Okay, let's get started. Thanks for joining us today. As a brief introduction, I'm Ryan MacWilliams, small and mid-cap software analyst here at Barclays. Excited to have this AI in the contact center fireside with the Five9 team today. I really appreciate their help in setting up this event. We have a full agenda, so we're gonna dive right in. With me today is CEO and Chairman, Mike Burkland, CFO, Barry Zwarenstein, President and Chief Revenue Officer, Dan Burkland, along with some special guests and Five9 attendees. From an agenda perspective, over the next hour, after starting with a safe harbor statement, we'll start with questions to Mike and some brief remarks on AI in the contact center. Following that, there'll be a 15-minute AI deep dive with Five9's product leaders, then a 20-minute customer Q&A, and then a 20-minute Q&A with the Five9 team. Now, we do have a packed agenda with multiple participants, so we'll be passing the ball around a lot here. Please feel free to send questions in to ryan.macwilliams@barclays.com, and we'll try to get those in if possible. Let's kick things off with the safe harbor from Barry. Barry, you're on mute. Thank you, Ryan. Hello, everybody. Before we start, I'd like to remind you that certain statements made during today's discussion are not historical facts, including those regarding future events, trends, expectations, projections, and beliefs that may affect our industry or our company. Product developments, AI and automation, and potential growth drivers are all forward-looking statements. Such statements or predictions should not be unduly relied upon by investors. Actual events or results may differ materially. Five9 takes no obligation to update such information in such statements. Please refer to our most recent Form 10-K and 10-Q under the caption Risk Factors and elsewhere with our filings with the SEC. Thanks, Ryan. Yeah, of course. It's just so great to have so many members of the Five9 team and multiple different customers, and we're gonna be passing the ball a lot around today. For investors on the line, you know, if we have some, like, technical difficulties or we're doing some screen sharing, you know, just bear with us, but we got a lot packed into the schedule. Mike, you know, I've been dying to ask you. We've seen a lot of changes to the contact center over the years with the introduction of IVR to the widespread adoption of internet and email. You know, how do you view the evolution of the contact center with large language models and AI? Why do you think Five9 is in a great position to help clients utilize this new technology? Yeah. Thanks, Ryan, and thanks, everyone, for joining us today. You know, today we have an opportunity to have a meaningful and important conversation about the realities of AI and automation, and how recent developments such as LLM and generative AI will likely impact our market and our company. Over the next hour or so, we're gonna cover a lot of material, and we expect that you'll walk away after that hour with the following two conclusions. Number one, generative AI is the next wave of opportunity for Five9. It broadens our TAM. Number two, platforms will win over point solutions and engines alone. The platform is the control point, and Five9 is the platform. Let me take each of those two, one at a time for a second here. The first, generative AI, is the next wave of opportunity for Five9, broadening our TAM. Five9 has been riding the wave of AI and automation for the past several years, and as we are positioned very well to continue to push this industry forward. Not only is the AI revolution a tailwind to our technology and innovation, but it's a tailwind for our business model. We provide software for our enterprise clients to manage all of their customer interactions, from 100% human interactions on one end of the spectrum, to full self-service automated on the other end of the spectrum, and a blend in between. Let me remind you that as AI drives efficiency and productivity gains in the form of a mix shift toward more automation over time, that leads directly to an increase in revenue per customer and a TAM expansion for Five9. Let's take the second conclusion here. Point solutions and new technology engines can accelerate and enhance a platform, but they cannot replace it. By now, most of you have heard, we've made this analogy between the airplane and the jet engine. Think of Five9 as the airplane and LLMs as the jet engine. To fly across the country, you need the entire plane and all of its systems. LLMs are like the jet engine. They enable our airplane to fly faster and further, but they are not a replacement for the airplane. Because Five9 is an end-to-end platform, where all customer interactions flow through our platform, we act as the control point, which is quite different from a point solution, such as a standalone IVA or a chatbot. Jonathan and Callan are gonna discuss this in much more detail. With that, let me turn it over to Jonathan Rosenberg, our CTO and head of AI. Hey, everybody. Thank you for spending your time with me today. I'm super excited to share with you my absolute most favorite topic, which is to talk about AI. What I really wanna do is cover that in three parts. First, talk about our AI strategy. Second, talk about Five9 as a complete CX platform. For that, I'll get help from Callan, our Head of Product Management. Lastly, I'll come back to me, and I'll talk about how that platform forms a competitive moat for us. Let's dive right in and talk about Five9's AI strategy. To do that, you need to have some context here. Over the last 12 years, which is not a very long time, we have seen a huge change in the landscape for AI in the enterprise. It started with what we call the pre-deep learning era. In this era, which ended just about in 2011, it was pretty challenging to build AI applications for the enterprise. You needed to go and build custom AI models and gather tons of training data and build and tune those models, and it was expensive and time-consuming. In this era, there was a certain set of vendors, Nuance, for example, is one of them, that really were amongst the leaders in this space. We saw a change. Deep learning arrived around 2011, and this introduced the era of, like, Alexa and Siri tools that dramatically arrived in the consumer landscape and also made their way into enterprise. In this era, it became much easier and cheaper to do speech recognition and language speech generation, but still required customization for the use cases for each business, one at a time, and that did involve model training and data collection. It was easier, it was a little less expensive, but it was still required customization. In this era, we had a different set of vendors who did really well. Google and Amazon and IBM, for example, were some of the leaders in this era. Once again, we've entered another new era, this time the era of the large language model, which just started last year. In this era, things have completely changed. Now, instead of about collecting lots and lots of training data and labeling data in order to build unique solutions, there's a general purpose solution which can be made fit to purpose through what's called