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 talk about the agenda. In just a moment, we'll start with our CEO, Scott Russell. Scott will hand it over to Jeff Comstock, our President of CX Product and Technology. After that, we'll hear from TripAdvisor. Arun Chandra, our COO, will be joined on stage by Accenture. 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. 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. 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. 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. 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 era of CX in AI. A few data points, and I've just got off stage, so I'm still in the buzz of being in that theater room. It is a great event. NICE World, we've got about 20% increase year-over-year, we continue to get more and more customers. What's really interesting is the proportion of non-CX customers, but are interested in the journey. Even last night, I had connected with five 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 their AI move, whether they were going to do it all. Their journey was part of the conversation, not just the destination. 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. 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. Today very much is a representation of where we are, but the opportunity of what we're going to be. Let me start there. I want to start with the market that we're in, 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? 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 Heltewig mentioned on stage and it's the personal agents. Personal agents are expanding this market dramatically, we're already seeing it. The way that you interact with a brand might have been through a website before. Now you're going to interact with an agent, an agent's going to hit a CX platform who has to respond to it. It's going to be AI to AI or AI to human, it's going to proliferate. I know personally, I have five different agents, PA agents, workforce. I do things for productivity tools. It's easy to build and deploy. I don't do it much in a professional context yet, but that's coming. On a personal side, it's already there. You're seeing companies on the personal compute space are already offering that. It's also expanding. 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. It hasn't increased, it also hasn't decreased much either. Whether that decrease happens as we all predict it potentially will with the less humans in the contact center, the volume of interactions far outweighs it. It's growing and it's expanding. That expansion means a proliferation of enterprise AI agents. It means that the digital volume and the interaction that we receive is expanding. Of course, the thing that we know for sure is that the on-prem base is still far from done. Again, those customers that I spoke to last night, of the five, three 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. We've got a considerable growing, expanding market, 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, 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 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. 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. 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 at an 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. We've combined it together for end-to-end orchestration. 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. 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. 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 intents, 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. If you think about 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. 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, building upon what I had mentioned before, is AI in CX, we believe, is reaching an inflection point. The market, we're just scratching the surface of the opportunity. The AI market is huge. You think about the volume of interactions, 3%-5% of the volume of interactions today are hitting the AI platform. Most of it is pointed at single tasks. 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. 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. Whether you start simple then move to the complex or do what Fabletics did, then they started with the complex and then they rounded it out with the more simple, the platform is built to provide that value. When you're going from simple automation to really embedded complex capabilities that can handle the scale, you're going to buy differently. You look at the technology differently because it has to work. The historical adoption patterns, this full enterprise CX stack, we're already seeing it. One of our proof points, 100% of our deals in CX and CCaaS over the last three quarters, I think maybe since I've been, at least in the last three 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, then they're figuring out how the overall CX platform delivers their end-to-end needs, their human management, the AI agents, the human agents, and how that operates together. 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? I'm going to have to either use a CCaaS platform then go an AI platform maybe multiple AI platforms, I'm going to have to figure out how to integrate it's got to work at mission-critical scale. When that Lufthansa flight cancellation, you get 20 million interactions within the one 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. We know it because that's what happens in CCaaS today. The only difference is in the CCaaS world, it's only human agents, it has the same expectations from companies. Big brands, they need a platform that will be able to work to that. We made a choice. We didn't have to integrate Cognigy into CXone straight away. We could have kept it bolted on, we would have been able to offer that as a really value-adding offering to the market. We bolted, we integrated because we knew where the market was going, not necessarily how they were always buying today, how the market is going to need that capability in the future. That's where CX is providing an enterprise AI, is where CX proves it at scale. We have high volume. I think everybody would recognize that the CX market is one of, I would consider, the two 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. 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 then she's going on to human scenarios, and then she's going to go into different scenarios. 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. Last but not least, it's obviously high consequence. Revenue, loyalty, cost. This isn't a cost play for many businesses now. They look at this platform and see, 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? 