how to work holistically within the platform. So let's make it -- also, at the end of the day, the #1 slide my clients use when I work with them is the following. They need to get to that 40% to 60% improvement, and they want to do it. You have to do it across all the layers. Number 1 is where you heard TripAdvisor go, proactive. We've been doing -- we, in fact, had a proactive messaging practice in our firm. We were already, for years, doing multi-day journey management. So take the telco space. When you actually have a problem with your router and you need to schedule appointment and manage that appointment, we would do that all through [indiscernible] journey management. We're actually managing the appointment, checking if they're going to be there, if they are, have they touched the equipment and then when it's done. And that then has been applied to in public service. We then used it in health care. We actually manage someone's appointment and make sure that you check in on them. the reason I spent so much time talking there, I'm more TripAdvisor was. I know I said you guys 4 times, so I was really impressed. That's where we get the most bang for the buck at the top. Then if there's an inbound call, can you then contain it. And so that's where a lot of these solutions are. However, that call, most of the conversations, the harder intents that we're told to start with, they don't usually get fully contained. So when it gets to a human agent, you want a smooth handoff. You want to make sure that, that agent does not start over again [indiscernible] been so frustrating, right? So frustrating. It needs to pick it right up and then help the agent then make that a tradition. Finally, agent assist. So how do you ensure that, that agent for instance, we're getting so much lift out of doing simple call summary, but more importantly, workflow management after -- like after you've handled a claims conversation is that you actually kick off the forms, kick off the process and make it work. And then you're thinking, well, that's 3 levers. People forget how about running the contact center. There're hundreds and hundreds of people in these contact centers who do quality assurance and the quality assurance on 5% of the calls. You can now automate quality assurance. You can now automate the routing. So that's another lift. And then finally, how about growth? We're not doing proactive outbound calling or leads that come in, you have a call and to say, I heard your interested in some wealth management products. The voice sounds fine, they take it, and then it kicks off a lead in a sale. So you got to put all that together. And what's great is it's all integrated in one platform.

So said another way, the fact that we've got Cognigy capabilities built across the entire platform that can serve all the use cases you talked about?

It's awesome.

Well, John, we've built a lot of real momentum together. Looking ahead, where do you see the biggest opportunity for a partnership and what excites you?

What excites me is getting the true agentic customer service. How many of you are right now going as your first question, is going to Gemini straight up? You're going there for the answer, and it's good. Well, guess what, we are already seeing Gemini giving the answer, and it needs to hit into your organization to make sure it's giving the right answer. That's where the future is legit going. The other future where it's going is bot to bot. It's absolutely happening. In health care, we already had a situation where you have the providers checking in with the payers whether or not the coverage is there, what's the -- what is covered, what's the different rates you have to charge and so forth. Well, the bots are hammering those calls. If you don't have bots to handle those calls you're getting crushed. So bot to bot is happening. So you have to become agentic. And so I love -- that's where the future is. And what I like is by having this platform, we can get there. And so let's continue to accelerate outcomes with where you have capabilities. The final thing I will say is what you've done to change the partner culture here is phenomenal. You, Scott, see, we worked with Arun and Scott. Everything at the end of the day is personal. We worked with you guys at your prior careers. And you guys know how to scale partnerships. Now the next thing is how do we just accelerate the certification of all of our skills. And if we do that, we're going to help our clients truly get the value out of AI that they want.

Well, that's an important takeaway for our investors. Accenture is choosing to deepen its investment because of the platform is resonating with their clients, the economics are attractive and the outcomes are really strong. John, I want to thank you for taking the time. We are excited about our partnership, and we'll do all things together.

We will. Thank you.

Next, I'm happy to welcome our CFO, Beth.