prompt engineering. I'll talk more about that in a moment. In this era, we have new vendors, so OpenAI, of course, is on everyone's mind. Lots of people are rushing to compete, like Google and others, and we'll see who the leaders are in this space. The most important thing to observe is that there's One thing has been constant here, which is change. Every few years, we've seen new technologies, new vendors, new leaders, each of which have unique capabilities. That led to our AI strategy, which was instead of building these engines in-house, we take them from whomever is best in the market at that point in time and integrate them to build a complete product, right? In fact, we will use multiple vendors, often even for the same customer. We have customers who deploy our IVA, and they'll use one vendor for text-to-speech and a different vendor for speech recognition. This agility has allowed us to ride the cost curves down and the quality and technical innovations as these mega scale vendors deliver amazing technologies. We then built our entire architecture to be prepared to swap them out as tech evolves. This was a vision and an architectural design principle for both Five9 as well as Inference, which is the IVA vendor that we bought some years ago. That has allowed us to be agile and quickly move and adapt to these different technologies. That allowed us to execute the third pillar of our strategy, was to focus on building business outcomes, right? At the end of the day, no enterprise wants speech recognition or natural language processing. What they want is to have a contact center that can receive customer inquiries and handle them quickly and efficiently, leaving satisfied customers at the lowest cost possible. That's quite a different thing, and it requires building a whole product, of which the language models, and other technologies are just a component. In fact, building that whole product solution, a great way to think of it is analogy that Mike just shared with you, which is that of an airplane. If you want to go across country, you're not gonna just strap yourself to on top of a jet engine and take off. I don't recommend that. You have to get in an airplane. The airplane provides all the systems that are necessary, the navigation, the wings, in addition to the human pilots and systems for loading the passengers on the plane and off the plane. All of this is necessary to ultimately deliver what the customer wants, which is to get from point A to point B. The jet engine is the enabler of that. This becomes ever even more crucial in this new generation of technology around large language models. In this generation of technology, the previous things you did, which was building lots of data and labeling it and building trained models, that's gone now, and it's replaced with a new technique for making these technologies fit for purpose known as prompt engineering. This is probably something you've heard of by now. What happens in prompt engineering is you customize it by taking different sources of information and putting them into the prompt. For example, if you wanted to build a system that was capable of answering customer inquiries about insurance on a website, you have to build an overall product, a system that took the customer data, that took curated knowledge, that took the customer inquiry, and integrated into the website, and used that to build a prompt, which was then fed into the large language model, that in the end, produces the result that goes back on the website to the customer. Again, with this new generation of technology, vendors who in the past had staked their futures on lots of labeled data, are gonna find themselves really without an edge in this next generation, because now it's not about that anymore. It's about integrations and connectivity with lots of systems that are required to build the prompts that are the core discipline in the usage of large language models. What I'd like to do now with that background on our strategy is talk about Five9's complete CX platform, and to do that, I'm gonna hand it off to my colleague, Callan Schebella, EVP of Product Management at Five9, also the former CEO of IVA Pioneer Inference. Callan, why don't you take this away? Thank you, Jonathan, I will just share my screen on this end. Just let me know if that is coming up. Excellent! Let's start by talking about what we mean by a complete CX platform. Basically, the platform has three major functions. I'm just gonna route here. First, we need to provide an aggregation point for customer contact, that is a means to basically take voice, chat, SMS, email, and more, and basically land them on our platform. Secondly, we then route those interactions to agents or to automations and bring in core engine technologies, as Jonathan mentioned, as required to allow us to attach meaning to the interactions that are taking place. Third, we combine our understanding of those interactions with our integrations into data sources and systems to create a real-world outcome for the customer, and the business are often referred to as fulfillment. This might sound pretty simple on the surface, but if we dive one level lower and bring up all the layers that comprise the Five9 CX platform, you'll see that there are a lot. The way that I'm going to help illustrate this is to start with the simplest possible use case, and that is just a customer calling into a business and having their call handled by a live agent powered by Five9 software. If we look at this diagram here, the customer starts on the left-hand side by making a phone call. You can actually just follow along with the highlighted elements on the screen there. The phone call is then handled by our global voice network in both a secure and a compliant manner, and then lands on our core ACD, which is the switch or essentially the routing brain behind Five9. In this case, we then pass that to a live agent who is logged into the Five9 Agent Desktop, and that Agent Desktop is integrated into the business systems that Jonathan mentioned. In this case, a CRM system and a marketing platform, as well as some sort of custom back-end integrations that are required for this particular company. Once the call completes, the call can be automatically summarized for the agent. To do this is an example of reaching out and consuming an engine. In here we consume a large language model engine to do that summarization. Finally, we post that information along with everything else we know about the call into the Five9 data lake. That allows the business owner to use that information after the call to do reporting, to do analytics, or to visualize it in an online dashboard. This is a really simple example, and in fact, for Five9, this is about as simple as it gets. Now let's look at a more typical customer scenario using the same type of flow. In this case, we're going to imagine a customer calling into a contact center to ask a question about an existing reservation that they have. You could imagine it could be a hotel, an airline, a restaurant, or really kind of any industry. Once again, we're going to start as a voice call, and we're again going to land on our global voice network and again go to the Five9 ACD. In this