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 confident with our win rates when we're able to offer our combined NICE Cognigy CXAI 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, there is 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. What it means is it's a risk when it comes to the enterprise AI space. Last but not least is I haven't yet met a customer. Sorry, this is not true. I've 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 agent 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 one way or another. 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'll 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'll be a much more seamless experience. 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 standalone 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 number one 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. If they are, they're nowhere near. The richness, the capability of this platform as a standalone AI platform in its own right is fantastic, and we try to compete and win on that. 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. 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. 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, they try to figure it out on their own. It's AI on CX, not in CX. 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 context in a contact center, we're now applying that in the AI world, it gives us opportunities to automate where we never could before, it also gives us the ability to learn from those different, 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, it makes that element even stronger. 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, burnout, challenges around attrition. You're using the data, the knowledge in a way. 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're nowhere near going to get the seamless experience. 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 three quarters. Our backlog is growing. Our AI is flying. That is in a market that is in very early days of what the markets demand on the AI side. 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's 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 eight-digit deal or a nine-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 CXAI platform operating with over 30,000 agents operating at scale, that's why they chose NICE. Let me move forward. Clicker. I'll move quickly. We've got an expanded role. We're 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 and the ROI. 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. 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. 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 will cover the scaling outcomes with Jon from our Accenture team. Then Beth will wrap it up in a monetization of how it all looks from the monetization of the platform. With that, Jeff, I'm going to hand over to you. All right. Good morning, everyone. 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. Before they onboard to CXone, what do they really look like from a conceptual perspective? 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. 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? On voice, they've added IVRs, digital channels, live chat came out, social messaging channels, they added those. They added the first generation crappy bots that we all had foisted upon us, virtual agents, and of course now today, with the emerging, very powerful agentic agents. They've assembled all these capabilities to run a basic customer experience function. Here's the problem with how all that got built out. Historically, no single vendor had even the majority of these capabilities. They've had to go add each one of these, they've had to bolt it on ad hoc over many, many years. 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. They've got to manage these fragile integrations between these systems, right? For these enterprise contact centers, that represents tremendous cost and complexity. They're spending a lot of resources on this, and they always have. That's coming at the cost of focusing and delivering incredible customer experiences. That's what they really want to be focused on. This is why the platform approach is so valuable. That, of course, is the path we've taken with CXone, right? CXone spans all the big three 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. 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. 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. All on one platform, it's all in one place, powered by CXone. 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. AI needs those capabilities, all that data, so it can reason over it and use that data to drive outcomes. Across all three areas of customer engagement, we lead. NICE is in a leadership position in every single category. 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. 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. We are leading in the CX platform space, full stop. We built this platform for adoption flexibility. 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 adapters. We easily slide into that fragmented landscape and customers can get going. Then from there, they can expand, right? As they expand, they get two big benefits. Number one, of course, they can start retiring all 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. Arun will talk to you through how we leverage this platform advantage from an architectural perspective in our land and expand delivery motion. Okay, in each one of these categories, we also have incredible depth and breadth. This view does not even scratch the surface. 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. By the way, all these capabilities are sitting on the same CXone platform, that same enterprise-grade, high-volume, mission-critical platform. It also supports the very long list of security, privacy, certifications that the most heavily regulated organizations on planet Earth require. We cover that. Of course, the latest addition to this platform is Cognigy, as Scott mentioned. Cognigy is now native to CXone. In our last investment day, I think that was in 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. 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 and Agentic AI layer for CXone. That means it's one application experience, one shared data layer, one set of communication channels, voice, and all the digital capabilities that we have. 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. We have a few more sovereign clouds to deploy. 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. Cognigy is now native, and that means it's already the conversational and agentic AI capability. 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 a role of specific copilots in our existing products, those are now completely replumbed with Cognigy. That means they even have more tool use, more agentic capabilities. Our existing customers with existing products now have more value, making those products more valuable for them, even stickier from that perspective. 