Thank you, Arun. It's really great to hear the conversation that you just had with John. I think following that, it's that we're in a really exciting time that our ecosystem strategy and the partner acceleration is really expanding. We're accelerating faster. We're extending our reach globally through this connected partner network. And so we're really pleased to hear that directly from John. So as we move forward, I think throughout the day -- excuse me, I'm clicking a little too fast here. Throughout the day, you've heard one connected story from all of our team. Scott started by outlining why we have a structural advantage at NiCE in a large and growing market. And then you heard from Jeff. And Jeff shared how that advantage is embedded in our CXone platform that orchestrates all of our interactions regardless of whether they're human-led or AI-led across our single platform, which is CXone. You then heard directly from some of our customers, both earlier today on stage, in the keynote as well as here from TripAdvisors how they're already realizing measurable proven outcomes from our platform. And again, of course, our partner ecosystem is really accelerating that adoption around the world. So now I want to take all of the things that you've heard today so far in the one connected story and talk about how we're actually monetizing that and driving durable ARR growth at NiCE. So at NiCE, we've built a monetization framework that captures value from every customer interaction that we have across our orchestration layer regardless of whether that interaction is being driven by a human or if it's being driven by our AI. Today, the large majority, as you see of our revenue is seat-based, and we continue to benefit from ongoing CCaaS migrations that we have in the cloud. But what's really changing is our AI and services layer, as we've been talking to you both throughout today and our recent earnings calls as well. When you look on the first quarter, as an example, you can see that our AI and self-services revenue now contributes 14% of our cloud revenue or $345 million. And that growth was 66% over the same quarter of last year. That 14% is up from 8% of our cloud revenue contribution just 2 years ago, and it shows you how AI is working for us. As we continue to sell across our customer base and we continue to add new logos, we expect that shift that you're already seeing to continue to drive additional growth in AI and and in our overall cloud growth as a result. What makes us really differentiated at NiCE, however, is what we've been talking about earlier today is that our customers are making a single platform commitment to us. It is one ARR envelope. And of course, within that, the customers have the ability to flex in between human-led interactions, AI-led interactions and all on our single unified platform of CXone. I think earlier today on the keynote, you heard directly from Citi, which was a great example of how they're using that package and able to flex with our hybrid pricing model between human and agentic agents. So that's really a connected advantage that facilitates our AI adoption across our customer base that all of our customers have that ability to flex between the human-led or the AI-led interactions, and again, all in that single ARR envelope. One of the strengths of our platform in CX is our ability to consistently increase the customer value over time, and we have a lot of data points that we want to share with you. Historically, when you look at how we've been driving our growth at NiCE, it's a combination of increases in user growth, it's also interaction volumes that continue to expand, it's increasing enterprise -- large enterprise deployments, and finally, broader product adoption. And you heard a lot today from Jeff specifically around our CXone platform, where we have the best depth and breadth of a solution for the CX market. And that's really what allows us to continue to both cross-sell and upsell as a motion into both our existing installed base, but also to offer that into new logos as well. So when we have customers coming on board in our CXone platform, and with the use of AI, they usually start with a specific use case. You can hear from our customers that they are proving the value and the ROI very quickly. And it's easy for them to then extend into adjacent capabilities that cover all of the breadth of our platform. The additional functionality can be added very easily. I think you heard earlier from the TripAdvisor team specifially that they do not need to rearchitect their environment to add these additional capabilities or Cognigy because everything truly is 1 integrated native platform that we offer. So this dynamic across the platform is particularly powerful when we look at AI adoption, and AI is our growth lever, our #1 growth lever here at NiCE, and it's extremely easy to continue to add that capability into all of our customer base. So I'm going to now talk more about the platform expansion we're seeing, both AI that predated the acquisition of Cognigy, and then a little more specifically around Cognigy, and what we're seeing there with some of the AI adoption as well. So when we look at the data points that we have, both in our existing AI customers prior to the acquisition of Cognigy as well as post that, we see clear validation that our AI strategy is working as designed. Today, when you look at an average revenue per a user for an AI customer, you will see that those customers generate approximately 36% higher ARPU than a non-AI customer. And then when you look on an average revenue per customer, or an ARPC of a customer that, again, is an AI user, you will see that their average revenue per customer or the ARPC is 4.5x that of a non-AI customers. These are really great validation points, and it shows you that AI is not just another simple product category here for us at NiCE, it's really a competitive differentiator and is increasing the overall economic value of all of our customer relationships as shown through the higher ARPU as well as the higher revenue per customer that we're achieving through the ongoing deployment of all of our AI capabilities. So next, we're going to look at some of the data points that we have here at NiCE. This represents a cohort of our customers that adopted AI in 2024. So we see this pattern of expansion over time. And this, of course, was again, prior to the acquisition of Cognigy. So when you look at this cohort of adopters of our AI during the course of 2024, you will see that in a 12-month period alone they added approximately 23% higher or had a 23% higher average ARR relative to when prior to the adoption of AI. So we have some great examples of customers across this full cohort of these adopters in 2024 with evidence of that ARR working and that durable growth happening deployment of our AI. And what's also important in this is to remind you that -- not only are you seeing that growth coming from the AI ARR that's incremental, but we are also maintaining the non-AI revenue layer intact. So of those customers about 7% of the ARR was coming from that AI contribution specifically. So they're adopting the AI as well as really having the benefits of the strength of the platform of CXone that's fully integrated. So next, I want to bring us on now to looking at a similar level of information regarding AI and AI adoption, but this becomes more specific to Cognigy. So for Cognigy, what really makes us excited is not just the technology that you've heard a lot about, but also the expansion profile and the opportunity it presents for us here at NiCE. So once