case, the call is answered by a virtual agent, so no human agent. It's 100% software, the virtual agent reaches out and consumes a variety of engines. Jonathan mentioned this as well. Here, for example, we need a synthetic voice so the IVA can talk. We need biometrics, so the IVA can identify the caller based on their own voice. Speech recognition engine, to convert what they're saying into some text that we can process, and then finally, an NLP or natural language processing engine to attach meaning to that text and respond appropriately. It is not uncommon at all for that to be split across, you know, four different vendors, for example. The virtual agent also draws upon information stored in the CRM and the marketing system. Imagine in this particular scenario that the virtual agent has determined that the caller is eligible for a free upgrade and wants to transfer that call to a live agent to discuss. One of the nice things about a platform is that the live agent benefits from all the information already captured by the virtual agent, and the live agent is also assisted with artificial intelligence themselves, this time from Five9 Agent Assist. The way that we do that is we use Five9 VoiceStream to stream the audio of the call to the engines attached to the platform. That allows us to suggest guidance and recommendation for the agent to use while they talk to the customer. Again, we could do this in a variety of manners. We could use a natural language processing engine or a large language model to do this guidance. Finally, again, a large language model is used to summarize the call. Often there's steps after the call. In this case, we're going to use Five9 Workflow Automation. Again, another layer, in this case, to send a confirmation SMS to the customer, as well as a thank you email. Once again, everything is written into the Five9 data lake, and then the business can query that through Five9 Reporting, Five9 Analytics, and well as web-based dashboards. They may even seek to use things like speech analytics, which allows them to look at sort of customer sentiment, using that engine there, highlighted on the right-hand side as well. As you can see, there are a lot of layers in the Five9 platform, this really demonstrates why our platform is so powerful. Everything you need all in one place, handling the most simple interactions, all the way to very complex interactions. With that, I'm going to pass back to Jonathan again. Thank you, Callan. With that, let me talk about how this forms a competitive mode. If you just stop the share, Callan. Much appreciated. Thank you, sir. All right. How does this form a competitive mode for us? The reason it really comes down to two core concepts, channel and agent ownership, form a competitive mode that favors platform plays over point solutions. Let's understand that in some detail. Let's say a point solution comes along. They've got the world's greatest chatbot or voice bot. In order to do that, to have any sort of bot, you ultimately have to plug into a channel. You have to be able to receive the voice calls, receive the chats, or the emails, or the webs integrations, and you can imagine that the voice bot or chatbot might do that themselves. Historically, actually, what's usually happened, and I'll explain why, is these things don't plug directly in. Instead, they sit on top of exactly the type of platform that Five9 has, that provides that connectivity and everything else. The reason for that, again, is all the capabilities that are inside that platform that are necessary for every voice bot, every chatbot or live agent, instead of providing that functionality one at a time for each of those, you provide it a single time as part of the platform. Again, if we go back to a specific use case, let's say we've got a call that comes in here, the first thing that happens is it arrives at our ACD, which is our routing engine. What should happen with this call? Should we send it to an agent? Should we send it to chatbot 1? Should we send it to chatbot 2? Most companies will want some flexibility here. They want to decide, "Oh, maybe this is a high-value customer, or a high-net worth customer, or a customer that, based on data and integrations, looks like they have a really bad account balance, and we want to send them right to a live agent." This kind of decision making is what our engine does, and you need that to sit in front of the voice bot or chatbot to even select whether to use it or to send the call to a live agent. Let's say the call then goes to a voice bot or chatbot. We still need much of the capability that Tom described, for example, around reporting. One of the things customers wanna know is what fraction of their interactions, whether it's chats or emails or SMSs, were able to be handled by the live agents versus which ones are able to be handled through these automations and bots. The only way to get that kind of aggregate reporting is when the voice bot and chatbot sit on top of the platform, so the platform that can provide it. We've got dashboarding. Let's say there are supervisors that are still watching the system in real-time, and they worry about things. "Oh, my gosh, there's too many people sitting in the voice bot or chatbot system, or they're all hanging up. Something's wrong. Maybe I should make some midday adjustments." That kind of real-time dashboarding is again, provided by the platform that allows for the whole system to work as a whole. Most importantly is the integration with data sources. This is the foundational part for any voice bot or chatbot. You can't do anything without access to data and APIs. Often in many of our enterprise customers, there are dozens of these integrations with all kinds of third-party systems in order for the overall contact center to work. By having the platform provide those integrations and allowing voice bots and chatbots to plug into them via our platform, the overall solution is more reliable, more secure, and more manageable for the customer. Again, this is why, historically, for many good reasons, the market has preferred the voice and chatbots to plug on top of the platform. On top of that, you have the huge complexity of building the channels. Just the channels alone is a huge amount of work. It's deceptively simple. If you think you just drop in a few lines of JavaScript, you get a web chatbot, and web chatbots are actually one of the easier ones to do, but still lots of work around customization and localization and flexibility. When you look at something like SMS, right? Which is the way a lot of us like to communicate these days, there is a ton of work required just to build SMS integration. As a vendor and a platform, you need to build up a huge inventory of numbers. You need regular numbers. You need them in different area codes and country codes. Oh, you need short codes also. To do that, you need global presence. To get global presence all over the world, you need to interconnect with providers who offer those SMS numbers to you. Once you do that, you have to comply with regulations and rules around provider registries to prevent robo-texting and malicious content, and that's a whole bunch of work and integrations. Messages don't