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 loops. As we all know, Cognigy, standalone product, very successful product. Customers are achieving 60%, 70%, 90% resolution rates, depending of course, on the intent. What happens to that 20%? It gets escalated to humans, right? 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? How do they get it resolved? 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. 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%. Basically, it's a goal-seeking loop that is goal seeking to just get more and more automation done past that 80%. Okay. Basically, at the end of the day, with every engagement, the system is just getting smarter and smarter. Customers are choosing us for these types of platform advantages. 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 our platform. Okay, 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. 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. One of these launches that we have this week is called the Agentic Engagement Plane. Just think of this as an enabling layer that puts AI agents on the same level playing field as humans. I will just give you an example to give you a sense of what this enables. I will tell you, this is a game changer. AI agents are so powerful today, this engagement plane just sort of unleashes that. Today, when an AI agent has trouble, it doesn't have quite the confidence to close the issue, what happens? It gets escalated to a human. With this new plane, the AI agent can now just raise its virtual hand and say, "Hey, I don't have quite the confidence to give 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 hand held. The human supervisor can go into that conversation, see the whole scenario, the conversation instantly, look at the scenario, say, "Go ahead and give that return voucher. Go ahead and okay it." Then the AI agent can go continue the conversation and close and automate that whole transaction. 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. By the way, there's a learning loop. Next time there's a scenario just like that, it knows that it can go ahead and give the return. This is a good example, I think, of how we're really changing the game in terms of that 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 those fleets of AI agents. Next, workforce empowerment. Across workforce empowerment, we're redefining what it means to manage this workforce with humans working alongside AI agents. We're extending that 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. We're delivering very targeted optimization loops there, right? 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 engagements. 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. This is where we've built a fleet of highly specific domain expert AI that 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 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. 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. We've basically bootstrapped 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. We have a set of tools for observations and just managing this at massive scale. Guardian AI is another key development 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, I'm happy to welcome up, from TripAdvisor, John Hanley and Dave Fox. Just down here? Thank you for the intro. Thank you all for inviting us here today to talk about our journey into the world of AI. I recently joined TripAdvisor around eight months ago. I head up custom operations and responsible for defining the strategy. My colleague. I'm Dave Fox. I've been at TripAdvisor for rather longer, about eight years now, and I 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. When I joined, I totally changed our strategy. We were a human assistance first organization, 100% using, obviously, BPO outsourcing. Hopefully, you all know who TripAdvisor are. It's one of the oldest brands in travel. The most exciting part of TripAdvisor is Viator experiences. This is our growth engine. This is what gives me and customer services our big issue. How do we service this hugely vast part of growth of our CS with this human assistance team? It was quite clear to me from day one 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? Because we have part of the data, our suppliers have part of the data, our tour guides have part of the data. A poor human being, as much as we can give them amazing tooling, they really slow down that conversation. We knew we had to go into AI, and fast. I set a very tough demand on my team. How do we in 90 days figure out our strategy, our investment, and go live? Of course, everyone said, "You're joking, John. You're crazy. This can't be done." I think it can be done. In those probably two or three months, we saw so many RFPs from other bidders on the world of AI. Every week I almost got a bid coming in. For me, the problem wasn't about call volume. 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, trying to hide the phone number, knowledge bases, and chatbots, right? IVRs with 75 options. I think we have 15, actually. I hate it, despise it. For me, 15 years ago, I was really passionate about enabling the customer first. For us, we had to find a technology that enabled this solution and not just deflect our customers. Dave, you had 90 days to implement. Tell me, how do you do that? I started off by swearing a bit, I must confess. 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 describes, you need to have a front door through which they can easily walk in and you can help them. 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 wanted. We'd then have to go and find out, is that really you? Because we can't just let anyone change somebody's booking. We had to go and find the booking. We had to find the detail. 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 four boxes on that slide, typically takes a couple of minutes. Not very long in the scheme of our lifetimes, perhaps, but it's an awful long time when you've got someone tied up for it that could be doing something else. That two minutes was the first place we had to look. John, if you can just skip on, please. To do this, we built Vesper. Not my choice of name. It's catchy. 