Cognigy lands inside a customer, you can see that the adoption is rapidly expanding. And what happens in a deployment is that typically customers start with a single use case, they get that proven value and the ROI that they're looking for very, very quickly. And then, of course, they start expanding. They expand into additional use cases, additional workflows, operationalizing the full journey of the customer. And so that's really a textbook land-and-expand motion that we're seeing. And as you see here, through the 2022 customer cohort data, those customers that had adopted Cognigy in 2022 have a 3x growth in their ARR from the first quarter of 2022 to the first quarter of 2026. When you also look now at their customer growth, their customers have increased 3x since that same period. And of course, this is Cognigy now looking at prior to the acquisition. Of course, we are continuing to greatly expand that opportunity across the NICE global installed base that we have here. And finally, the other thing I want to highlight here is the stickiness of the Cognigy solution. Cognigy has a lot of proven use cases. You heard from some of the keynote speakers earlier today. They are at enterprise scale, working with very large, well-known global brand names, and they've had a 100% enterprise logo retention over the last 3 years. So as we bring all of this together, you can see that the opportunity, even prior to the acquisition of Cognigy, was very strong for NiCE with that strength and the ongoing ARR growth. You can see that Cognigy had a similar experience. And now we're bringing that all together, the power of NiCE together with the power of the agentic capabilities that Cognigy brings. So that stickiness and the land-and-expand motion is exactly why we reached out and proactively worked with a small number of large marquee customer we discussed on our earnings call last month, to accelerate the AI adoption and, in parallel, securing long-term commitments with those customers as well. So we saw a win-win opportunity for us to provide some short-term economic benefit to our customer, and in parallel, again, driving this AI opportunity where we've seen proven results that the ARR growth is strong post deployment. So now I want to just walk you through 2 of those customers that we were referencing. The first is a Fortune 50 enterprise customer and this customer has an 8-digit ACV. So as you can see in the chart here, while there is an initial impact on ARR that we had discussed last quarter, as you look at the longer term and the expanded ARR, we expect to see a 5% uplift as a start for this customer. And it's through a combination of again, securing the long-term commitment, it's coming from also they have in addition to AI and capturing that opportunity with expansive growth opportunity. Looking forward, they also increased their users in both CCaaS and workforce management. So it's important to say that this particular customer is really looking at securing the relationship with us as well. They're a long-standing customer. And so they're expanding both CCaaS, workforce management and AI, which again is really demonstrating the power of the platform and the integrated relationship that we have. So the second example is a utilities enterprise customer, which is a 7-digit ACV. And for this customer, you can see that we expect to have a significant uplift to more than double their ARR in the coming quarters. So for this customer, really, our ability to capture the platform economics and combined with the AI innovation that we offer through CXone is what really secured this relationship into a long-term commitment and made them very excited about how they're going to continue to evolve with us adopt more of their AI capabilities in the platform. So now I'd like to share with you a bit of what we're seeing in our business more recently post acquisition with Cognigy. Here, we can see that in our first quarter bookings from this year, it really demonstrates the enormous opportunity and success we're already seeing in our bookings. We reported a first quarter record of cloud bookings this quarter and the past quarter that just passed. And it's also really highlighting the strength we have in the Cognigy bookings. So importantly, the Cognigy bookings, you can see is broader in terms of the bookings we're achieving with going out into our global installed base with NICE customers. In addition, Cognigy is continuing to sell stand-alone across their customer base and other new logos as well. And I think if you were at the keynote, you heard Phil talking about a little bit of that strategy earlier today on stage as well. So the acquisition of Cognigy is really providing us with an additional growth layer that we didn't possess before, that provides a true end-to-end CX AI platform. And so today, while our CXone customers represent only a single-digit percent of Cognigy revenue, yet they represented the majority of our Cognigy bookings in Q1. So in other words, the cross-sell motion, it's already landing in our bookings. We're seeing that in our results. It's building that backlog that will convert to revenue, future revenue in coming quarters. And the monetization aspect is still in the very early stages of adoption and scaling. So the opportunity is immense, as you've seen because we have multiple data points that show post adoption both on the Cognigy side as well as on the NiCE side, great durable growth with our customers. So I want to conclude and before we break for Q&A to really highlight 3 key takeaways. First is that AI truly is the next evolution of our growth model here at NiCE. Second, we already have clear evidence that we've talked about that AI adoption increases customer value over time through higher ARPU, by greater platform adoption through taking on the more of the capabilities and solutions and the breadth of our CXone offering as well as a proven land-and-expand motion to our large global CXone installed base across the world. We're also continuing to win large strategic customers. You've heard us earlier today talking about a recent win of HMRC. We're very excited about this recent win. It actually is our third mega large international win. We talked about our international region last -- back at our Capital Markets Day last year about how it's one of our key growth drivers. It is demonstrating that continued success with that win and really demonstrates also the strength that we have at the high end of the market, large enterprise and public sector environments where their expectations are extremely high in terms of the level of collaboration and the strength of the solution that we offer that it will operate at the high expectations that we deliver at. So that's why, coming in all together, we believe we are uniquely positioned to benefit from both interactions with your human-led or AI-led all through, again, our integrated CXone platform that we orchestrate across the CXone offering. So that's why we're confident that we'll continue to see durable ARR growth. And looking ahead, we have multiple data points, strong, solid Q1 that we came out of, increasing backlog, 66% growth in our AI revenue of $345 million, and as you can see, great ARR expansion over time with those customers post adoption. So with that, that's going to -- I'm going to wrap up our -- all of our comments from earlier today from our team. And so I would encourage you all now to take a quick break to grab lunch, which is outside, but we'll continue on Q&A immediately after. So please feel free to grab some lunch, bring it back in and we'll continue. Thank you. [Break]

