NICE Ltd. (NICE) Earnings Call Transcript & Summary

Great. Well, let's get started. Good morning, everyone. Thank you for joining us here at the Morgan Stanley TMT Conference. My name is Jamie Reynolds, and I'm here on behalf of Elizabeth Porter. We're very pleased to have with us here today, NiCE's CEO, Scott Russell. But before we begin, some important disclosures. For important disclosures, please see the Morgan Stanley research disclosure website at www.morganstanley/researchdisclosures.com (sic) [ www.morganstanley.com/researchdisclosures. ] If you have any questions, please direct them to your Morgan Stanley sales representative. With that, let's get started.

Scott, obviously, great to have you back here at TMT with us. Maybe to start off, investor sentiment on the CCaaS space has been challenged for some time now, despite positive commentary towards the AI opportunity from NiCE, your peers in the space as well as consistent optimism in our conversations with channel partners. Where do you feel like that disconnect lies? And what's the path to closing that chasm?

Yes, there's definitely a disconnect. There's no doubt about that. Well, so first of all, I understand the discussion. I guess investors are underwriting AI as a disruption, we are clearly indicating that it's a tailwind. There's no doubt. Why the disconnect? I think it's partly because there is a lack of understanding of what the future revenue models are compared to what they were in the past and trying to figure that out. So let me try to explain that a little bit in NiCE's terms. Historically, we're a company that, yes, we have generated our revenue primarily through the number of seats. Those seats were people sitting in the contact center that were receiving interactions from consumers. Our revenue model in the future is interactions, and that interaction volume is growing and growing rapidly. So first of all, the number of seats are not declining, but even when they do, the number of interactions continues to grow. Just conceptualize it for a second. Right now, we live in a world, the single biggest constraint that a human has when it contacts a brand and the biggest single constraint the brand has when it interacts with a human is time. Time is the biggest inhibitor. Your willingness to contact the company is limited by your availability, your own capacity. And a brand's limitation is purely how many agents it's got, how many calls it can receive or how many interactions and the productivity of the contact center. If you fast forward the way the world is going to roll out, you're not going to be limited by your time anymore. You wake up in the morning and say, "Hey, personal AI, contact my bank and increase the credit limit by -- because I'm going to go on holidays with my family next month. Hey, personal AI, can you change my seat on my flight, I've got a business trip tomorrow and I want you to change my seat. Hey, personal AI, contact my utility, I noticed there was a line item on the bill that I don't believe is accurate. Hey, personal AI, I ordered some shoes last week, they're the wrong size, can you get them picked up and returned and then get the new ones." You will no longer be limited by time. But what will happen is the interaction volume between you and your brand will increase. So you're going to have -- and then likewise, for the brand side, their ability to be able to absorb that is not possible in a capacity-constrained contact center. They need the AI platform to be able to then deliver to that. So I think the fundamental assumptions about the disruption of existing revenue streams, while I understand the high-level thesis in the past, when you think about it in the world of customer experience, volume of interactions, complexity of interactions, speed of interactions and the ability to have interoperable interactions. You will not accept being handed one query by an AI agent and then your call shut off, you want to go to the right human that has the right knowledge that is -- at the right time to be able to deliver the right outcome for you. That is what customer experience expects. And in an AI world, we are just scratching the surface. Most use cases that you will see that we deliver and our competitors deliver in the AI market is pretty simple use cases for the large majority. It's why of the total interaction volume, only 2% to 3% are handled by AI. We've gone for the low-hanging fruit. And that's why the capacity of contact centers hasn't gone down because all it really has done is freed up capacity to do more value-adding activities that otherwise led you sitting on a phone waiting for an hour. Now you're waiting for 45 minutes. Maybe you're waiting for 30 minutes. Ultimately, you'll get to a point that you won't wait anymore then you'll start to see that -- and in between time, the revenue shift is obviously to our advantage. So look, I'm realistic about it because the way that we are winning in this market has changed materially, and our revenue models have changed materially, but it's a tailwind not a headwind. And our Q4 results and what we showed in our backlog, what we showed in our uplift, in what we have guided on 2026 and beyond, clearly indicates the market moving as a tailwind with AI and not a headwind.

