NICE Ltd. (NICE) Earnings Call Transcript & Summary

So hello, everyone, and welcome to our Investor Day here at Interactions 2024. My name is Marty Cohen, pretty much know most of you, Head of Investor Relations at NICE. With me today is my IR colleague, Omri Arens. Omri raise your hand, over there. Also sitting in our front row is David Kostman, our Chairman, who will be here for the session. So I hope you enjoyed the general session. Let me now just take you briefly through our agenda and then we can begin. So for this session, we hope presentations from different members of our senior management team and as well as one of our customers we have today, which is great. And then we'll end with a Q&A session with senior management. We'll hear from Barak Eilam, CEO. As you all know, David Gustafson who is our General Manager of CX AI; Mike Fox from Henry Schein. And of course, Beth Gaspich, our CFO. Barak will provide a general overview on our strategy. David will talk about NICE, CX AI, and Mike will talk about how he's using NICE CX AI to improve the customer experience. And then Beth will discuss our financials. Just please hold all your questions to the end. Again, we'll have the Q&A session when all the presentations are done. So after the presentation, we'll take a quick break. We have lunch outside these doors. And then we'll have the Q&A session over lunch. And after lunch, we've arranged for you a private tour of the Innovation Hall where you'll see demos of several of our solutions, mostly our newer solutions. And this will end our Investor Day here. But for those of you who are staying, we have our happy hour at 5:15, and then we also have our customer appreciation party at 7:00. So let me just put up the safe harbor slide, just also, mostly all the numbers in this presentation, probably except for free cash flow, are non-GAAP. And now I'll invite Barak up to the front of the room.

Okay. Hi, everyone. A bit of a change from the big room over there to this small stage, but it's great to see all of you here, and I want to thank you all for a well-attended Investor Day and joining us yesterday, the reception. I've seen some of you and also, of course, this morning. I'm going to go in my presentation predominantly into the world of CX. I'm going to mention a few things about the other 2 businesses that we have. But we're going to have another follow-up session since this event is focus on CX, but we'll have an Investor Day in New York in our offices where we can discuss also Actimize and our criminal justice business in more depth and length. Few words about the event things that happened through the day. You probably have seen some of it. So I'll start with the event, you've seen it this morning, we have 2500-plus attendees, a record attended session for us. It's also the mix of the odds we have there is very interesting. We have 150 sessions. Most of them presented by customers, similarly to what you've seen on main stage earlier this morning from Hunter Douglas and Sony. We have sponsors and, of course, see how many companies are represented here from Fortune 100 all the way down to SMBs customers. This morning and yesterday, we made some few significant announcements, which I wanted to stop on for a second. Obviously, CXone Mpower, a big one. You've seen kind of a sneak pick to what it is, and I'm sure we'll have questions later on. But to take a step back, last year at interactions on the stage, I announced Copilot, Autopilot and Actions and really 12 months later, the adoption -- as I said, the adoption rate is staggering. And I believe we'll see the same thing on even more with CXone Mpower. Something I didn't mention on the main stage. It was too much to cover, but we also launched this morning 1CX, an all-in-one UCaaS offering. It's something we have launched softly in the last few months. We saw some great acceptance from customers. We already have customers on that offering. And we believe there is an opportunity for us in certain areas of the market to offer the UCaaS together with our CCaaS. And we believe, I think I was asking the last earning call, I think the UCaaS market is completely commoditized. And there is an opportunity for us just to bundle it in. And we are offering it at a price level that is disruptive $5 per channel or $5 per user. And we already got, since we launched it more officially, dozens of requests. And I think it will make some good noise and positive vibe for us in this market. The last one, which we announced yesterday is that we got awarded with our largest ever -- it says international, actually, APAC deal in -- the largest one in our history in terms of CXone. It's an 8-digit ACV deal, very large 10-digit ACV deal with a significant commitment and a very large displacement of long-standing players that were providing a legacy solution for many years to this very large customer. So this is just kind of some of the news. And obviously, Beth will talk about, we also announced yesterday our largest ever buyback program on top of the existing one, bringing the 2 together to roughly $800 million of buyback in motion. I'll try not to repeat on messages you heard in the main stage, but we do have people on the line. And I think you've heard me loud and clear with our customers cementing this notion of giving the perspective on cloudification, digitalization and AI-ization in a different way, calling it a grand refactoring for cloudification, grand convergence for digitalization and grand fusion is what AI brings to the market in terms of what -- I believe it is doing to the enterprise software market as a whole. But I think that the beauty for NICE is that we are in the center of a new era for enterprise software. All of those forces are really reshaping our market, and we have invested heavily, as you're going to see in a second, to make sure that we constantly bring NICE into the center of the big technological waves, and we're very fortunate to be at the center of those as we speak. I don't remember if it was the last earnings call or the one before, I was trying to explain what is the thing that we see right now in our business that is driving our success. And it is our platform or platforms as you'll see in a second, that is driving our success in fueling the demand because our platform are designed through those lenses, if you would like, of refractoring, convergence and fusion. And if I have to think about currently, what is that we see, thanks to the strength and the superiority of the CXone platform, is those 4 elements over here. First, it is allowing us to have a better and higher cloud win rate. I think we see more and more enterprises, especially large enterprise becoming more sophisticated, more knowledgeable and educated about -- it's not just about moving to the cloud, they are looking for the long term. They don't just looking to move to the cloud, but rather to adopt a platform. So one thing the platform is helping us is to have a higher win rate when it comes to shift to the cloud. The second on the right, the top right over here is trailblazing digital convergence. And Beth is going to statistics about what we see in the business. But a bigger and bigger part of our business is no longer just voice, but rather a full convergence into digital, and you've seen it earlier this morning, from Sony, from Hunter Douglas and you'll hear from other customers in the last couple of quarters or more than the last couple of quarters, almost all the deals that we're having looking at this together and we find ourselves converging these 2 separate [ subcategories ] of the market that used to be completely siloed. The third one is that this whole notion of AI, and I'm going to talk, of course, about AI later on. But more and more customers understand that in order to bring AI into CX and you've seen a demonstration of these elements earlier this morning, you really need a platform in order to do it right. It's just about the algorithm. It's not just about the tool or the application. How do you bring together knowledge, processes and data in a way that the AI will work in high accuracy in the most efficient way. It is the reason why customers choose us as a platform and not just as the AI tool. And last but not least, the deals that we are winning and you can see it in our gross margin today and into the future because we have built a platform in a certain architecture, we have a great economy of scale, and we believe that we have the best industry economics. And because of that, it's not just about our economics, but also allowing us to win larger and bigger deals because we can do things that some of our competitors cannot do because of the architecture that they have or the economy of scale that they have. So I said that I'm going to focus predominantly or actually almost just in CX, but in the spirit of looking at NICE holistically, that would be my only slide where I am going to cover the other businesses those who are either less familiar with the other 2 businesses or actually to give you more of an updated view of what's going on over there. So there are many ways to describe those businesses, I'll try to do it through data and less of hand-waving. And I will say that we operate in 3 -- with 3 distinct platforms. There is some sharing of technology and know-how, but they are built in a similar way to serve or to cater to very specialized markets. One of them, of course, the largest one is customer experience. Then there is the financial crime and compliance. And the last is the criminal justice that you may remember as a public safety business, but you'll understand a second, why it has evolved from just public safety to a full criminal justice platform. So if I dive into the customer experience and again, there are many ways to describe it, I think one of the things to understand the magnitude of what we're doing with our platform is what you see over here. [ 61 ] today manages 10 billion interactions per year, and this number continued to grow in a very significant rate. It is important that this unit continues to go because some other insight I'll give you as we think into the future. We analyze 2 trillion words per month. Two trillion words per month are being digested into AI engine, making it smarter and better. This is an amazing statistics because AI it's a