Okay. We're going to get started with Q&A. Two mic runners. So if you have a question in the room, please raise your hand, and we'll get you a mic. Okay. We have one here, please. Also, Peter, if you don't mind just saying who you are and where you're from, that would be great.

Peter Blostein, PB Investment Partners out from California. Thank you for the terrific event presentation. And I'd also like to just express appreciation for the management team, all you guys have done on behalf of customers and shareholders with this -- I mean, basically company reset and redirection and acceleration. It's quite impressive. Cognigy partners, management team buyback, all that stuff. Okay. So what I'd like to ask about is basically the big -- to me and others here, the big disconnect between the first half of the presentation and the financial revenue growth. When we go talk to customers, when we see the quality of the platform, it's phenomenal. The platform of the point solutions, Jeff made a terrific argument for it's going to be recursively self-improving, that's even better that customers don't have. Yet when we look out in the world, great AI products fly off the shelf, Anthrapic adds $1 billion of revenue a day. And yet we're here at mid-single-digit revenue growth and giving pricing concessions to customers who have a 7-digit ACV. Can you help bridge that gap and maybe explain the commercial strategy behind your choices which I'm sure makes sense but aren't apparent to us and certainly not apparent to the stock market. So any insight there would be appreciated. Thanks again.

I'll try to lead in please add in 1 thing to add. I think there's a few things. So first of all, if you remember what Beth had presented before, what we're signing up with our customers. So when we talk about record bookings growth and the backlog that we've generated and the backlog growing, the AI backlog growing in the 80 percentage the cloud backlog growing at 27% on the back of renewals and bookings, that is of a contractual commitment. Most of the AI growth is consumption-based. So if you look at what Cognigy did and all of its expansion, that 3x that Beth mentioned, that's all on top. That's not in what we report. So you've got a growth because -- and the TripAdvisor example is a really good example, and Disney did the same thing [indiscernible] when you were there. But if you take the TripAdvisor example, they started with those first 4 scenarios. That was the first use case, but it wasn't the most value-adding one. It was the one that they needed to get right first. Then they add more and more use cases. And so either they'll do that on a consumption basis, or they will just continue to rebaseline their agreements with a higher commitment. So first of all, it's exciting because the revenue will come. The second is, well, why is it not with Anthoopic and those examples? In the world of CX, I think you will have heard if you sat here today and you listen to Mia at Citi or Jack with Fabletics or John and the team here with TripAdvisor, CX they have to make sure it works. This isn't just a trial and expand. In the CX space, it has to be operationally resilient. So you take the Citi example of the complaints. They first had to qualify and make sure that the agentic was going to be as accurate as what the human was. That takes time and effort. So there's a lagging effect to that as well. But what we know is once they've implemented, once they've proven the scale, and it expands, the beauty for us is that we're then monetizing the interaction not the agent. I'm actually most excited about that transition. The economics of a per seat model, all of the advantage ultimately is with the customer. Now we want them to get huge advantage of course. But as the interaction volumes expand, and John mentioned it from Accenture about the bot-to-bot, every time that happens, that's an interaction, that's an experience we're able to then monetize that. So I guess the reason why we're saying we're being -- we're driving our outlook based on the real backlog, the real bookings, the real expansion, but we see so much potential for beyond that because that's what the Cognigy experience has been. Beth, anything...

Very well said. I think maybe just a couple of other things that I would add. I think the acquisition of Cognigy is new. You saw the really strong bookings and the impressive Cognigy contribution to that out of the first quarter, that's not yet in the revenue. And as Scott has highlighted, more and more of our revenue is coming from consumption and the ongoing agentic capabilities that we're adding. Jeff earlier today talked a lot about how easy it is for customers to and add on additional capabilities even more so as we look to the future in AI, yet we are also working with some of the largest enterprises in the world. I would use HMRC as an example. So HMRC is a very recent win for us, really exciting, very large customer, more than $100 million TCV, 8-digit ACV. So really impressive customer when we look on how that will trickle into the revenue, however, you're really looking in the back half of 2027. So it's the technology, yes, the customer can turn it on immediately, but large enterprises like HMRC or Citi you heard from today, they have their own programmatic approaches to how they deploy, what that looks like, and consumption continues to expand post adoption.