Got it. And so just to follow up a little bit more on that. Where do you think the argument is most flawed today, either in terms of the number of agents that potentially get cut or who ends up benefiting? And why do you believe NiCE is best positioned relative to competitors, whether it be AI native start-ups or larger hyperscale and application software peers?

Yes. So where I think it's flawed is that if you look at it simplistically on a seat basis, our competitive moat, most SaaS companies monetize internal users of their software in an enterprise workflow. We monetize based on consumers interacting with the brand. We are the digital front door. That digital front door and the ability to monetize that digital front door has no limitation. So whether it's done by seats, whether it's done by an AI agent, whether it's an intermix of both, [ higher I'm ] able to win, the more the consumers interact with brands and interoperate with brands and deliver outcomes with brands, then we are able to be -- so our -- we don't have the disruption of seats and the revenue models of seats the way maybe some other SaaS companies have. And I think the early hypothesis of CX is everybody understood, "Oh, gee, AI could make it easier." Yes, it could, but it's still not going to displace all of the -- because no AI company has said 100% replacement of humans in terms of customer experience. So you still need humans, all the complex stuff that you want and a lot of companies will keep that. So the competitive moat around that. The differentiation for NiCE is very simple. Up until September 8, when we closed Cognigy, none of the CCaaS players could offer the market a best-in-class AI platform to deliver their AI experience needs. We all, at that time, leveraged third-party solutions that are out there in the market, some of the -- those competitors, those AI natives that are out there, none of them -- and to this day, we are the only ones that now have a best-in-class AI platform with NiCE Cognigy, a best-in-class CCaaS platform with our CXone platform. And as I quickly integrate and build a single unified stack, I am the only company that has the combined platform to do both, which means I can compete and we compete and win really well on a head-to-head basis on an AI-only where we're not involved with that customer, no CCaaS at all. We are winning in that market because it's growing, and you're seeing all of those AI start-ups in that space. It's why they're all flocking to it because it's a great market. Demand signals are high, buying indications are high. So we win there. But when the company wants to do real complex orchestration between humans and AI, and I use this example because it's real. What contact centers do today, what you probably don't realize, but it's built-in within our core platform is when you contact that agent, not only are we figuring out what you want, "Hey, I want to get my -- I'm disputing this line item of a bill." They're actually judging your tone, your speed of voice, what time of day, how many times you've called before, what did -- your purchase history, all of that data. And then what they do right now in the contact center is they hand you to a specific person. The technical integration to hand off from an AI agent to a human, anybody can do that. The logic to be able to route and switch to the right person at the right time, you don't even realize this, the amount of time a supervisor listens to your call with a human agent and then routes you to somebody else, it happens a lot. Why? Because they're worried about the call quality. They're worried about the resolution, a specialized knowledge and skill that is required. That embedded complexity and knowledge in enterprise CX, we are the best at it. We do that better than anybody. And then I infuse that with the AI world, I've got something that no one else -- the native AI players can't do it. The current CCaaS players can't do it. We have the embedded capability, and we're looking to exploit it. And I guess I would refer again to our bookings, the growth and what we're seeing is a clear proof point that we're winning and being able to gain advantage out of it.

Got it. And so then are you actually seeing these AI native start-ups show up in enterprise evaluations today? And to what extent is the message that you just outlined really resonating with the enterprise customers?