lot about owning the data and having the data and that's an amazing asset that we have. And we have the industry R&D investment when it comes to CX. When you look at our competitors, either they are not -- just focusing on that business or because of their financial strength and others and the situation with their debt, they need to cut more and more into R&D, and we're starting to feel it. So maybe in the short term, they have some benefits. But in the long term, there is a question about their ability to continue and catch up with the market. So that's customer experience and again, more about this business in the rest of my presentation. When it comes to our financial compliance business, some of you know the brand name is Actimize, of course. I'll remind you that we are sitting at extremely strategic intersections of the financial services industry. And as a result of that monitoring 5 billion financial transactions daily. Five billion transactions are going through our system, and in real time, either added to our capacity and ability to provide value or in many cases, we are the ones that are deciding in a matter of tens of milliseconds whether that particular transaction is legit or not for money laundering purposes, for fraud and so for trading and for some other capabilities. Overall, we protect daily about $6 trillion of assets. And if you look at the third one, top 10 of the global banks are our customers. And we didn't have enough room for bullets here, but I'll tell you that also, if you look on the top 100 banks globally, 90% of them are our customers. And if -- the list goes on and on, and it goes today way beyond banking. Anyone that is moving money, you'll start to see -- we're starting to see names that are more in the retail side and new emerging companies that would like to ride out of the gate, be adequate with different regulations and money laundering concerns and they adopt, of course, our platform. This business, as you know, and Beth, I think will cover that, historically, it was on-premises extremely loyal customers. It's rarely the case that we lose an Actimize customer, manage a cloud transition an amazing journey. And today, a healthy chunk of this business is already in the cloud, growing nicely, extremely profitable. We're very happy with that and usually a customer that sign up in Actimize, sign in advance for 5 years, and the retention rates are staggering above anything that you've seen in the enterprise software industry. Last but not least is the Criminal Justice business. And again, for those of you who are less familiar with how we got to this business for years since I remember myself at NICE, we were the provider to 911 centers when it comes to their needs to have a system of record. So if you live in the United States and you call 911, in most cases, that call is being recorded by our solutions for more than 30 years. But several years ago, we realized that, that asset -- we have some very significant assets. We have a great brand. We have great data over there, and we have some great relationship with adjacencies to policing. So we invested to build a platform that we call Evidencentral as we realize that, that market is very much behind when it comes to modernization and digitalization. In fact, today, in most cases, if someone commit a crime, I'm sure it will be shocking or not, those evidence are kept in a box, physical box, including papers, CDs of the camera, et cetera, the detective from the police taking it into the DA office. The DA office actually make copies of that. It puts it in a warehouse, it being moved to court and to the defense, all the way to the corrections system. In 99% of the DA's offices around the United States up until recently, this was the case. We have built a system that automate and digitize this entire thing. And today, we have north of [ 13 ] million cases stored on our system, and we charge by the case, not 1 time. But every time a case is on our system, we charge on it annually. And those cases stays forever some time. Overall, the potential is that there are 17,000 police departments in the U.S. and 4,000 state attorney offices. There is no central purchase decision. Every one of those DA's offices sign on those completely separately. Even in New York, and just recently, we won all the 5 borrowers of New York. It was an effort to go to DA office by DA office. So they'll all have the same one. And today, we are the provider of that solution for New York as well as for many other DAs out there, and there is huge potential for that business. So that covers those 3 businesses. I wanted to make sure everyone is familiar with all the different activities and the potential that we have in all of these markets. This is not a history lesson, but I just wanted to make sure you understand that platforms are not born overnight. It's not that you can just start up tomorrow morning or decide that you want to become a platform. It's a decade long, if not more effort that is built both organically and through the right acquisitions. I believe you are familiar with our history. We started as the WEM leader of the market. It was a great leadership, but operating, if you would like, in a relatively small pond. We then decided to extend our leadership to analytics with the acquisition of Nexidia and that acquisition. Obviously, a pivotal moment was our decision before the market started to elevate immediately is to acquire in contact and invest heavily from that point, not just to take the solution, but to build a platform CXone natively built in the cloud from all the assets that NICE had and inContact had, rewriting everything from scratch with the domain expertise and building CXone. We didn't stop them there. We, of course, realize that there is an opportunity, as I said, to converge into digital, and we have made a few tactical acquisitions in order to bring the know-how into NICE, but invest heavily also internally. And today, as you've seen on stage, we are a true omnichannel platform, finding ourself displacing not just the legacy competitors in the world of contact center, but in many cases, the digital providers that are out there and at least those that are public, I believe that the decline that you see -- we are helping to the decline that you see in their revenue. And last but not least, AI is not new for us. It's a natural evolution from all the data assets that we have and of course, for analytics, and it's moving extremely fast in a positive way, evolving our business. And as you can see, we launched last year multiple solution. Today, something we believe is extremely significant. But if you take all the investments we've done since 2015, we estimate that in CXone today, we have north of 20,000 many years invested in platform just to understand the magnitude of what does it take to create such a platform. So let's talk about the TAM. And the potential moving forward. Today, we estimate that the relevant TAM, and I know that there are a lot of numbers out there. But the [ real time ], as we speak about 2023 of the core customer experience, the customer service market is roughly $8 billion. And the reason why we believe the next 5 years are extremely exciting is what you see over here. First, it's a market that is still nascent in its cloud adoption. I know it's shocking, but it is the case. Even enterprises that said already that they adopted cloud in many cases, it's only at 5% or 10% of their service operation. So we're going to see, we believe, an accelerated move from 20% to 80% cloud penetration. Second is that we're experiencing an exponential growth in the number of interactions that are going through our system, whether assisted interactions or non-assisted interactions that are going through our platform. It's relevant because we believe we can monetize on that. We are already seeing the monetization. And we think there is a great incremental monetization opportunity. And the last one, as I said on the main stage, still 90% of this market spend is with labor. Those 15 million agents, that's the lion's share of where people spend -- organization spend their money when it comes to customer service. We believe for the first time in a more significant way, there is an opportunity with AI to really tap into this expense. And Beth is going to show you some, I believe, great examples because we heard that you want to see that about real-life examples of what happened when we see users are being displaced by our AI. And you'll see that the fact that we are monetizing on those interactions, although there is a decline in users the ARR grow in a very significant way. So that's what we believe are the motions that will take this TAM to become [ 22 ] in 5 years from now. The second one and the market is in a financial crime and compliance. There are numerous drivers to the growth of the relevant TAM in this market, both the market as well as what we are doing in our role in this market. This exponential growth in transaction is always there and we continue to monetize on that. Diversifying beyond the core, it's more about the customers. As I hinted already, we find us more and more discussing interacting and signing deals with customers that none of us will consider either a bank or a classic financial services. And the third one is that we are starting to expand now that we have from a cloud platform, we're starting to expand of the role and the definition of what we do in this market, from just monitoring transactions for money laundering or for fraud or for trading surveillance, we find ourselves occupied more and more as the provider of full KYC, onboarding or CDD or vendor due diligence. And that allows us to expand from kind of what we're doing what we call customer life cycle risk management. The third one, I'm not going to repeat too much. It's a market that is really at the beginning. And we see already that the potential over there is tremendous. We think that there is, for us, a compound effect on lending those customers because the minute they adopt us, the cases are there, and it's almost impossible for them to decide to delete them and the beauty or not of the U.S. markets that the -- those forces are extremely fragmented. So those of you who are from the U.K., we have customers in the U.K., you have 4 general police forces in the