always get delivered, so you have to worry about delivery statistics and reporting and retry systems. There's these opt-out things. You probably see, "You can type stop to discontinue," and that requires a whole pile of work in the platform to manage that ensure compliance. You need language and personalization and billing on top of all this, and that's nothing compared to voice, which is even more complicated with networks and telcos and all kinds of capabilities that I won't be able to get into. The complexity in building this is what makes the platform, and that's why voice bot, chatbot products typically plug in. Channel is number one, the second is the human. That most customers want some amount of agents in the system, whether it's more or less, depending on the capabilities of the automation, they want the flexibility to route some calls to the human agent or go to the chatbot and then transfer it to a live agent in case there's challenges. That transfer process can't be done effectively without being on top of the platform. The platform provides things like the transcript so far, or the actions taken by the user when they were conversing with the voice bot or chatbot. All that is necessary for the overall experience to work. When you put that together, in conclusion, these point solutions don't displace us, they require us. This has historically been the case. We've got many third-party chatbots and voice bots that have historically run on top of our platform because. Customers like them on top of the platform. Second, by owning the platform, it allows Five9 to offer differentiated capabilities to our own voice bots and chatbots that sit on top of the platform, and that's why it's often customer preference to choose those products from the vendor of the platform. Third, owning the platform means that we can monetize those third parties when the customer chooses them, and that's another strategy that allows us to take advantage of our platform position in the network. With that, thank you for your time. I'm gonna hand it over to Dan Burkland, President of Five9. Dan? Excellent. Thank you, Jonathan, and thank you, Ryan, and good afternoon, everyone. We thought it would be a great opportunity, rather than just hear from Five9, on our technology, to have three Five9 customers share their experience with all of you. I'm very pleased to be joined today by Joe DeLuca from Wyndham Hotels & Resorts, Ronald Benjamin from Chipotle, and Joe Friedrichsen from Blue Cross & Blue Shield of Rhode Island. Thank you, gentlemen, for joining us today. I thought we could get started. If you can enable your videos, that'd be super. I thought we could get started with some very basics, an introduction. Why don't we start in the order I just described and a quick background on you and your company and what you do there, and then we can get into how you're leveraging Five9 to help you with your customer experience. First, Joe De Luca, why don't you start us off? Quick background on yourself. Sure. Thanks, Dan. Joe DeLuca, I am the senior director for Enterprise Voice Contact Center Systems and Collaboration at Wyndham Hotels & Resorts. Been with the firm for a little bit over five years and responsible for all of the contact center technology and solutions for Wyndham. Excellent. Ronald? Yes, I'm Ronald Benjamin. I'm the Senior Director for guest and employee experience for Chipotle. Been here for a little over almost 2.5 years, formerly with Delta Air Lines, and I'm responsible for all contact centers for employees, guests, and social media for Chipotle. Excellent. Thank you, Ronald. Glad to have you here. Joe Friedrichsen, Blue Cross Blue Shield. My name is Joe Friedrichsen, worked for Blue Cross & Blue Shield of Rhode Island. Been here about seven years. I manage all the infrastructure. ... that includes, in this case, the contact center as a service, and prior to that, I was at Fidelity Investments for close to 20 years. Excellent. Why don't we take the next question in reverse order? I'll start with you, Joe Friedrichsen, Blue Cross Blue Shield. Just describe, if you could, you know, why you moved to the cloud, and in particular, why you chose Five9. We'll get into talking to each of you about how you've leveraged and how you're utilizing, our AI and automation solution. About three years ago, we decided to get out of the data center hosting business and move all of our technology into a cloud. Most of that moved into Microsoft, again, we had to focus on what are we gonna do for a contact center? We had two different technologies. Both of them were end of life. Both of them would take significant upgrades to get to a supported version with no added value. We looked at an RFP for contact center as a service. We knew we wanted to move to a SaaS model. We looked at companies like Genesys and NICE, Cisco, and Five9. We did an RFP. I led that RFP along with some of the business teams, and we decided that for us, Five9 was a perfect fit, not only for the short term, but really for the long term, based off of the technology roadmap. Okay. Joe, while I've got you, I know you've done some work with our AI and automation solutions. Maybe share that with the group on what that's done. Yeah. For your company. Yep, earlier this year, we actually started with that interactive voice agent, and we actually rolled that out. We rolled that out to our customers directly, as well as the doctors who call us up when they have claims questions. We really looked at two different real use cases. One was the authentication or authenticating people through that natural language processing that John talked about. Also looked at how do we understand their intent of calling, and then route them appropriately to either our own internal centers or to external providers for us. What we saw was, in the first three months, we actually surpassed our three-year goal of authentication rates, which was really remarkable for us to see that. Then from a containment perspective, again, like, routing calls to the appropriate areas and routing them to external third parties, definitely saw that go much above where we were targeting. Our interactive voice agents really did a great job from a self-service perspective for us. Great. Excellent. Good to hear. Over to you, Ronald. Tell us about your choice of Five9, and then how you've implemented AI and automation. You know, I had much of the same journey as Joe had. Earlier, we went through the exact same vendors because they're the best in the space. We landed on Five9 because we feel like we could grow with you. You were growing, you are a great solution, and it's tailored to what we need for what was going on. It allowed me to have multiple vendors in multiple spaces, because I have the employee experience, customer experience, and social media. All these different areas, I have multiple vendors using the same platform. It allowed me to leverage all those things and to exceed, much like Joe, the markers that I had in place for customer experience, as well as average handle time, and actually understanding what was going on in the business as well. Good. Joe DeLuca from Wyndham Hotels & Resorts, you have a rather unique model in how you're leveraging the