Peter, can you wait for the mic?

A brief follow-up is on the slides you presented of the customers resigning with a dip and then a growth with the AI coming in the second year, does that reflect the same dynamic of Cognigy's not really in that little bar on the right-hand side because it's consumption not contractual?

Yes. It's a part of the AI. So that first quarter, they were included because that was the first quarter bookings. The comment I would make about the renewals is -- and it's easy for me to say this, but directionally, I hope everybody probably understands where we're going. When we get them onto the platform, the growth takes care of itself. I need to make sure, we need to make sure that we have our customers on the platform. And by doing so, by sometimes using our commercial leverage, I don't think that's a playbook we will always need to do. We were very targeted, very strategic about it. Most of our customers will naturally go there. I mean we'll obviously, at this event alone, have an incredible number of new leads of existing customers. And so that doesn't require a lot of that commercial leverage. But it's certain places we do, and it was primarily around not about the AI growth. They knew they were going to expend on AI. That was a given. It was more, well, how much do I need to spend on my existing environment? It was really a question, if I wanted a multiyear commitment, what my agent count is going to be in 3 years' time is very different than maybe what the agent count is today. So we basically modeled that and then came to a win-win for both parties.

Okay. We'll take this next question from the webcast. What are the main benefits from a customer's perspective of having Cognigy fully integrated into the platform? And why can't AI native competitors recreate your platform and offer voice?

Hopefully, we've answered that a fair bit. But maybe, Jeff, can I ask you to comment on that one?

Yes, absolutely. I think the first benefit I talked about just in my session here, is a lot of contact centers are spending so much time managing these integrations between systems. We have lots of different systems. They're very fragile in how they connect. Of course, customers adopting our solution, they don't have to do that, right? We -- it's integrated out of the box. I think the second big advantage that we have is because it is one platform, learning loops, the recursive self improvement that I talked about, that's big. That's game-changing capability for our customers, and that is going to compound over time in a very big way. So I think those are 2 big benefits. I would say one third thing maybe is voice as a channel that we have obviously baked into the platform, and we're proven leaders there. Voice is really, really hard. And you heard [indiscernible] talk about that today as well. Building an operating voice at global scale is tremendously difficult. And it is going to continue to be a critical channel. So I think that's another thing that we bring to the -- in terms of the value proposition with all the digital channels, that's really hard for others to just add, right? So I think that's to consider.

And if I could just add 1 thing. I mean the rollout of voice, I mean you see voice coming back. I mean, you think of the AI world, think about how you interact with your business applications in your desktop, your business environment, it's going to change. It's going to be voice and it's going to be a voice AI agent that you're going to be interoperate. We're leading the way. Cognigy team, Jeff's team are leading the way, speeches, Techspeech, how does it work now speech technology. So our knowledge in voice more broadly is becoming a real thought leadership in this as well.

Anyone in the room? Right here.

Clarke Wright with D.A. Davidson. One of the initial pieces that you referenced early these data points was around 50% of the overall customer contact center seats are still on on-premise infrastructure. we'll love to understand the AI strategy that these customers have that you're engaging with today versus the on-cloud providers or at least where they're at today, as well.

This is -- I'll probably answer it and please chime in anyone. I'll try to simplify. Every one of those stand-alone AI cases that we solve with Cognigy are either an on-prem CCaaS customer or a cloud CCaaS. But when they're on-prem, they are choosing to do an AI step first before they then do the CCaS rollout. And I think you heard John and others talk about a multistep. Customers are in different parts of their journey. Some have already done a CCaaS move into the cloud. But they've got some other capabilities they haven't done their AI piece, and others are already starting on the AI side first and then moving maybe to the ACD or the contact center. Basically, our strategy now is now that we've got the one platform, we didn't really talk about it, but what Jeff's done is build a modular architecture. All of those boxes he describes is a deployment option. You can switch it on. And so what we're finding with customers who are in that on-prem world know that they want to move, want to benefit. They're taking modular pieces and they'll take some of the -- what we traditionally would have said in CCaas or in workforce management, they're taking pieces there and automation of AI agents, and they're doing that on the first deployment. So we're seeing really different rollout schemes compared to what they were before. And that's where Aruns' team working with our GSI partners become so important. So it's no longer, I've got it on-prem, I've got a maintenance window, I've got to flip. Yes, but that's not the only driving factor they -- and that's why 100% of our CCaaS deals, our 7-digit deals have AI included because they usually stop there.

Awesome. And just a follow-up on the deployment time lines. Is -- are you seeing those get consolidated as a result of a need to to see an ROI on AI? Or is that -- I mean, the on-prem to cloud was a multiyear transition. So I'm just trying to understand how we should frame this layering on that next step?