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. The only way we could do that is not to have some bot which we bolt onto the side, we transfer across, like you forward in your call to your voicemail. We need those calls to be a voice inside of our architecture and something that becomes part of a seamless journey. If you'd step on again. Yeah, I think just a quick call out there, Dave, I think on the session this morning, which was awesome by the way, the key word that I heard was, if you're going to invest in AI, don't do the easy thing, do the right thing. So many people, even as of last week, were saying, John, chat is the easiest thing to do for AI. Absolutely. You know what? For our customers, we sell an emotional product. When you go on vacation with your family and friends, you don't want to be chat botting. You want to call somebody. Okay? We knew voice was absolutely the place to start. Unfortunately, what Dave told me was it's also the hardest. Absolutely, I will go to my grave saying voice is the hardest as a telecoms engineer. I do valuable work, John. Take that back to HR. Not only do we have to have these calls, and from an engineering perspective, and none of you guys need to hear about the engineering of it's way more complex just as the simple mouth to ear delay. In a global environment, the speed of light gets a bit slow. Also, it's a big black hole, what we talk classically to customers about. With chats, you have a transcript. With emails, you've got a mail trail. 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. There was this huge black hole historically of information which we couldn't see. For us, that was an untapped resource, an untapped opportunity. The guys through the presentations have talked 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 who's got an issue? Is it actually an issue which we could fix by moving the big blue button a couple of inches to the right on our website? 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? Yeah, I think one thing I had a problem with was, it sounds good, I think the technology's there, I thought to myself, actually, will our customers accept voice AI? I'm on vacation. I'm with my family and my friends and seeing the tour buses and turn up. Am I going to accept some kind of chat AI kind of talk to me? The big bet, the big investment wasn't necessarily the risk of who we go with, I think we've picked someone fantastic. Probably proof of concept that we did actually was, will our customers accept voice AI? That was the unquestionable that we had at the beginning. Absolutely. Why did we choose NICE? We're a long-standing NICE customer. We've been a CX customer, a CXone customer for many years. It's done a great job for us. They were always someone we were going to talk to about this stuff. Scott, from everything you said, you'd be quite pleased at some of my reasoning here. 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 you, 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 bloke's asking me to deploy bots in 90 days. 30 days. More. You changed the goalposts. 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 to have, 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 delay 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. They had a track record. We trust them. I see them, again, it was mentioned in the keynotes, as something of an extension of my technical team. I'm sure, John, you see it as an extension of your customer- That's right 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 in there with us. Thank you. Yeah, Dave's a techy guy. He'll tell you the important things about a single platform, but it's true. My demands are fast, not because I'm getting older and grayer. It's because we were late starting the journey like so many CX organizations. Unquestionably, it's not a speed to finish, it's a speed to start. I think it wasn't the risk about jumping in, it was the long-term part of things. I think for me, when I was talking to other organizations, they tried 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. NICE, honestly, was the only organization that got it. He never talks about cost reductions being the primary focus. It's about solving the issue. Now that we've actually launched Vesper, which by the way, can I just tell you, I go out drinking as a guy from the U.K., I don't talk anything other than Vesper. I actually play Vesper on my phone live. I get my friends to call Vesper, and they think it is just freaking awesome, right? We launched in 45 days after we did the contract. 45 days. It's incredible when I think about it, what we did. Vesper is version one, and now we've internally hired a bunch of people to kind of really grow Vesper into version two and version three, 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 proactive side. How can we figure customer problems before it's 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 the destination to find out there's a problem? Nobody. Standing there with the family and the kids shouting, "Daddy, Mommy, how long until?" I am phoning customer services, give me an hour. There's a 25-minute wait. It's horrendous. What if we could solve the problem before it's a problem? NICE really understand that journey that we're on. Things like, what if we have bad weather and you can't go on the tour that day? How about we just rebook it for you for the next day when the weather's fantastic, rather than phoning customer services? This is the part that we're starting on. This is just the tip of the iceberg. In fact, if you talk to my account manager from NICE, I sent three emails in the key sleeps this morning going, "Can we, can we, can we, can we?" There's so much opportunity. For us, for Viator and TripAdvisor, yeah, it's all about putting the customer first, and this is really exciting. Thank you. It's been a great partnership and we're thoroughly enjoying it. Thank you. 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 six months ago, I was at Disney for four years, transforming the CX function that served over 180 million customers. Using the NICE platform that Scott and Jeff spoke about, I modernized the end-to-end CX stack from a digital AI front door to CCaaS to all other aspects of WFM, 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 roadmap 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 pre-built connectors and APIs to common systems like CRMs, 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 DEVone ISV apps for the platform. 