IVAs, the virtual agents. Maybe you can take us through not only your decision to move on to Five9, but then what you're doing today and kind of what your plans are moving forward. Sure, sure. I think the decision to move to Five9 was a pretty easy one. Did go through the whole process with an RFP. All the major players, you know, Five9 checked all the boxes. You know, what was supporting our centers prior to Five9, I guess the best way to describe it was hybrid. There was some on-prem, you know, in conjunction with a data center and managed services. Lots of operational complexity, to say the least. The cost, of course, obviously, you know, that comes along with that, was pretty extreme. Five9 allowed us and afforded us the opportunity to streamline, reduce that complexity, and of course, the overall cost and made it much simpler. There's a lot more to say about that, quite honestly. Yeah. Just to speak to the IVA component, you know, one of the first things that we started to do with the IVA was directly associated with deflection and containment, right? The low-hanging fruit, we had notice had 40,000 + calls per month coming in just to reset passwords for our loyalty members. You know, between the verification and validation of credentials and the entire process, it was pretty burdensome to have all that handled by an agent. The IVA allowed us to automate that through an authentication process, right? Checked all the boxes as far as our compliance and legal departments were concerned, and then we were able to move forward and really chip away at that overall volume on the. Yeah the password reset. Yeah, and I understand what you've discovered since is handling a centralized means through an IVA to now alleviate the load that you used to route out to the many, many properties and have the front desk clerks and all that labor force have to take mundane, repeating questions. What time is room service end? Is the bar open? Is there a swimming pool? Those kinds of things. Yeah, that's and that's the next level we've taken to. We've gone from the, like, say, the low-hanging fruit with the password resets, really simple stuff to automate, to the next level, where we're taking that sentiment analysis and intent analysis. You know, the AI is delivering self-service, being able to answer calls, you know, along the lines of, you know, whether or not you're running a shuttle, what's your pet policy? You know, a lot of opportunity from that perspective, and it's really taken a significant chunk out of the non-revenue generating calls going to our centers and ensuring that, again, they can be self-serviced or routed more accordingly to the property to be handled. That was a huge win for us. Excellent. Ryan, any questions from you or the audience that you'd like to ask in the panel? Yeah, for sure. Guys, thanks so much for being here today. I just want to say I love that breakdown by Jonathan and Callan, because it just shows how complicated a contact center could be. I mean, you guys live this, but it's much more than just answering a question, right? Look, as a former contact center agent myself back in college, it does pain me to ask this question of you, which is: Given this rise in AI, you know, do you see a potential reduction in the number of agents in the future for contact center, and over what time period? Love to hear your perspective. I can jump in here. Really, at the end of the day, we don't see AI change, you know, eliminating our agents. When we look at it, we really look at it from an omnichannel perspective and what's that member's journey, right? Sometimes they're on our website first, and then they're calling us. Sometimes they don't even go to the website, and they call us. Really understanding that the AI can solve some of the basic kind of questions, but then typically, you know, our customers want to talk to a human being. The analogy I was given is really around how when the internet came out, you know, everyone was thinking, like, retail banking is dead, right? That people don't wanna go to a retail site. What we found is people wanna go to those retail sites, not for the basic stuff, but for something that's very specific to them, very unique. The... And what they found, and what we found the same thing, is our Net Promoter Scores go up as we provide those great services, both from a self-service and then easily transitioning that to a human-assisted experience. If I could just add to that, I think that it's a misconception that an AI is just gonna automatically remove jobs out of the equation. I think, quite honestly, that, you know, while there is opportunity for to be some kind of reduction, for the most part, though, it really just allows the agent, the opportunity to focus on other areas. You know, be more productive. It really optimizes the agent's time more so than replacing an agent outright. Ryan, I'll go one step further to say I think it will grow. You know, that's really being optimistic because it now allows us to focus on getting more customers through our venues. It allows us to work on the things that we read that need a human touch to really work on. In actuality, if we can increase the footprint that we have in our businesses, give a higher level of service, it actually opens the door for us to increase our market share and actually hire more people with better intel, better customer service, to really take us all to the next level. Building off what you were just saying there, Ronald, we talk about agent happiness. One of the things that every call center suffers from is the high turnover. What we see AI doing actually is helping us with that agent happiness. Giving that agent the information that they need in order to service that customer, understanding what they're calling about, what they did on the portal, a whole history, bringing that all together so that when the agent gets the call or the contact, they know what's going on, and they're not struggling for the first, you know, minute or two. That can just help them, then with some of the Agent Assist, you know, you can have AI guiding them through the conversation, which again, helps us from a training perspective, that we don't have to train our agents to be the best at everything. They have, like, a coach on the spot, helping them through the process. Really, what we see from an agent perspective is the turnover rate should start to go down because the agents are happier with the tools they have and the information they have to service the customer. You guys are making some great points, I guess. I've been thinking about how AI could impact, like, the labor spend and the cost perspective. What I'm hearing from you is, like, more the efficiency and how you can provide a better customer experience. You're almost more interested in, like, how you can drive more revenue opportunities. Is that a fair characterization about, like, how you guys are viewing the AI potential in contact center today? Yeah, 100%. Perfect. You guys all mentioned, you know, having IVA or other AI solutions with Five9. Would love to hear how you're finding the payback and justifications around what you've implemented so far and kind of the ROI that's driving at this point. I can jump in