I'll let you add to it but let me just maybe start by saying, again, one of the reasons why this architecture is so important is it modular. It is so much harder to do deployments when you've got fragmented solutions within your own stack. That's why we didn't do Cognigy as a bolt-on. It had to be integrated because then you can switch on rather than reimplement because you're not reimplementing different technology. So the benefits of that from a rollout haven't -- we haven't got that because we've only just completed the integration of Cognigy into the core of CXone, but we do expect that to come. But do you want to comment on the...

Yes. I mean, I think it depends on the use case. So if you as a customer who's trying to do a proof of concept or wants to build a single agent for a single simpler use case, a matter of weeks. Somebody who wants to do a really complicated use case, could be a bit longer. But if you're looking at trying to deploy the workforce management solution or the other parts of the portfolio, integrate that into your back-end systems, that obviously becomes a multistep process, if you would, very much like I did in my previous role.

But I guess just remember the question, how do we think about it? AI deployments are faster and they're more agile, and they will become more and more so as time goes on with this integrated platform compared to what you saw in the CCaaS where it was a pretty significant shift in particularly given complexities of voice.

Okay. We'll take this next one from the webcast. Can you talk about the switching cost from a customer's perspective once Cognigy is deployed?

the switching cost to move away from cognitive?

Yes.

Well, I guess the first comment I would make is we haven't seen it. And I don't say that with arrogance and I'd just say that with reality.

100% at the enterprise leve.

100% at the enterprise level. I think I think there's 2 things that I would say about the switching for -- in the AI space. Once you've established the platform, and I think it just reinforces why we're so focused on the platform. Once you've established it, it works. The AI agent is not the hard part, it's the operating intelligence and the plumbing that sits underneath it to make the AI agent great. And so we've been really focused on helping Cognigy get a richer data context, a richer orchestration even with its existing customers benefiting from CXone from NiCE and then for all of our new customers, getting that out of the box. So I do -- I expect we've not seen any retention risk of those customers. And it's not so much about switching costs. It can move to another AI agent. But if you're going to move to another AI agent who doesn't have that operational context, doesn't have the richness of data, doesn't know how to work with the humans that are in the contact center, doesn't know how to do a combined workforce, why would you? So it's a great product in itself and it stands tall by itself, but now is an integrated suite even stronger.

Can I add something?

Please

So I think the added thing I would say is that if it's a stand-alone agent for a simple use case, which is not connected to your systems of record or your back-end systems, it's a much easier thing to do. But the real value from these agents comes when you actually like the Lufthansa example or the Fabletics, you connect your agent to your back-end systems, and that's where the real ROI comes from to be able to resolve real issues and drive containment and better experiences. Once you start building those integrations, the switching cost becomes much harder.

I've got to say, 12 months ago, what you heard from Fabletics today and going after the moments that matter, that was not the way customers were thinking about AI that we're going for the simple repeatable tasks. Now they're thinking, okay, this can do some really interesting complex things. The Lufthansa example, the Alianz example, there's so many examples where we've got -- and I think that then drives that stickiness that we're expecting from the platform as well. So it gives us confidence that once they're using it in that way, switch out is very unlikely.

Anyone in the room? Let's go right here, please.

I'm [indiscernible] here for [indiscernible] on William Blair. Scott, at the end of the keynote, you had mentioned many customers already have access to AI features, and you encourage them to better utilize them. So I'm curious to hear how prevalent is this underutilization and what NiCE is doing to help support adoption?

Yes. You can probably, by my noting you probably sensing a little bit of my frustration. We have got an incredible installed base that are already using CXone. And because it's got CXone has now got Cognigy native, we've now got this inherent capability that is available that can be switched on. Now yes, if you think about augmentation, so agent augmentation, Copilot, there's still configuration and work to be done, but it is not -- we don't need to go through contracting. We don't need to -- it is simply being able to switch on a service and being able to expand those use cases. And so we're trying to make it simpler both commercially, but also from a deployment point of view and being able to do that more easily. So auto summary, like automated summary is such a simple, easy thing that we can roll out and deploy on voice calls, on digital chats and on AI agents that we're able to roll out. So it's now -- it's been more a case of us showcasing and unlocking that in making that visible rather than any resistance from the customer. There's no resistance from that side. But we also need to remember that we don't want them to be thinking about another tool to do chat. And another tool to do summaries, we've already got it out of the box. So that's the reason why I highlighted it. And we're very excited about the land and expand opportunity that, that brings. I've got to say again, what Jeff and the team have done for us allows that to be a switch on rather than a deployment. It's such a critical task that maybe I didn't represent as well as we could have when we talked at Capital Markets Day. This isn't just about the integration of an acquisition into our tech stack. It is about the underlying foundation that allows us to create that value model for our customers, but also for us. So it's a really important work that we've been doing over the last 6 to 9 months.