U.K. and you cover the entire market, in terms of centralizing buying decisions, equivalent to the 17,000 over here in the U.S. and 4,000 state DA's offices. And as I said, each and every one of them buying system separately, which is -- which we see as an upside and not a downside necessarily. So if you bring all of that together, you can see that we believe that our current $11 billion TAM can almost triple in 5 years, and we don't have the TAM issue as a company. It's all about executing on our vision, strategy and plans. So how do we win? You see it over here. I'm not going to go line by line. But when it comes to think about those 3 main pillars of cloud, digital and AI, we think that this explains exactly how are we winning each and every 1 of them. We are not -- we don't always win, but more so than not when we win is -- in many times because of those capabilities. And I think you heard from the 2 customers on stage, we're going to hear from 1 customer over here. And you can see that customers today enterprises are going through a very rigid process of evaluation, not just buying from the slides. And I think that the example that we've seen, for example, from Hunter Douglas and the process they went through, it's not a rare thing to see, and we're very happy to come up at the top in each and every one of those evaluations. Well, it's not just about new customers, it's about the existing customers that we have and of course, about the competitive landscape. It is an exciting market. I've been in this market, and I am in this market for about 25 years. And I must say that the first 15 were pretty boring because you would tell people on the customer service space, and they don't know what you mean. The past 10 years, obviously, it's a growing market. And there is huge potential in this market. There is no such thing as being in the market with great potential without many wannabes. So there are different type of wannabes. I would say that these days, less so of the small start-ups because of the cost of capital and the appetite to invest in significantly new start-ups because the barrier of entry here is high. There are some companies that I think that they can easily step into this market and potentially commoditize it. I'll tell you that there is nothing simple about customer service. I know it because I'm running business for many years. And our customers, they know it -- it's not something -- it's not a cookie cutter. It's not a project base either. But when you come to an organization and you go and connect all of the systems and the complexity of the challenges in customer service, create a very high barrier of entry for both mid- and high or large enterprises. We have a very large customer base, and we believe that the 5 bullets that you see over here will defined and describe what we call our modes of differentiation. First and foremost is the breadth and depth of portfolio. And if you would like to define more customers and more CIOs, understanding that this -- buying a point solution versus if you'd like, taking a full portfolio, they like it. There is a new breed, younger generation of CIOs that are not willing to become a system integration factory. The second one is widely adopted platform. We have thousands of using CXone Every 3 months, they have new version. Every few weeks, they have new capabilities and they're widely adopting it. When I see what happened since we launched those capabilities of Copilot, Autopilot and Action and how fast they were adopted both by new customers and by existing, I've never seen anything similar to that in the past and it's not just about the demand. It's about how easy it is to toggle on those capabilities as soon as you're a CXone customer. One small example of -- I think David is going to talk about it, auto summary. It's an AI capability. We launched it in October, if I'm not -- sorry November of 2023. So Q4 last year between Q4 and Q1, dozens over dozens of customers, both new, but also existing ones that added it to their portfolio from NICE and turn it on overnight. And of course, we are charging incremental revenue on that. Our brand is very strong in our market. We believe it contributes to our moat. These things that I said about -- one may ask yourself, why those 3 markets. They are exciting markets, but they're also very specialized. You walk in the corridors of NICE and some of you have worked at the corridor of NICE, you don't meet just developers. You meet people that are really experts in those markets. If you talk to our sellers, they are not just generic wine and dine enterprise account executive. They really have the domain expertise of our markets. And last but not least, something we are realizing more and more is the data and knowledge assets that we have. We have not just the data and knowledge assets about -- but you also have the way to organize them, federate them and bring in -- bring all of them into CXone. And it's not just about how critical and the longevity of this data. It's also how you again, bring it together and derive from this data for the purpose of AI. I didn't talk about our go-to-market, so I'd say only a few words about our go-to-market. Beside our product leadership. I believe that for NICE, the go-to-market is a very significant asset. Obviously, we have a global presence, most of our business is in the Americas. But as you've seen just from this PR, we are growing very nicely and expanding into the international markets. We operate in multiple verticals. And I think it also gives us an opportunity, but also a great difference to our business. And you've seen it through the different cycles of [ COVIDs ] and the financial crisis in 2008. If 1 vertical is a bit weak, immediately, others catch up. We have amazing customers, I've been in the enterprise software industry for years. We have 85% of the Fortune 100. But we have learned a lot from our journey also to cater to the smallest mom-and-pop shops and coming up to not just thousands but tens of thousands of customers. And we play not just directly for our customer. We have a vast ecosystem and a very diversified ecosystem, as you can see, different type of players that work with us and benefit from that. In fact, 70% of our deals are either through partners or referred by partners or impacted by partners. Our market leadership goes just beyond what we are saying. It's also what others are saying about us. There are multiple of course, reports out there, and we intent ended up on the top, and it's not just about in 1 report, it's about in multiple markets, categories and the move that we are doing by the way, to converge industries. What happened is that some of those analysts end up also converging those categories, following our moves. We have a great leadership team. As you can see over here, this is what we call the executive leadership team, my direct reports, but I'll tell you in a second, and you're going to be David. We have dozens of leaders reporting to these individuals and a very strong and a very stable leadership team in the company. I want to finish my presentation on my part is also giving you a view into the further out into the future. I truly believe, and we have, as a team, built newer strategic plans for NICE and always executed on that. I believe from where we stand today, we have a line of sight and a path to bring NICE to some I call [ 5br40 ], which is getting nice into a $5 billion revenue at a Rule of 40 Company. And the reason that I believe that we can do that beyond the great markets we operate in that provide the relevant size in order to grow to that level are the 4 vectors that we are planning to execute on in the next several years, and we are already executing on them. The first one is doubling down on platformization. The term platform without getting into all the details, can go wider and wider and there are multiple benefits how you can monetize and build on your platform. And there are many things that we are already doing and planning to do further in order to double down on our platform. The second, I've mentioned is tapping into the labor TAM with AI. It is a market with a lot of workforce and there is a real desire to monetize or to move this from people to technology, and we believe that we can be the major benefactor of such a move. The third one is about our architecture that has great potential to drive our unit economics and our profitability. You see the -- you saw the gross margin that you have. Beth is going to talk about it later on. We think there is great potential over there as we continue to grow to these levels. And last but not least, it's about monetizing or incrementally monetizing on the exponentially growing number of interactions. We already have today and you'll see example of customers that as soon as we add AI, on top of the users base charge are paying us for every time AI is assisting an interaction or completely taking over that interaction. So this is a summary of my presentation. I won't read through all the bullets, but I believe NICE has a tremendous strength, great leadership, great differentiation and of course, great future success. I'm going to hand it over to David in a second, but I will introduce him. He's going to introduce himself, but I'm going to say a few words about David. David is, by himself, but also is a great example of NICE's great muscle of being able to acquire smartly. We have done 20 acquisitions in the last 10 years, small and big. And if I think about the leadership team that we have, 1/3 of my skip level are coming from acquisitions and the same true in many other places in the company. And David came to us through the Mattersight acquisition. He's been with Mattersight for many years. And when was that in [ 26 ] years. And like many others who came through acquisition in the first couple of years, they continued to run Mattersight, but then took a much larger and bigger role and their example of many like David. And we have from all of those acquisitions, every time we wanted to keep a team and in most cases, we wanted to keep a team, they stayed not just for a year or 2. They stayed for the long run in the company and continue to build their career at the company, not just within the company domain, they came into NICE. So with no further ado, I'll hand it over to David.