again to start us off here. When I talked about we're reaching our three-year goal from just an authentication perspective, that's a dramatic operating expense reduction for us. You know, we were forecasting that to take three years, seeing it in three months is just remarkable. We actually don't have to hire as many people as we used to. We stripped about 10% of the duration of a call, so the average handle time, by utilizing this, and this was just our first phase, which is kind of, I think, what Joe was talking about, the low-hanging fruit side of the house. Now we're going into a much more- complex phase, much more API-driven phase of helping our members understand their benefits, where they are with their benefits, and what's the next logical step for them to process a claim or anything of that nature. Much more complex, but what we've seen so far with the conversational design that has gone on to really drive that best member customer experience, we're looking forward to deploying the next phase of this later this quarter. I'm following in the footsteps of Joe DeLuca. We are moving down the pathway of using the IVA to do password resets for us. With us, we're on a path, growth path, at Chipotle. As we add restaurants, add staff, their mandatory training is every 90 days with those things. What happens is, they forget, and they call in, "Well, what's going on with this and that?" It just drives us, allow us to continue the growth trajectory without having to hire more people or spend more output with other of those who are gonna answer the phone and do those things as well, but also give us actual intel. I mean, with the everything you have there to make that experience what it should be, also a great coaching tool, it comes back to tell us where we need to put more money, training, and put our focus to really make it a better customer or employee experience. Make sure that we are not missing anything. It just helps us all the way around. I see it as an ironclad, our future, really. Making us better for the future to make sure that we are, our investment maximizes that, then we also become the best we possibly can be. Just to jump in, I'm so happy you brought that up because it's not like a contact center, set it and forget it, right? Right. These are evolving, living, breathing systems that, like, you already have new use cases and new marketing programs. It makes sense that, like, as you see more efficiency, look to see where other areas you can do more with. Guys, just as we wrap up here, love to hear, you know, just your thoughts on, like, what's coming next in the contact center. You know, how you can see this technology impact, you know, your business over the next three to five years, and if there's any use cases or anything particularly interesting that you think you can adopt to make your contact center better. I think, if I could start that off. I think what's next, undoubtedly it revolves around the use of AI. Without a doubt, you know, the solutions that provide all of those insights, the things that Ronald was talking about, that's invaluable, right? Understanding why folks are calling and being able to utilize that information to further target and focus and personalize the experience, right? I think solutions that ultimately achieve that personalization is what you're gonna start to see across the board. Of course, obviously, it ties into a lot of other aspects of, you know, different benefits that are easy to achieve, such as, you know, augmenting just the experience itself with automation and not having to rely on a human, right? You know, that's the easy stuff. Take it to that next level, like I said, the insights are really what's invaluable. I'll tag on what Joe said. The three Ps for me, too, is predictive, personalized, and proactive care. Those three AI will catapult my three-year plan into probably about a year to help me internalize those things, set systems in place, and actually go after to make our business grow more profitably, and also give us a higher level of satisfaction, not only for the employees, but also for the guests. I'll wrap this up by talking about, really from our perspective, again, long term, AI really would impact our back office more so than our agents. I think about, you know, our knowledge management, and how do we take all that knowledge that we have, and being able to share that with our members when they attach to our portal or when they're calling into our IVA. It's really that knowledge management that in every contact center I've ever worked in is problematic and takes a lot of effort to manage. Now there's the possibility that by pointing, you know, the technology at our data and then using it through APIs with Five9, that we have much better outcomes as far as quality is concerned. Again, I think we'll... As I listen to this conversation, I hear what others are doing, really, I think that the opportunities are really unlimited as far as how it can drive up Net Promoter Scores while reducing our costs, if you design it the right way. Which is also something that we really haven't talked about, but you gotta really design this for the right experience, so that you're not creating customer abrasion. Well, Joe, Ronald, and Joe, thank you so much for taking time today. I know this was invaluable for our audience to hear directly from you as customers and how you're leveraging AI and automation. I know, Ryan, that you had several questions you wanted to ask of the Five9 management team. Thank you all, and back over to you, Ryan. Thank you. Excellent. Guys, appreciate the time. Just as a transition, just following off what Joe said, yeah, I always complain about how my first two weeks in a contact center, they just gave me a binder to study student loans for two weeks, and then it's like, "All right, you can hop on the phones." It's like, there's got to be a better way to do this. Dan, you know, just because we came off the customer panel, would love to start with you. You know, just as activity begets activity in the contact center, and there's new technology, and you're probably receiving a lot of inbound questions, love to hear kind of like, what are the pain points or interests of your existing customers today around AI? What are they thinking about buying in the near term, just in terms of AI and automation? Yeah. Thanks, Ryan. You all heard some of those examples just in the last few minutes. I'll kind of break it into three categories. One is, and what you heard first, was customers are experiencing this end-of-life scenario where their products on-premises are legacy, they're older, the manufacturers have said, "We're done innovating there. We're done enhancing them. You've got to move off of them." They have very few choices. They mentioned the three main providers, including Five9, that are CCaaS providers or cloud platform providers. That's the first step is get off the legacy, move to the cloud, then it's the ability to leverage the AI and automation that's truly only available on a platform that's cloud-based. That's something we see as a potential catalyst and an accelerant to companies saying, "Aha!" It's gonna take us a year or two, in some cases, depending on the size of and scope