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. Finally, 70% of CXone 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 CXAI 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. Third, the opportunity to win seven, eight, and even nine-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. healthcare 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. Rather than me speak to it, let's hear directly from Accenture. Joining me on stage is Jon Bold, Accenture's Senior Managing Director for CX Solutions and Ecosystem. Great to see you, Arun. Welcome, Jon. Thanks for joining us. Absolutely. Jon, 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? For years, CX has been a top priority of our clients. Why not? Because 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 when it was customer experience, you had marketing, you had digital and so forth. The laser focus on service is amazing. Secondly, think about over the years, that investment was going onto digital. It was drive self-service, better web, better mobile app experience. Now, even with all of that, still voice, I agree with you, TripAdvisor, voice is so hard. There's still so much that goes into voice. Now that investment's into that channel. With the promise of AI, what they're seeing with conversational, our clients are, the objectives, our C-suites, our segments from our leading companies, they want 40%-60% reduction in the cost to serve. At the same time, they want to see NPS increased by 2x-3x across the board. That sounds like the Fed's dual mandate. Yeah. High employment, low inflation. Bingo. Deliver exceptional experiences at the lowest possible cost to serve. Yeah. There's nothing wrong with that. I know people say it's not cost. It's still a big one. 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? Because our customers now want an AI-powered contact center. Remember, a contact center, a lot of people think it is the same as call center. It is not. There is a reason it is called contact center. It is omnichannel. They want an AI-powered one. The other thing is, you will hear Julie Sweet, our CEO, say it quite a bit, our C-suite is going, "When do I get the value from AI? I am watching everyone else get value. When do I get the value?" They are seeing, wow, if I had an AI-powered customer service, I can get there. Number one is they want companies who actually get customer service. NICE does. It is at your core. Secondly, we have that, so it is a nice match. Third, they want a platform. They do want a platform. NICE has it all. They really do. They now have the CCaaS, the IVR and routing, the workforce management, the intelligence. You saw Jeff Comstock's slide. It is a perfect blueprint of all the capabilities. NICE now has them. What is super cool about NICE is that you can start anywhere because our clients are at a different part of the journey. They all are. They have different parts of the components, and you have such a huge install base. We will go in there where you have workforce management and make an impact there. We will 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. Finally, we are still doing, I love how you guys said it, CCaaS is not over. There is still massive CCaaS plays to be made. We can start anywhere and expand from there with outcomes. That resonates. I have 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. That is great. Let us turn to AI for a moment. How can we have this conversation without specifically focusing on AI? For sure. The market is flooded with point AI solutions. Yet, Accenture decided to invest meaningfully in Cognigy on the NICE platform. Why bet on an integrated platform versus one of the point solutions? Yeah, the reason is because at the end of the day, point conversational AI solutions are interesting. They work. You have to make it work within the IVR, in the telephony stack, within digital, within all of the different channels. I think people underplay that, and that's why you're seeing this. Again, I wanted to give you some provocative points that I found so interesting over my years. This move of having to have people skilled in digital. Now, all of a sudden, you need to take that digital skills and apply it to the telephony side. Therefore, we like that Cognigy and that AI has at its core, integrated in the platform, how to work holistically within the platform. Let's make it. Also, at the end of the day, the number one slide my clients use when I work with them is the following. They need to get to that 40%-60% improvement, and they want to do it. You have to do it across all the layers. Number one is where you heard TripAdvisor go, proactive. Yep. We've been doing proactive. We, in fact, had a proactive messaging practice in our firm. We were already for years doing multi-day journey management. Take the telco space. When you actually have a problem with your router and you need to schedule an appointment and manage that appointment, we would do that all through multi-day journey management. We're actually managing the appointment, checking if they're going to be there. If they are, have they touched the equipment? When it's done. That has been applied to in public service. We've used it in healthcare. 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 where TripAdvisor was. I know I said you guys four times. I was really impressed. That's where you get the most bang for the buck, at the top. If there's an inbound call, can you then contain it? 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. 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. Come on, that's been so frustrating, right? So frustrating. Needs to pick it right up and then help the agent then make that a smooth transition. Finally, agent assist. 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. Yep. After you've handled a claims conversation, you actually kick off the forms, kick off the processes to make it work. You're thinking, "Well, that's three levers." People forget. How about running the contact center? There are hundreds and hundreds of people in these contact centers who do quality assurance, and they do quality assurance on 5% of the calls. You can now automate quality assurance. You can now automate the routing. That's another lift. Finally, how about growth? We're now doing proactive outbound calling for leads that come in. You have a call in to say, "I heard you're interested in some wealth management products." The voice sounds fine, they take it, and then it kicks off a lead in a sale. You got to put all that together, and what's great is it's all integrated in one platform. 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. Jon, we built a lot of real momentum together. Looking ahead, where do you see the biggest opportunity for our partnership and what excites you? What excites me is getting to true agentic customer service. How many of you are right now going, your first question is going to Gemini straight up? You are. You're going there for the answer, and it's good. 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 healthcare, we already had a situation where you have the providers checking in with the payers whether or not the coverage is there, what is covered, what's the different rates they have to charge, and so forth. The bots are hammering those calls. If you don't have bots to handle those calls, you're getting crushed. Bot-to-bot is happening. You have to become agentic. What I love, that's where the future is. What I like is by having this platform, we can get there. 