Thank you, Barak. I appreciate the introduction. I'm excited to be here today to talk to you about our AI Obviously, you've heard a lot about our AI over the last many years. What's exciting about our AI is why we're able to make sure that our customers can realize the full potential of AI in CX. And our strategy and our approach to AI is what allows them to do that. I'm going to talk about myself real quick on the slide and then dive back into AI. So as Barak mentioned, I came over just about 6 years ago. I see Pat taking a picture Pat, how are you doing? Pat covered Mattersight prior to the acquisition. Currently, at NICE, I manage our CX AI business, which encompasses our analytics products, our VOC products, but also our AI applications. And more importantly, our AI models and our Enlighten AI models, which I'll talk about more in this presentation. AI is not new to me. It's not too NICE either. I do have 52 patents in analytics and AI, some of those dating back to 2010. So AI has been around for a while. It just wasn't called AI in the same way that it's called AI today. And frankly, if you talk to customers about AI 5 or 6 years ago in the contact center space, it scared them and we had to position it in a different way, more about the value versus the branding and the marketing about AI. We were an early adopter of NVIDIA GPUs. Everybody knows who NVIDIA is now. A lot of people knew who NVIDIA was 13 years ago, the Mattersight Chairman of the Board and our largest investor, was also the first investor in NVIDIA. From a VC perspective, he is still on the board of NVIDIA. We used NVIDIA GPUs for large language models and AI applications in CX over 13 years ago. So we've been doing this for quite a long time. I've been doing this for quite a long time. We had the first predictive AI models. So it's now about generative AI. We had the first predictive AI models almost that long ago, even longer ago. That predicted post contact NPS scores, CSAT and churn. So we were able to take outcomes of interactions with all the structured data and interaction and have an AI model, figure out and predict the outcomes a very, very long time ago. And I'm currently responsible for our teams that lead research and are building all of our Enlighten models. So this is where Barak ended. I think it's an important place for us to continue the conversation about AI. AI isn't just about an LLM or using some other off-the-shelf LLM or building an AI. At the end of the day, we is valuable because of a number of things. The most important thing that makes it valuable is about the data, so if you're out using ChatGPT, as many people have the reason, it's so impressive is because of all of the data that has come from the Internet and all the data that it has to build that AI. That's what makes the AI valuable is the data. At the end of the day, these things that Barak talked about are what makes our data strategy and thus our AI strategy so impressive and so valuable in our space. We have a huge platform that spans agent to digital interactions. We have built AI applications in our Enlighten applications. This was launched 5 years ago. We've been doing this for a very long time in terms of Enlighten, we have a huge customer base across every vertical and every domain with billions of label data assets. So data is important. But as I mentioned in the NPS example, if you don't know what the data means, you can't build AI on top of it as well. So if you know that this conversation ended in a really good NPS score or a really good customer outcome and you are able to label things across that interaction, it helps train the AI and make a more powerful AI. And as Barak mentioned, and as many of you leading the market in terms of our revenue and profitability, which allows us to invest in making sure that we have a platform with data that allows us to build and leverage the best AI in the industry. And so what does that really mean? So I'm going to be a little bit repetitive here. You're going to hear me say data a lot, even though it's about AI. But talking about data and what data means and why data is so valuable in AI. So we have input data from over 40 applications. And we don't just have input data from over 40 applications. We have this for a very long period of time. Some of these for many years. And as we've acquired companies and built them into the platform that comes with data across different applications and different domains. So when you think about all of this data sitting on a native CXone platform across this time frame in these applications. I'll get to why this is so valued talk about our AI and why our AI is leading in the space. But you can't just have the data, right? You also have to have the AI that sits on top of that data. Now we do use LLMs. We experiment with every LLM out there, we've experimented with it, whether we use it off the shelf or use it in conjunction with our data. But we also build our own AI applications and AI models, and that is our Enlighten brand, which covers Enlighten applications, but also the underlying models that sit on top or underneath our application. So we have this massive data set that we've talked about -- largest label data set as well in the domain of CX across every vertical that exists in CX with all these different outcomes, and we're able to create these Enlighten AI models to understand, predict and guide. We'll talk about what it does throughout every step of a journey in CX because the data has also been measured across every step of the journey in CX and link together. So I'm going to get to it a little bit when we talk about data, driving AI. It's important for a couple of reasons. Data is really important to figure out how you build the AI. Data is also important that when you have AI, you know what it should do in the moment. And it has the awareness in the current state of what has occurred and what is occurring, so the models you can build can guide and assist and drive a decision in that moment. So data is important to build things in AI, data is also important to figure out what to do in that moment with the awareness of what has occurred and what is occurring right now. And that gets to Mpower, which we launched today. This is a bit more detail around -- you think about the concept of Mpower, but also to really articulately understand our AI and why it's so valuable. And I'm going to show you some real-world examples in terms of when AI doesn't work in a CX environment because you don't have the right level of data and knowledge. So we have our native platform with all of this data, and that data goes across this entire customer journey. So a journey can start proactively where a company is reaching out to a customer. That customer journey can then have self-service where a customer has engaged with the company on the website through a self-service channel and there's an interaction -- a digital interaction happening. It could then move to Autopilot or a bot, where a bot is interacting with the consumer, helping them solve their problem. It can go to augmentation where it's a human and an agent interacting, but there is AI and software and a Copilot interacting with that agent to help them throughout that interaction. And then the interaction can end. And at the end of the interaction, there is massive amounts of data where a business needs to figure out how to analyze what happened and to act upon the analytics and the data that happens at the end of that interaction. So Mpower is looking at this native suite with massive amounts of data with Enlighten models built on top of all the data that goes across all of these interactions so that you can figure out at a single point in the interaction in time right here, what is the AI supposed to do? And what an AI is supposed to do is not just about what's happening right now and it's not built on data, all the times that's happened right now. It's important to understand that the AI is figuring out what to do right now based off what happens previously. And for the 100 million other times, the customers have gone through this journey to get to hear what has happened previously? And how do you build AI to have that level of awareness and that level of memory to be able to assist in that moment to have the best interaction possible for a consumer. So I'm going to give you some common industry gaps of when this fails and why this doesn't work. In terms of executing on a CX AI strategy. So the first is going to be a do-it-yourself example, where we have a leading financial services company that wasn't even looking at the entire experience I talked about. They were just looking at automation. And how do I have a do-it-yourself bot and automation. They spend a year trying to put everything together, resulted in a very poor customer experience, and I'll about that in a minute. And then we have another CCaaS provider that someone used, where it was a national pharmacy retailer, they tried CCaaS but it wasn't a native application stack, right? You integrated vendors that they need to solve that entire platform gap. That data sits in different spots. They had to plug in other solutions, and it still resulted in a very poor customer experience. And I'll talk about that example in a minute. This is the intended customer journey, right? I kind of talked about on the Mpower piece, but a customer could have a proactive interaction. They could be out searching for something. They could be on a website where they're -- we're guiding them through the interaction. They might watch video. They might look for knowledge. There could be a virtual agent, a human agent. In that journey, there needs to be a consistent awareness and memory that follows throughout that journey for the AI to guide it. But that doesn't always happen. It doesn't happen when you try to do it without a fully cloud-native platform, so a platform where all the data sits in 1 place and the AI has the awareness to follow throughout that entire journey. So what you have here is you have a customer that was trying to solve automation and what happens before automation is self-service. And what happens after automation if it fails is an agent has to get engaged. So we're trying to solve this problem here. And you can see some of the solutions stack that they have on the bottom, they have an LLM. They have speech, they have a CRM. They have chat. They have knowledge articles. They have all of those things, but they're in different silos, and they're in different data structures. And when they try to solve this problem, they have the CRM, and they have chat in some area here, but they're in different data sources. And so what happens is when they go to self-service, they weren't plugged into the knowledge and the self-service fails. When the self-service fails and they go to a bot, because it's not in the same data structure, the bot doesn't have any context of what happens in self-service. And so when the AI tries to assist in this interaction because it doesn't have the knowledge here to help it in this process. And only that the models that were used here weren't built on any of the data across the entire stack. And then when that fails and they go to an agent, you have the same problem because they are in these separate silos, that data structure that I showed that's a consistent data structure. It's not the same data structure. And the AI is not executing on the entire set of data and doesn't have that context. Different examples, same story, looking at a CCaaS provider. So they had a CCaaS provider. This is a national pharmacy retailer. But when you get to a large enterprise level, there aren't CCaaS providers out there that have all the applications that we have let alone that they have those applications they can operate at the enterprise level. And so what happens is you have to have partners of that CCaaS provider that are then providing other solutions like speech analytics, not up here, but WFM, they have bots that are third-party bots that get plugged in. And so you have the same issue as you built it yourself, where the data structures are separate. The AI is not built across the entire memory experience of the entire journey. And when the AI looks to execute, it doesn't have any of the data of what happened previously to know how to execute in that moment from an AI perspective. So going back, that's why our approach is so powerful. It's because we have -- again, Barak said this, too, but it -- another click down. We have this platform that we have built with all of those applications, and all of that data sits in 1 place from all of those interactions across all those applications across the entire journey, we have built our AI on top of that data, having that awareness of the entire experience from the beginning to the end. And in whatever moment, the customer is needing to be assisted from a company. Our AI is able to provide the best level of assistance because of that data structures of that memory. So in summary, CX AI realized, how do we make sure that our cutters are realizing value from the -- to the full potential of what AI can do. Winners in this race will have the data from every interaction in 1 place, and they'll have brand-specific data applications that are built on top of that data structure. And you've seen that with Mpower, right? So Mpower has advanced AI memory-based awareness through every step of the CX journey, a complete solution to drive AI optimized outcomes, all cloud native, and there isn't anybody in the market that has a platform like this. And if you want to build AI in this way, it would take years to put a data structure in place that crosses all of these applications to have all of that data in 1 place. And if it -- you built it, if you took years to build that or even if you built it yourself, you're lacking historical data, you are starting from scratch to have all of that data in 1 place to then have enough data across verticals, across brands, across domains to be able to then build AI on that data structure to then use it going forward. Thank you for the time. Next, you're going to hear from Mike, who will talk about how he's used our applications at Henry Schein One. Thank you.