Can I just add a little bit of a customer kind of view as well, and, Arun, feel free to jump in here. I think one of the things you probably heard in the keynote is how customers have highlighted that our approach in working with our customers is really understanding their pain points. It's not about trying to push our solution on to them. It's really trying to understand what we can do to help them on the ground deliver their best customer experience to their own end customers. And I think that last night, I had dinner with a few customers as well, several of us did. And I was really excited to hear how they talked about how we are collaborative. We don't just go in and sell. We're collaborative. We continue to maintain that relationship. And I think that's also what blossoms the ongoing relationship and adoption post deployment.

I mean I lived it for 4 years, so I know.

Did I see a hand on this side of the room before? Okay. We'll take this next question from the webcast. Can you talk to your planned usage of forward-deployed pods? Is this a shift in strategy? And is it scalable?

Do you want to come on that?

Yes, I can do that. So it is not a shift in strategy. It's a complement to what we have already been doing. So we basically have enterprise grade deployments, as I spoke about. We have a full deployment life cycle that we discussed. This is an additional tool that we have complemented by the nice labs that we had -- we announced this morning. The intent is to basically how do we quickly deliver value to the customer. So this is a huge complementary solution. It is not a shift in strategy. And what we are doing is we're making sure that the AI COE that we've built, our forward deployed engineers are working synergistically, anything that we learn from the FDEs is fed back into the AI COE to ensure that we're building it into a repeatable framework unlike many of the point, AI solutions were essentially relying on scaling their FDES, which is not an economically sustainable model.

Peter?

So something that just clicked for me listening actually after thinking about this quite a bit, is that this business is transitioning from CCaas, right, enterprise -- a SaaS model to a platform. And platform -- building a platform can be a very, very valuable enterprise, but it involves decisions that might be different than those decisions you make as an enterprise SaaS company. Can you talk -- Scott, you're nodding, and I'd like to ask about your experience at SAP, and Jeff, your insights from Microsoft building platforms. How is that different than building SaaS? And which KPIs -- we should probably look at different things as you think about building a platform and what should those be, customer count, Cognigy sign-ups, what have you? Because you said, look, what's important is to get on the platform revenue growth takes care of itself. The stock market doesn't get that. And so I'm trying to understand, look inside your brand is what you see because you see something different and exciting.

So I'll start. And Jeff, you can comment on the technology side and your background as well. So the platform strategy is so crucial to the way forward. And let me just take a few of the indicators of why we believe that to be so. CCaas was built primarily from a human to enterprise on a one way. It was an inbound and it was a time-bound exercise. So it had limitations about my time and the enterprise's ability to absorb it. That's why you could never see the contact center phone number, they would never look to find it because they were capacity bound. And as human, we didn't want to be sitting on the phone waiting the whole day. So it was built on that construct. The world going forward is going to be an unlimited interaction model. There is literally no limits because your time and the organization's time are no longer the constraints. Now to deal with that scale, you have to have a platform that handles scale. In my background, you're right, at SAP, we dealt with the most mission-critical environments, and we were very clear when I was there that these business applications that were sitting on top, the orchestration, the data layer, the foundational intelligence was built that everybody leveraged. And that means that when you thought about a customer context or sort of supplier context, you could think of it in all of the different suite of applications. So for us, in the CX space, what does that mean for us? We're not limited to service. It's really important right now. But with proactive, you get to be able to do sales, marketing, outreach. You can do revenue generation, service volume increases, we can switch between AI and human. It's really going to be a design toggle for companies to say, "Look, we've got this really critical moment that we want more humans in the loop and we want them to be interacting because it's a really critical exercise." We're going to turn that up and do less of our AI agents. This is a typical business day we'll do more on the AI side. So it gives you that operational flexibility. And for me, ultimately, as the CEO of this company, it gives us much higher predictable revenue growth. I don't want to be only worried about the CCaas to on-prem migrations, I'm looking for platform expansion, how the market consumes and we clip the ticket every time and be a valuable addition. So when we think about our revenue model going forward, I'm not thinking about only the bookings and the backlog, I'm thinking about the market expansion and how their platform can be the monetizing angle to it. Jeff, do you want to add anything?