of their company, to make that migration. They're starting to recognize, especially as companies like you just heard from, have already started in implementing these solutions, that they better hurry up because they've probably got a year or two to get to the AI point. So we see that as a potential accelerant. Excellent. Yeah, that touches on my next question, you know, either from Mike or Dan. We talked about how, like, in the past, some large contact centers would never go to the cloud, right? Like, they would just sweat their assets for years and years, it's like, what are gonna make these guys finally move? I think, you know, could AI be that catalyst? Like, could this be the thing that finally catalyzes, like, "Okay, well, we're never gonna move, but now we need these features." Maybe for Mike, you know, do you expect the rate of cloud migrations to change or maybe see interest from those customers that you thought would just stay on those assets for a while, given this change in generative AI? Yeah, Ryan, it definitely is a catalyst. As Dan said, we view it as an accelerant to the process. It's happening for many, many years, right? We've saw for the last, I'd say, you know, decade, and I think we'll see it for, you know, several more years, this mass migration off of on-premise solutions to the cloud. As we've talked about many times, this is still a market that is, you know, 20% in the cloud and 80% on-premise, so it's a massive opportunity. If you think about... We, you know, we debate about agent counts and what that's gonna do over time, but don't lose sight of the fact that this is a massive market that is going to the cloud no matter what. This is, you know, this AI revolution is just gonna accelerate, and that is gonna benefit Five9 and other players in CCaaS. Got it. Dan, you talked about, like, your pipeline and how things are going well. Would you be able to characterize, like, how AI conversations are impacting that? Like, are you seeing, like, shorter deal cycles as a part of this, or maybe more RFP activity or more testing? Like, you know, what has that made any changes in terms of, like, your near-term opportunity set? Yeah, a couple of things to unpack there. One is, you know, the fact that the doubling in the pipeline of the high-end enterprise, our strategic accounts, over the year, somewhat driven by this AI and automation revolution, but also by the fact that you mentioned earlier, why enterprises were, you know, quote, "reluctant or willing to sweat more one more year." A lot of the large enterprises needed to wait. We saw this very same thing happen with CRM, right? Until you could go prove yourself at the highest point and most complex and global organizations in the world. We demonstrated that with a couple of the large Fortune 50 accounts that you all know of at this point, with tens of thousands of agents in a very complex environment, their criteria was, we got to make sure you can scale, be reliable, protect our data, deliver all the functionality you have today, and give us an easy migration path through the tools and expertise to move off of one very. This is like, I think Mike's used the term, it's like heart surgery. You know, you're basically taking, you know, you could say heart surgery or central nervous system. We have tentacles into all the back office systems, and when you go off of the prem systems into the cloud, all those integrations need to be rebuilt. Hopefully, we can just replicate all the feature functionality that comes standard and move that over to our platform and spend our time on that new, innovative, and complex side of things. As soon as they saw that we could check all those boxes and deliver, you know, at scale with all those capabilities, and to give them the platform to then innovate on top of, that was key for the large enterprises to start on their process. We're seeing an acceleration there already. Yeah, I loved hearing that from so many larger customers, that it's like: Look, we're really excited about the opportunities today and the future improvements today, but we're really future-proofing our system here, and it's not just about this year, but the next five years. I think it's a good, you know, time to tag in Barry. I know we're still early in this AI revolution, but love to hear about how you think about the potential for AI to be monetized today, and how do you envision pricing given AI capability? Yeah, absolutely, Ryan. Thank you. Just as a reminder, for some of the audience who may not be intimately familiar with Five9, we get $200 per month just for access onto the platform that Calvin and Jonathan described, all those features and functions. With respect to AI and automation, the best illustration, of course, is the IVA example, which is, or what the two Joes and then Ryan talked about so enthusiastically. We sell those on a per-port basis, and that's $400 per port, per month. That's only one of the portfolio of eight different products that we currently have, with more to come. It only goes up from there as we embed throughout the whole-... more precisely, as our engineering department and product department embed throughout the whole solution, all the AI and automation. By the way, this has been a passion of Five9 for... We've been talking about this now for 4+ years. We're a software company. We believe that AI and automation drive efficiency and productivity gains, and the more software we sell, the more revenue we get. Our customers are also happy because they get a, you just heard, significant and tangible ROI for what we're delivering. It's early days, but as Mike pointed out, a little while ago at the beginning, we look at this concretely and confidently as a TAM expansion, as a mix shift towards automation. I appreciate that perspective. Look, I have to talk about some of my own research. We published a note today talking about some estimates around pricing and agency growth, maybe for Mike or Dan, you know, we'd love to hear your guys' perspective. You know, we keep hearing like, "Oh, what if half the agents go away? What could that mean?" It seems a little interesting given how, like, for years and years, we always talk about how contact centers kind of only expand. Love to hear how you just think about changing agent growth rates and maybe the overall agent opportunity in light of AI. Yeah, sure, Ryan. I'll start, Dan, feel free to pile on. you know, there's an ongoing debate as you stated, Ryan. It's If you look at industry analysts, they'll tell you that the agent counts are not projected to go down, even in very recent reports. If you talk to, you know, you listen to the customers we've talked to today, it's not a massive decline if there is a decline in terms of agent count that they're anticipating. Let's just, for the sake of argument, assume that there is a more significant decline. The good news for us is, remember, Five9 is a software company. We provide solutions to our enterprise customers to process interactions. Think of it as interaction capacity, and those interactions can be human to human on one end of the spectrum. They can be fully automated on the other end of the spectrum. Most of them, in my opinion, are gonna be in the middle, in this