Not part of the deck, but that was the first time I've seen that presentation that's us today, right? What you saw with the different sources of knowledge and data down at the bottom. That's -- I was over there chuckling to myself, David know me at our group. We'll go through who Henry Schein One is, the challenges that affected our customers, our goals and achievements, the strategy and the tactical areas that guided us to success and some of the best practices that we learned from this experience and then what we're going to do next. So I've been in the software industry for over 20 years. In fact, I used to work for -- we'll see how many heads nod, Wasatch Advisors, Wasatch Funds, I see a couple of smiles, yes. Moxy, Axys, Advent software, right? And so experience there. And in the work management world, I've been in the dental industry, software dental industry for the last 13 years with Henry Schein One. Henry Schein One is a privately held entity by Henry Schein, Inc. Henry Schein One is the software solution provider to dental practices. So these statistics are specific to Henry Schein One, not Henry Schein Inc. 100,000 practices worldwide. We have a big business -- we've got -- we are the largest dental technology company in the world. I'm not going to go through all the recognitions at the bottom. But we've been around since 1985. Dentrix Dental System was the first platform -- Windows platform for the practice management solution area in the dental world. And then we were acquired -- Dentrix Dental System was acquired in 1997 by Henry Schein, Inc. So we've been around for a little while. Henry Schein, Inc. themselves have been around for 90 years. This is our very simple vision for Henry Schein One. We empowered dentists to focus on patient care and ensure practice success. So we're very focused if we can do both those, right? Doctor goes to school to be dentist, not a small business owner, but they go together, right? So we help them run a successful practice. We help them take care of their patients if they're successful, we're successful. So who are we? We consider ourselves the care catalyst inside these practices. Even though we're a technology company, we consider ourselves a care catalyst, which means we bring them technology that unlocks better outcomes for their patients, right, and their practice. So for example, I don't know if you noticed the AI Award slide or icon down here but that AI was for our digital imaging software, right? The AI has the ability to pull out things in those images that human eye can't. So from a preventative care standpoint, that's extremely beneficial to the patient and very profitable the practice. Even though, again, we're a technology company, we still consider ourselves key to providing care to our customers' patients. These are our solutions worldwide. And believe it or not, that's not all of them. And I put this slide up here not to say, look, how big we are. We actually don't like this slide, so I'm showing it anyway. The reason why we don't like it because it's complex to our customers, right? Who are you? What are you? You're just a conglomerate? Or what are you -- hence, the name in '19 -- in 2018, rebranded as Henry Schein One because that's our aspiration to get to a platform that provides what feels like to the customer 1 experience, right? So with all of these products, they all sit into what we call product families, right? That's how many products we have. We have to have product families for them, right? And inside each of these product families, we have multiple products. Again, this slide is to say we have a complex business because behind all these products, you have the line support and services and get the customer to the right place ideally the first time, right? So I'm not going to go in details on this slide. I just know it's complex, right? And what adds the complexity, a customer could be using a practice management solution like Dentrix. And if they're a DSO, a digital service organization where they own multiple practices up to 1,000, they could have multiple practice management solutions across those locations. And they can have one of our patient experience platforms, 1 or maybe 2 or maybe 3, right? You get the complexity. So for routing, our customer helping our customers, getting them through this complex business as we work to consolidate and create that 1 Henry Schein experience. It requires technology, right? So our problem -- a big problem that persisted for as long as I've been at the company, was we have a manual process that sat in front of a good portion of that technology. We had a CSR team, a customer service representative sitting in front of that team to do 2 things that was identify the customer and whether they're paying their customer support plan and get them to where they needed to go, right? And from that, came a lot of problems. One in particular -- there are several, but 1 in particular, it's very costly to the business. We were on a legacy Avaya system with Calabrio for our workforce management and quality management. But the CSRs during peak volume, right, they can only take so many calls. We have seasonality. There's events that occurred. We actually had 1 a major industry event occurred just recent Change Healthcare cyber attack. If you're in the dental industry, you'll know what that -- or the prescription industry, you will know about that. They do 80% of the claims -- electronic claims for the dental -- did sadly. And so of course, volume, right? Customers are calling, my claims, my claims are getting rejected. But the biggest problem here, withstanding the 30 minute was a big issue during events was the number of mistransfers. So you have these CSRs, right? And you saw in that last slide, the breadth and the depth of knowledge, they have to have to be able to route the customer to the right place the first time. So naturally, these people who are desperately trying to learn where customers need to go. They're not doing a very good job. You can hardly blame them because of the depth and breadth of all of our solutions. So we have 7% in this transfer rate, which is about 7,500 calls a month, but the worst part about it was the 2.5x it took of transfers to get them on to where they needed to be, right? And so all of a sudden, you have pressing 19,000 calls sometimes more, sometimes less, depending on the volume of the time, just creating inflation inside of our call volume, voting around our system. That's costly for us, right, or almost anybody. So what happens, so we set some goals and said, there's got a way that we can create a better experience for our customers and eliminate the noise. Our goal is to reduce, by 50%, the CSRs. Why 50%? Why do we grab that number? Because we happen to know that 50% of our calls are how-tos, and there's got to be some technology out there that can route that for us rather than having to talk to somebody. Reduced mistransferred rate, right, we wanted to get back down -- we wanted to get it down to 3% to 5%, being on Avaya. They just wasn't working, eliminate mistransfers feedback. As sales was telling us, our customers tell us, it was one of our top, always, again, since I've been there, to get rid of that. In 2023, we hit all those goals. We nailed it, and I'll tell you how. We had a $2 million savings through that process with that 50% reduction in volume. We -- our contract with CXone was $1.6 million with a $400,000 cost savings, which is -- we're very excited about. We actually had a goal just to be neutral, right? We don't care about making or saving here. We just want to improve the experience, that savings enough. But we actually got something out of it, which was awesome. So to launch Autopilot is what we implemented to do this routing. Right out the door, we had 26% adoption. My mind was blown because I have never seen anything like that in the industry yet. And I'll tell you how and why that came to be 55%. This slide deck was made in the very end of April as we were prepping for this. We just hit, for a few days, 58%, so we're celebrating that. The solutions that we used, right, clearly, the platform, right, you'll hear more about that from me here in a minute. ACD, IVR, performance management, all of this stuff was gravy to us, getting off of Avaya and getting a system that gives us visibility. That was a no-brainer. This was the deal maker, right? This was -- this solidified it for us. We gave XO, we used Enlighten XO, we put in 0.5 million calls recorded calls into Enlighten XO. It punched out and working with the working with our NICE CXone partners, we begin to pull out intents and utterances, right? What the customers