You covered a lot, but, yes, I would just say, if you're fortunate enough to have enough scope to really go after a platform approach, which we obviously do, there's both internal or obviously an external benefits. The external, Scott touched on a lot of them. For customers, it's just start wherever you have the most urgent need, expand from there, and there's just a whole bunch of stuff the platform takes care of, fully integrated, we get some -- like even in the past, there's some form of learning loops, leveraging the data, leveraging the knowledge of that stack, lots of customer benefits there. But one thing we shouldn't overlook is the internal benefits of running a platform play. And especially with NiCE, our heritage again is voice. I can't emphasize enough. Voice is really, really hard, mission-critical, massive scale. And we take all that heritage and now we apply it, we can just make that same investment, but then we get all these returns across all these other workloads. And by the way, they become industrial strength, mission-critical because that's just what we do. And all of it is sitting on that same platform. So I love where we have come from, from that voice heritage and everything we're doing now sits on that. And so we get tremendous leverage from the engineering, the operations across that entire portfolio. And as Scott said, it's expanding, and so it's gotten great...

And I sure have added 1 last thing it's a conscious decision. When we acquired Cognigy, we could have easily just said, let's add more function and feature in Cognigy, let it run, we could have, but we decided to integrate it because the return is not necessarily today, it's what we are able to get into the future. It was the opportunity that we felt differentiated us and gave us a winning advantage. So that was the other thing about conscious.

And if I could just add we did talk about this. We weren't going to -- if I could just add 1 thing, we didn't talk about it today. We believe that, in the future, the volume coming into contact centers is going to increase exponentially. We're all going to have AI agents going out. We're not going to call up 1800, whatever it is, we're just going to tell our agent go handle this, go find this product, go return go figure it out for me. And if some event happens globally, guess what, millions and millions of AI agents are going to go pound on these brand websites and all these engagement, whether it's voice or digital and all that. And so that platform approach for customers coming on, whether it's Cognigy, anywhere on CXone, they're going to be ready for that, especially as they get that front door in place and all that mission-critical platform is going to support that. So I think that's really important. And I think customers are just starting to think about it. But getting that digital front door in place with someone like NiCE who can handle just incredible mission-critical volume is going to be important in the next generation that we're heading into any day. I don't know if it's 6 months, 9 months, but those personal agents are coming and when they're good enough, it's going to happen really quickly.

We have time for 1 more question. There.

I'm Kincaid from Citizens. I work in your Pat Walravens. I'm really, really excited by this idea of recruitingly self-improving your guys' systems and using your data from a human to improve the agents. This is something I'm a data scientist, my bachelor is in it. So I really, really like this. My concern is that that's something that I've seen the big labs targeting as well. This seems to be their strategy of how they want to continue to improve their systems. How do you retain engineering talent when you're targeting the same type of problem that they are and they have such a large gravitational force behind them?

So I guess there's a couple of things. First of all, specialization matters. They might be doing that at a general level, but there's a reason why there's a whole lot of AI companies in the CX space that are dedicated because those companies, when you get to the granular needs of what happens inside of a customer interaction and the complexity and the knowledge framework and the security and all of those other things and the operational systems, it takes penetration. It's why, for example, I've made the decision that we don't go into HR flows. Our platform, Cognigy could easily do help desks and -- can you easily do that, the core platform, but once you get into the specifics, it becomes a lot more granular. So first and foremost, we're targeting -- the depth of the problem we're targeting is different and it's unique and it's focused. Having said that, capturing engineering talent, I think capturing talent is matched to the story and the vision that you're driving. So we have engineers who love the world of customer experience. They love the idea of creating a platform that makes your life better. I had this analogy. My first job was a paperboy, and I loved it because every morning, I got up and through papers and somebody had a great day if it was on the front doorstep. In the world of customer experience, our engineers, and I'm telling you, they love this. They love the fact that their technology has made millions of people's day better. So I think when you're capturing because you can be an engineering, you can do all sorts of interesting things. We try to connect it to our vision. We are always in the war for talent. I would not lie to say that we're not always looking for the retention and the expansion, but that's where great engineering leaders like Jeff makes such a difference because you want to work on interesting things. You want to be able to build our products. And I've got to tell you where we are as pervasive a user of the AI technology, the front-end models, as any software company on the planet, and we're getting the benefits...

And Cognigy, our entire IT help us actually does run on Cognigy just internal internally. The fact that it can run, but we chose not to put it externally out there.

We've not been challenged on the war for talent. But I also think we've been looking for scale. So we're not -- the opportunity with all the AI tools has allowed us to get expansion and efficiency and innovation without necessarily continuing to add a lot more people and our operating margins reflect that as well. Very good. Well, look, I -- first of all, for those of you who are in the room, I hope you found it interesting. Hopefully, we've been able to unlock a little bit for you about why we're so excited about the opportunity where we're at on that journey but also the validation from the customers. For those of you who can, we're going to join you in the show floor. For those who have joined us online, thank you for joining and listening in. We're in a great place. We're in a great market. I think you've heard from both myself, but our customers and analysts, the amount of investment coming into this space is incredible and we're the leading player. So we're looking forward to capitalizing on it and making sure we deliver durable shareholder returns and great value for our investors. Thank you so much. Appreciate it.