blend of somewhat assisted by AI, but probably still involving a human. We can debate whether that impact on agent count is gonna be zero, small, medium, or large. In the end of the day, we monetize any interaction, whether it's human to human, whether it's fully automated or somewhere in between. We're a software company that provides solutions. We provide the platform, which Jonathan talked about, as kind of the control point, which you have to have. You know, it's important for everybody to understand that we have products and solutions for all types of interactions, not just human to human. That interactions hub or that plane is pretty complicated, right? Like, walking through the Jonathan example, like, when people always ask me, like: "Why do contact center deployments take six to nine months?" It's like, well, it's not like they're just sitting there waiting for it to get spun out. Mike, I would love to kinda hear your perspective on just, like, what goes into a contact center deployment that requires this significant customization. Like, what backend systems you need to link into? Like, why is professional services such a moat for Five9? I mean, it is a huge moat for us. It's a huge reason why many customers choose Five9, quite frankly, is our team of experts. We've got, I think, close to 500 services people that are absolute experts in this field. Most have come from the legacy of Avaya, Cisco, Genesys in terms of their backgrounds. As Dan said, this is very much like open heart surgery. This is a major technology transformation. You talk about ERP or CRM transitions and transformations. This is in most cases, more complex than those transformations. It requires expertise, but it also requires integrations. You mentioned it, Ryan, most of our large enterprises probably have 30-40 backend systems that we integrate to. 30-40. Talk about complex and sticky and, you know, and requiring expertise. At the end of the day, we talk about this a lot, you know, Five9 really brings the power of technology, but we also bring the power of our people. That's a big reason we win in these large enterprise opportunities, is because of our expertise and our cultural, value-driven behavior in terms of customer first. We do whatever it takes to drive success for our customers, and it's about driving business outcomes, as well as obviously joyful customer experience. I love the idea that, like, the efficiency gains don't just stop there, right? They keep wanting to do more and more, and like, the more capabilities new products you come out with, the more they can add to their own platform in terms of software adoption. Count, if you don't mind, I had a question come in from an investor that I thought might be interesting. Just would love to hear your perspective, maybe perhaps on how you think the evolution of voice AI versus chat-based, you know, GPT conversations could shift over the next year or so, given the advances in technology there? Count? Sorry, is that one was directed at me? Yeah. Yeah. How will the shift take place? Well, I basically think that the way to think about it is if you think of LLM as an engine that allows a new class of interaction to be unlocked, then you're likely to see it used in those sorts of interactions. Now, it doesn't really matter whether we're talking voice interactions, chat interactions, email interactions. Basically, in all of these channels, we essentially convert to text as one of the first steps that we do, and then once you have it in text, you can apply either an NLP model or an LLM model or any other model that comes out for that matter.... I think what we've seen over the last few months is that there's certain classes of tasks that are now much more easily solved using an LLM than with traditional techniques. The big one that you'll see is summarization as a task. We already have in market, essentially a post-call summarization product that essentially is powered by LLM that does exactly that. If you look at summarizations as a task or a class of interaction, that was really hard to do with just the earlier generation of technology, NLP, and things like that. That's the way I think people should think about it, as essentially unlocking new types of interaction automation using LLM. Then we've seen this time and again, as Jonathan went through in his section of the presentation, as the new eras have rolled out, we've seen new types of interactions being automated. Ryan, if I may touch on that from a customer's viewpoint, what I'm finding is the customers wanna offer. When you talk about voice versus chat, versus email, versus chatbot, they wanna give choice to their customers. They don't wanna push them towards one or the other, 'cause, remember, at the end of the day, the customer experience and that NPS is so important to them that they wanna just give that alternative. At a convenient time, one version or one channel may be far more appealing to you than another. You know, I'm gonna use my PC and a website to do certain things when I'm here in my office, versus when I'm driving down the road or, you know, in some other capacity. You got to really giving choice and helping those customers, but not forcing them into a self-service option. We've all seen how that's been responded to. That's one from a customer standpoint. Then, as Mike mentioned, the beauty of looking at this not as a seat thing. I know we've always used seat 'cause it's an easy thing for people to understand, 'cause historically it's been agents. But think of it as we're handling all the concurrent customer interactions, and those aren't going down. As a business grows, those go up. We're looking at it from a port, each port or simultaneous concurrent transaction, and there's gonna be a whole lot of mix. Some come in and do a little bit in the IVA. We saw that from one of the customers here, that's just doing voice authentication and some intent, and then getting the calls routed to a, to a more specialized agent, and then helping them with more. The key there is we're an interaction hub or an interaction management platform, and we'll take all interactions from whatever channels, we'll handle them from each end of the spectrum and everything in between. The more automation enters the equation, the more software enters the equation, and therefore more dollars enter the equation. Excellent. I think that's a great place to wrap things up. You know, you never know what new technology is gonna pop up. Maybe next year, Mike, will be talking about like AI and VR and contact center and virtual reality, but we'll see. Mike, do you have any closing remarks there? I appreciate the time. No, I just wanna say thank you, Ryan, and thank you to everyone that joined us today. Hopefully, this was insightful for everyone. We sure as heck enjoyed putting it together. Thank you to Joe and Ron for joining us as well. We really appreciate you making the time to be here and to tell our story. Yeah, thanks so much for providing us full access. It was great to hear from the entire Five9 team. For the investors on the line, if you do have questions, we can get them in front of these guys, and we'll start to connect some answers. Guys, appreciate the time. Thanks so much.