are uttering and saying on the call and mapping those to intents. And when you know those 2 things, you can map it to the skilled resource on your team, right? So what happens in Autopilot, customer calls, right, the experience of taking that, the human experience they have is now replaced with Autopilot saying, "Can I get your customer ID," which we train our customers to know. "Can I take your customer I'd," data-dips into Salesforce, right? Checks if they're paying. If so, then the question is, what can I do. "What can I do for you? And using those intents and all those utterances that are now mapped, "I am having problems with running month end." Okay, it'll data-dip, go in and look and see what practice management solution they're on, because we have that in Salesforce, right, and then we have that mapped the skilled rep, and go straight to that skilled rep. And funny story on that real fast, we had a doctor call complaining about the phone system. So my boss thought, send it to me, we'd talk to the doctor. So I talked to the doctor, he was unhappy about a wait time that happened somewhere else in the business. And I asked him about the phone number he was calling. He was actually calling some other phone number that, anyway, IVRs. So I gave them the correct phone number, invited him to use Autopilot. "When you prompt it just use it." So he did. I never heard back from him. But we did go look up the next call he made, and he did use it, and it was an interesting experience because it went from having to talk to the CSR, wait, talk to the CSR, get routed again, and then rehearsed the same routine with the technician. It went like this, right, he -- through the process I just talked to you, the updated process, but when he got to the technician, the technician asked, rightfully so, what's your customer ID. And he said, let me guess, you're just going to transfer me again. And he goes, "No, I'm here to help you. What can I do for you, sir?" And there was complete silence. That's the good silent we want on a phone, right? It was a complete shock that was -- that was super rewarding. We passed that around the office and had a good chuckle. But one more thing that was really, really quite fun here. We had someone coming with colorful language, right, some people don't like. They just don't. And they came in and just started blasting Autopilot with a lot of colorful language. And I had forgotten months earlier, we addressed this in the design was, we want to say something productive. We want Autopilot to say something productive. So we had intents and utterances mapped to this occasion and we had it say, "It appears that this conversation is taken to turn for the worse. Could you please tell me what you need and we'll route you." And you could see the tone completely changed, because it was such an intelligent response, almost instant respect. And he said, "I just want to talk to somebody." And then it routed into someone who could help him. So that, again, flew around the office. That was a lot of fun. But moving on, Okay. So what happened? Here are the numbers, January, very tall. Just know January is our peak season. Volume is always high every January, okay? May -- or excuse me, April circled, April previous year. This is our call volume to our CSRs. You can see, I don't need to tell you, right, it dropped. This is the date we went live with CXone and Autopilot at the same time. So we spent all this time prepping for that go-live and building those utterances and testing. And you can see it. I don't need to say much about it. But I do want to point out here, but I can't read my month, January. January, right? So this is the percentage of that routing. This is Autopilot routing 26% out the door. People have asked, how did you get this? How -- the experience was improved. The experience rework -- customers are smart. They really are. Sometimes they're not. But in general, they are. But they know when their experience gets better by using technology, right? And so it was that noticeable to them that they get to where they need to get to be, to the right person the first time faster than -- way faster than before. So this is the percent of calls that were successfully routed by Autopilot. And again, we hit 58% just a few days ago. Our current -- this was the big one. Our current mistransfer rate, 0.8%, 0.8%. How did we do that? I'll tell you on a slide here in a minute. This is how much inflation we had in our system, floating around, mistransfered calls just going everywhere and people going -- it was ridiculous. And I'll tell you what happened in the business in the next slide. But 170 flows later. We actually have more utterances come to find out than that. We're up in the 1,800 now because we continuously build out those other instances. We have -- we did it with 4 individuals. They were assigned, not dedicated. So we have the CSR supervisor, who knows, right, person with knowledge. We had a manager -- the technicians who knew what they were supposed to receive and what skill. We had our engineer, who we repurposed from our Avaya. He was a CMS guy and he knew everything. It was technical, transferable skill sets, boom, right? And with them meeting 1.5 to 3 hours a week and meeting with the CXone, the NICE CXone team, we developed all these flows, developed the utterances, did all the mapping, and we continue on our daily improvements in those utterances, in auto summary, and we continue to improve it. So our best practices, what did we learn? We learn when you take out a lot of short mistransfered calls, a lot, by, like, thousands, right, and you reduced the volume of quickly answered calls, your ASA and AHT, they're just going to go up. The lesson here is you probably should let leadership -- made sure that leadership understand that while we do this endeavor, it's going to appear that we're doing worse, but we're actually doing better. And I'm still having to remind them that today whenever we do a MVR. Drive the partnership, driving the partnership. No one in the history of implementing software, and I've been doing it for 20 years, both as a customer and doing it with customers who used to manage the onboarding team for Henry Schein One before I was doing this, and there is nobody that comes out of an implementation who goes, "That was the best experience in my life," and "Give me an NPS score because I'm going to give it a 10. I want to recommend it to everybody." No one ever does that. But what they do, do is after that process, they go, "Man, that -- our partners were there," right? "They responded perfectly to imperfect situations," and it's just going to happen. And that's what happened with us. NICE CXone was there. When things did not go perfectly, there was a healthy response and a healthy relationship. And a health relationship requires reciprocation, feedback. How did we get -- how did that -- we continue that trajectory up, what you saw 26% to 58% is within CXone, when you end a call, you can disposition the call. It means you can put an attribute against it. We have 3: call completed, elevate and the third one was mistransferred. So we could get, as the calls were coming in, look at the mistransfers. If it was human related, then we would go and coach. If it was related to Autopilot, we'd go and improve the utterances based off what we saw. And that discipline is what got us to where we needed to be. Negotiate the sales for outcomes -- to be outcomes based. The partnership was that 50% mark, right, so whatever amount of hours it takes, hit that mark. And again, that goes back to driving a partnership and reciprocation, make us successful and we'll make you successful. So what's next? When we did our RFP 2 years ago and we selected NICE CXone, we wanted a platform that we could leverage for the future, optimize and leverage. So it was more -- if you remember the 3-part slide, it was more than just getting the CXone solution with the IVR management. It was, we want to deflect, we want to put CXone chat inside our own platform so they can reach us where they're at doing business, and then begin to deflect within that channel and also put in the product the ability to search knowledge and get generative responses back within our platform, utilizing the generative capabilities. And so in the end, deflect as much as we can, utilizing the technology that's available to us in the platform that we purchased and NICE CXone was nicely aligned with that. We actually go live chat in-product next Wednesday. AutoSummary, we go live at the end of the month. I played with it last Thursday and Friday with our senior management team. It will be great. That's all I got for you.