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? 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. Jon, I want to thank you for taking the time. Sure. We're excited about our partnership, and we'll do wonderful 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 Jon. I think following that, it's clear 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. We're really pleased to hear that directly from Jon. 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. You heard from Jeff. 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 TripAdvisor, how they're already realizing measurable, proven outcomes from our platform. Again, of course, our partner ecosystem is really accelerating that adoption around the world. Now I want to take all of the things that you've heard today so far and the one connected story, and talk about how we're actually monetizing that and driving durable ARR growth at NICE. 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. 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. That growth was 66% over the same quarter of last year. That 14% is up from 8% of our cloud revenue contribution just two 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 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. 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. 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. Finally, broader product adoption. 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 install base, but also to offer that into new logos as well. 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 specifically that they do not need to re-architect their environment to add these additional capabilities or Cognigy, because everything truly is one integrated native platform that we offer. This dynamic across the platform is particularly powerful when we look at AI adoption. AI is our growth lever, our number one growth lever here at NICE, and it's extremely easy to continue to add that capability into all of our customer base. 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. 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. 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 or revenue per customer or their 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. 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. We see this pattern of expansion over time, and this, of course, was again prior to the acquisition of Cognigy. 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. 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 through the deployment of our AI. 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're also maintaining the non-AI revenue layer intact. Of those customers, about 7% of the ARR was coming from that AI contribution, specifically. They're adopting the AI as well as really having the benefits of the strength of the platform of CXone that's fully integrated. 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. 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. Once Cognigy lands inside a customer, you can see that the adoption is rapidly expanding. 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 quickly. Then, of course, they start expanding. They expand into additional use cases, additional workflows, operationalizing the full journey of the customer. That's really a textbook land-and-expand motion that we're seeing. As you see here through the 2022 customer cohort data, those customers that had adopted Cognigy in 2022 have a three times 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 three times since that same period. 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 install base that we have here. 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 three years. 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 has 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. That stickiness and the land-and-expand motion is exactly why we reached out and proactively worked with a small number of large marquee customers 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. 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. Now I want to just walk you through two of those customers that we were referencing. The first is a Fortune 50 enterprise customer, and this customer has an eight-digit ACV. 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. 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. 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, 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. The second example is a utilities enterprise customer, which is a seven-digit ACV. For this customer, you can see that we expect to have a significant uplift to more than double their ARR in the coming quarters. For this customer, really our ability to capture the platform economics 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 and adopt more of their AI capabilities in the platform. 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 quarter that just passed, and it's also really highlighting the strength we have in the Cognigy bookings. Importantly, the Cognigy bookings, you can see is broader in terms of the bookings we're achieving with going out into our global install base with NICE customers. In addition, Cognigy is continuing to sell standalone across their customer base and other new logos as well. 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. 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 CXAI platform. 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. 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. The monetization aspect is still in the very early stages of adoption and scaling. 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. I want to conclude and before we break for Q&A, to really highlight three 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 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 install 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 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. That's why coming it all together, we believe we are uniquely positioned to benefit from both interactions, which are human-led or AI-led, all through, again, our integrated CXone platform that we orchestrate across the CXone offering. That's why we're confident that we'll continue to see durable ARR growth. Looking ahead, we have multiple data points, a strong, solid Q1 that we came out of, increasing backlog, 66% growth in our AI revenue of $345 million. As you can see, great ARR expansion over time with those customers post-adoption. With that, I'm going to wrap up all of our comments from earlier today from our team. I would encourage you all now to take a quick break to grab lunch, which is outside. We'll continue on Q&A immediately after. Please feel free to grab some lunch, bring it back in, and we'll continue. Thank you.