So thank you, Mike, for sharing your experience with us and showing how our customers are deploying with AI and winning in practice. So as you've heard Barak present earlier today, NICE is at the center of a new era in enterprise software with 3 technological fundamental driving forces shaping the operating markets and the markets that we operate in. That includes cloudification, digitalization and AI-ization. And at NICE, we have always been strategic. We have always been at the forefront of the competition, and we are driving the evolution of the markets where we operate. We have been building cloud platforms across all 3 segments that Barak talked about earlier today that are feature-rich and can scale to organizations of any size. So that foresight that we have in the shaping of our markets plus the pure execution we've delivered on our strategy to build best-in-class cloud platforms are consistently evident in our financial results. We pride ourselves, at NICE, in the strength of our financial results. And you can see that here demonstrated by the strength of the growth we have, both, in total revenue as well as in our profitability and cash flows. This doesn't happen by accident, and it begins with our clear strategy where that's followed, at NICE, by creating clear priorities and very targeted KPIs that we provide to all our teams at NICE. This creates a very focused approach and it has repeatedly paid off for us. So you can see that we have double-digit growth in all of our key financial metrics over the last 5 years with 11% CAGR in our revenue, 13% and our operating income and 11% in our free cash flow. Our operating margin has increased about 210 basis points over the last 5 years. And as we exited last year, 2023, is really -- in the last 3 consecutive quarters, we have delivered a 30% plus operating margin, which was a prior operating margin target that we had shared with the community. And what's also important to see is that our profitability and the health of our business generally flows all the way into our free cash flows. And then while we had a CAGR of 11% over the last 5 years, you'll see that in the last year, we reached almost $500 million of free cash flow. And so it's a significant step up in terms of our growth rate for cash flow generation. So our success is coming from those very focused and intentional approach that we have at NICE, setting our KPIs, and that also adds to the strength of our go-to-market engine at NICE. So we have a go-to-market engine, which is coming from both our broad partner distribution network. Barak talked about that earlier as well. So in 2023, if we look at our new bookings, about 63% of our new bookings were coming either through a referral or a specific reseller from -- as part of our partner in distribution network. And the remaining 37% was coming from our direct sales force. And of course, our direct sales force has been operating at the high end, working with large enterprises for decades. So you see that the effectiveness we've had in our go-to-market and how that's playing out with our 27% growth and a CAGR over the last 5 years. And here what we're going to with you for the first time is that you're seeing in growth is not only coming from the Americas region, but also a combination of our EMEA and APAC region that's represented here by the international cloud breakdown. So we've delivered great growth, really, across all regions. And I think one of the things that's really important to highlight at NICE is that we have gone through a transition from an on-premise company with less than 5% cloud revenue several years ago, to almost 2/3 of our revenue coming from the cloud last year. And we've done all of that with the sustained high top line revenue growth as well as ongoing increase in profitability. So today, our cloud growth is coming from 3 main factors. And this is a breakdown of looking at, again, our new cloud ACV bookings that we delivered in 2023. So you'll see that almost 70% of our business is coming from our existing customer base. About 1/4 of that business is coming from new logos that we've added. And the remainder or the smaller portion is conversions of our existing customer base that are using our on-prem solutions and then they're subsequently shifting over to use our cloud platforms. When we first look at the existing customer base here, the 69%, what's important to understand about customers that are existing customers and as they continue to grow with us, it's really happening in 1 of 2 key ways. The first is that they're adding more and more agents using the platform. And the second, of course, is the expansion of all of the different solutions that they're using that are part of the embedded platform. And of course, more and more frequently, you'll see that, that is part of digital and AI offerings as well. So we have a rich portfolio, and the new customers representing about 1/4 of our business, that has also been quite consistent. On -- in general, we add about 200 new logos each and every quarter. We added nearly 1,000 new logos in the last year in 2023. And finally, with the existing customers that are migrating over to our cloud platform, first, it's important to recall that these are some of the largest enterprises in the world. These -- this is the customer base that we were working with for many, many years on-prem. And we know that as those customers convert and move over to our cloud platforms, that we typically see about a 2 to 3x ARR uplift on a like-for-like basis and upwards to even 9 and 10x uplift for those customers, others taking more of the suite of solutions off of our cloud platforms. So we have a long-standing large and loyal customer base. And here, we're showing you specifically a breakdown of retention, what we've seen over the last 12 months, specifically for our CXone customers. So we're calling out CXone as CXone is largest growth driver for NICE today. And we have an internal saying at NICE that if you land a beachhead, you will have a customer for life. And I think that's evidenced here, both in the growth -- or the gross retention rate we've seen over the last 12 months of our customer base which is at 95%, and that's highly consistent over time that we see anywhere in the mid- to high 90s with our customer retention. We've also seen that effective land-and-expand strategy continue to play out as our customers buy more and more of our suite of solutions and add more agents. And that's reflected in our 113% net revenue retention rate that we've experienced over the last 12 months with those same CXone customers. So we have strong success, executing against our land-and-expand strategy, and you'll see more of that in some of the slides coming up. So today, this will give you a better breakdown. Again, we're sticking right now with the CXone portfolio and our existing customers. You'll see that 84% of our customers are using, today, 3 or more solutions of the CXone platform. And a little over half are using 4 or more products. But what's really interesting and what's really noteworthy is if you look at the right-hand side here, what the average ARR looks like as our customers continue to adopt more of our solutions. So you can see that for those customers that are adding 6, 7 and up to even 12x or 12 of different solutions off our suite of our cloud platform, it has an enormous uplift in ARR. And so the opportunity is immense. If we look at -- most of our customers have around 4 solutions and the uplift that we can achieve just with cross-selling alone is immense. So as we think about the growth drivers, both in the last several months, but also looking ahead into the future, the growth driver is coming really from 3 key areas: The first is further penetration into the large enterprise. The second would be further penetration into the international arena. And finally, the third, of course, is the ongoing selling of our digital and AI solutions. So I'm going to start by talking about our large enterprise customers. And this represents all of our cloud customers today at NICE that are $1 million or greater in ARR. And so you'll see that as we exited the first quarter of this year, we now have 365 $1 million plus ARR customers. So those customers make up more than half of our cloud revenue at NICE and actually, it's right at 53%. So as you look to the right-hand side, the estimate today is that only about 24% of organizations have adopted a CCaaS offering. And so there's an enormous runway, both in the large enterprise, where we have decades of expertise as well as into the international arena and regions as well, which is still highly underpenetrated. And of course, Barak mentioned earlier that yesterday, we announced that we've been awarded our largest CXone 8-digit ACV deal in our international region, specifically in APAC, which is -- has a total contract value of greater than $100 million. So we're really just starting down that journey of furthering our international business, and it has a great runway ahead of it. But of course, the biggest tailwind and growth driver that we have, looking ahead, is our digital and AI solutions. So during the first quarter of this year, we exited with more than $150 million of ARR, which is associated with the sales of our digital and AI solutions. And what you'll see on the right-hand side is that today, those customers represent about 8% of our total cloud revenue. And when we look on the 24%, this is the percent of the bookings that we had in the first quarter of this year that came from our digital and AI solutions. So it's about 3x relative to the revenue contribution we have today, which means it is going to continue to add incremental revenue for us. And as Barak, as well as David talked about earlier, for AI and digital, we are now increasingly using a consumption-based model, which means that as these interactions continue to expand, we will continue to see that ARR increase with any sales intervention. This is a little bit more granularity to really see immensity of the opportunity ahead of us for our AI and digital solutions. We have a customer today that has adopted some of our digital and AI solutions. We see that the average ARR for those customers is 4 to 5x higher than the customers that have not yet adopted those solutions. And likewise, when we look at their ARPU in a very similar way that we see the average ARPU of those customers is also greater than 50% higher than those customers who haven't yet adopted those solutions. And you can see that today, of our existing CXone customer base, we've now sold into 17% of that base. So first, there is just an incredible opportunity available for us as we look at penetrating this additional 83%. And it's important to note that this is just the very early days of the 17%. So of course, we're going to continue to sell more and more of the suite of digital and AI solutions into those customers and we'll monetize on increasing volume of interactions that I talked about earlier. So last year at Investor Day, I talked about how our pricing model has been evolving. And that, while historically, pricing for our software was based on the number of agents or the users using the platform. But that has evolved and is now, as we have introduced more digital and AI solutions, which are agentless, we have shifted to consumption-based pricing. And so that pricing has been based on either an interaction or a session. And so that is being reflected more and more in our model. What I'm about to share with you is a scenario, because I'm often asked, "What is going to happen to your growth rate as your customers effectively adopt your AI solutions and potentially drive efficiencies as we've seen that are happening in all of our customers, and are able to actually reduce the number of agents in the contact center." So we have created a scenario that shows a customer or an organization that today has 1,000 agents in the contact center. So if you look at the right-hand side, they're spending about $50 million annually on their labor cost. And what that looks like on the NICE side of the equation is that they have what would be a typical adoption starting off with workforce engagement, adding routing over time and then really getting to adding the full complete suite of our CXone offering. And so you'll see this nice ongoing increase in their ARR to about $3 million. So now we want to share if the customer, post the adoption of our Enlighten AI offerings, is able to effectively reduce their agents to 750 agents, what does that look like for both NICE and our customers. And what you're going to see is, clearly, it's a win-win for both. So in this scenario, you'll see that for the customer, they're able to take their contact center and reduce it by 250 agents, reducing their labor cost by 25%, now at $37.5 million annually and inclusive of the cost of our software, they have a combined 20% annual savings. So it's an enormous, very attractive ROI for our customer. And what you see for NICE is that we have a 50% uplift from the $3 million ARR we have today to the $4.5 million ARR after the adoption. And there are 2 things that we should highlight here. I think, first of all, is that -- I highlighted that this is an example of a customer that's really taken on a complete suite of solutions. But we know that the average is more around customers that have adopted about 4 solutions off the platform. So that means the opportunity and the uplift in the ARR is even greater than the 50% than what you see here. So now that I've shared kind of the win-win scenario of what this looks like for us as organizations are able to effectively drive further efficiencies from the adoption of our software. I'm going to shift to a couple of recent customer examples. So in the first example, this is a long-standing NICE customer. They have been with us for more than 20 years. And for many, many years, were using our workforce engagement solutions on-premise. They have more than 15,000 agents globally, and over the last few years, they have adopted our routing on CXone. They also adopted some of our digital capabilities. They, in turn, also moved off of the on-premise workforce engagement, moving over to CXone as part of their overall migration. And then more recently, they've added our AI solutions as part of the overall platform adoption. And you can see that it has an incredible ARR, which has increased almost 2x, and this is just within a 3-year window. And this is very early days in terms of the AI adoption. And as you saw from the example that Mike shared earlier, what we see with customers are that in early days, that they see kind of the lowest level of return. And as they continue to iterate on the adoption of AI, they received higher and higher ROI. And likewise, for NICE, we receive a higher and higher ARR as a result of the monetization of the consumption-based model. So now I want to share with you also an example of a new logo example. So this is an example of a multinational financial services company. And this organization was using one of our competitors' workforce management solutions. They had some challenges around compliance and decided to go to market to replace it. So in the practice or the process of this happening, they selected NICE for work management. They displaced 3 disparate vendors they we're using: 1 for workforce management, that was a competitor that we displaced, another for analytics and a third for routing. And they consolidated all of this business onto our CXone platform. But what happened is during the sales process, our sales team also shared with them the Enlighten AI suite and all of the capabilities we have there. And so as a result of that sales cycle, they ended up increasing the size of the deal by 2.5x by adding AI digital capabilities, including AutoSummary and CXone Expert into the deal. So this had a great uplift. And as I've mentioned in other examples of the AI, this is very early days. So as the customer looks into the future, we have the ability to first continue to cross-sell more the portfolio, including more of the AI and digital capabilities and to continue to monetize on the interactions. So now that we've seen the growth we're experiencing in our customer base and how it has also driven the growth in our cloud revenue overall, I want to share with you how that's really trickling down directly into the overall health of our business at NICE. So increasing profitability and really managing a healthy business has always been a mainstay of how we operate at NICE. In the last several years, we've seen a lot of organizations bleeding cash, laying off taking on a lot of high interest rate debt but that is -- none of those practices have read at NICE because we've always taken a balanced approach. And it's really evident in how we manage our business focusing, not only on continuous top-line growth, but also great strength and expansion of our profitability and cash flows. We have increased and expanded our cloud gross margin by almost 900 basis points over the past 5 years. We have double-digit growth in both our EBITDA as well as our EPS and our ongoing returning capital to our shareholders. So this has -- this profitable picture has allowed us to continue to innovate far more than the competition and really investing back and creating CXone in the strength of our offerings. What the -- what else I wanted to share with you today is that, not only are we being innovative as it pertains to our AI and digital solution for our customers. But more and more, we're increasingly also using Gen AI tools internally at NICE. So we have multiple different areas across NICE, along with multiple different use cases that are now deploying various Gen AI tools to write code faster, to have more testing capabilities and generally just to drive further efficiency into our internal operations. And so last year, I had shared that we are on a path over the next few years to achieve 35% operating margin. And initiatives like this give us great confidence in our ability to achieve that margin as we've shared last year. So our financial success overall at NICE is evident from the profitability that you've seen as well as the free cash flow generation. And that has allowed us to have a terrific capital allocation program, which has always been focused, both on innovation, regardless of whether it's organic or through acquisitions. And we have an extremely strong muscle, and you heard from David earlier today as part of the success we've seen in acquisitions, on really streamlining the integration of the acquisitions that we do. And of course, the more recent one is the $415 million represents the acquisition that we just more recently did of LiveVox last year. Likewise, we are also using our balance sheet to further increase our share buybacks. So we almost doubled the amount of buybacks that we had between '22 and 2023. And as Barak shared, we publicly announced, just yesterday, we have further committed to the continuation of our share buyback program with a new $500 million share buyback plan. So what we're sharing here is that we have just under $200 million left that is remaining on the existing $300 million program. We had originally expected to utilize that by the end of this year. We are accelerating that, expect to use it even prior to the end of the year and we'll immediately initiate the new $500 million program. So when I look at our capital allocation priorities, they haven't changed. They continue to be both M&A and share buybacks. And it's important to note we remain committed to share buyback programs and that we expect them to continue beyond even the newer program that just recently introduced. So before I leave you, I have 2 more slides. First, I just want to reaffirm the guidance that we provided coming out of last quarter. So our expectations for total revenue, cloud revenue growth and EPS growth are unchanged as you can see that we're sharing here in terms of our expectations. But what is new is that we're sharing a bit more granularity into the core of our operations. So with our operating margin, I shared that we have been just around 30% in the last few quarters. We expect that to continue to expand on our track to a higher and higher operating margin. So we expect to have an operating margin this year between 30.5% to 31%. Similarly, our EBITDA margin, if you recall the slide where I showed you, we've consistently been around 30% or higher in our EBITDA margin, we expect to set a record this year, going above the 32% into greater than -- equal to or greater than 33% in terms of achievement of an EBITDA margin. And then finally, I shared with you that we had an 11% CAGR over the last 5 years of our free cash flow. But we have greatly stepped up that cash flow generation in the last 2 years. In last year as well as what we expect in the current year. So currently in this year, we expect to generate at least a minimum of $600 million of free cash flow, representing a growth of 26% or greater. So some really great achievements that we're looking forward to delivering on throughout the course of this year. So in summary, at NICE, we have a proven track record of sustained execution and reaffirming the balanced growth that I've talked about, both top line and growth and profitability. It is the way that we lead the company and expect to do so into the future. So we have consistent execution on delivering that profitability that I talked about and the opportunities and the TAM that Barak shared with you are enormous. We're in very early days in terms of penetration into the large enterprise, into the international arena. And of course, the digital and AI, as you've seen, has just more enormous opportunity, both due to the richness of the suite of solutions that we offer that are really just unmatched in any of our markets. And then finally, of course, all of this is surrounded by the strength of our balance sheet, where we have $1.5 billion of cash and investments on our balance sheet that allow us to return capital to our shareholders as we've announced in that recent share buyback program. So we have always been strategic visionaries in our space. And we're really excited with this next stage of these technological forces that Barak talked around cloudification, digitalization AI-ization. And we're really confident that we are extremely well positioned to continue to deliver the strong execution that you've seen across all of our financial metrics. So that completes my presentation. With that, I'm going to hand it back to Marty. Marty is just going to do a quick update or a reminder of the agenda, and then, I think, we'll break for lunch. So Marty, I'll hand it back to you. Thank you.

So let me just take a 15-minute break. I think there are lunches coming out now outside and we'll come back after 15 minutes, and we'll do a [ Q&A ].