Yes. I've got to say, when I decided to make the acquisition of Cognigy earlier last year, the speed of the change, I wish I was -- I could lay claim that I was that prophetic. I knew the change was coming, but it was even faster than I had anticipated. I knew we needed that AI capability. I am not seeing -- so first of all, am I seeing the AI native players? Yes, I do. They are definitely -- mainly their value proposition is targeted use cases. They'll go into an enterprise, and they'll say, we -- let us build this use case using full deployed engineers, let us build it, don't have to pay anything, we'll fund it. And then when we prove that use case, that scenario, password reset, customer account creation, certain scenarios that have got a high volume, low complexity, and they come in and they do that. And they're good at it. Cognigy does the same thing. Are they being used to go and do the majority of enterprise engagement with all of the inherent complexity that a current contact center does? No, they do not. Do they want to? Yes. But that is a journey. It's why only 2% to 3% of the interactions are being handled by AI versus the -- what we all hope. And here's the trick that the enterprises are trying to figure out. They're doing these POCs and these pilots with AI companies, including us. Cognigy does a number of pilots with our own customers, but also with our net new customers. We often go in there and say, "We've done this. We've proven it." I'll go to an airline and say, "This is what we did at Lufthansa. Let us do the same thing." But what they're trying to then figure out is, "All right, how -- what's my road map of doing this at scale? How is it going to interoperate with my current CCaaS platform? How am I going to make that a consistent experience? So that has not started. It's all been on top. It's an incremental investment. But we're moving into when they're going to make enterprise technology decisions. And that's why the move of Cognigy with NiCE was so important because I've got a single platform that compete on that basis versus single players on either. The last thing that I would say is I think companies -- customers are no longer willing to just accept that they're going to have to go and build the agents. What are we doing with Cognigy? We're using those 20 billion interaction data and then generating, with a click of the button, AI agents. That's part of the integration. Because I don't believe the advantage is going to be my AI is better than yours. It's democratized. Everyone's got access to it. I can use the same agentic reasoning models as good, if not better than anybody else. It is not a competitive advantage. What is a competitive advantage is your specialized knowledge that you can put into an enterprise context at scale. So if you're a bank and you've got 100 different interaction types and you've got 0.5 billion of interactions that you do a year, we are able to, out of the box, click of the button, generate the 50 AI agents and how they will interoperate with your human agents, and I will natively have that in a single platform. An AI player can't do that and a CCaaS player can't do that. And I think that's what enterprises will need as they continue to expand in the use of AI in the context of their CX platform.

Okay. And then to put some numbers around the market opportunity. You've articulated a vision where the CX TAM expands from $31 billion in 2025 to $72 billion by 2028 as AI enables expansion into front-office, mid-office and back-office workflows. What gives you the confidence in NiCE's ability to capture these adjacent markets where you haven't historically participated? And to what extent are customers coming to you today to address some of these workflows?

Yes. So the most logical and easy one, and I think everybody understands the opportunity of a reduced number of people in the contact center and the reduction of that labor spend getting reinvested, more than 50% getting reinvested back into your technology stack. That is a big part of the wider TAM. Most of our customers today, for example, they ask us what's the ROI? Can I reduce my number of seats? So what we've seen is we haven't seen the reduction, but we've modeled the reduction from an ROI and the total addressable revenue spend goes up because any reduction of seats gets invested in more use cases that you deliver on your AI platform. The second, and I think the more complex battle is in the battle of orchestration. Our view of orchestration and what I mean by orchestration, I'll give you a simple use case with, you're a great customer of Disney. You call up about your streaming and you've got a family subscription and the quality of the service is not very good, and you want to be able to complain about that service and say you want your service canceled or you've got a change. There is a series of tasks and workflows. The human agent or the AI agent that interacts with you is not allowed to make the decision whether to cancel that. It goes through a workflow in through the organization. They will then maybe introduce a human to -- hey, look, can we understand your concern, madam or sir, how about I offer you something new and unique. And unique to be able to retain that customer. So there's a series of complex workflows that involve different stakeholders inside the enterprise that's not just done at the front office. Whose agent does that work is the battle yet to be won. My honest view is it is going to be a combination of our AI agents interoperating with other AI agents that are done by either enterprise LLMs or by enterprise SaaS players or by hyperscalers or a mix thereof. We've already got proven use cases. In the Disney scenario, we work really well with Salesforce. They use their platform in terms of the internal workflows, but they use NiCE as the digital front door. I could give you other examples as well. But that is where I think the market will go. And our belief is when that enterprise workflow of AI agents is to ultimately fulfill a customer requirement, we are the most likely builder of that workflow, and that's where the addressable market continues to expand because right now, we monetize only the human that receives the phone call. All of the tasks that happen in the back office, we've not had any role in. The human who is running on our platform does, but we've had no monetization of it. Now through the creation of AI agents that perform those tasks -- and I think we will go to the mid-complexity and task closed to the front office, but I think there will be an ongoing battle in that space.

And then when we think about the core, you've spoken to only about 40% of enterprise contact centers have made the shift to the cloud. We still have 60% to go. But within that remaining 60%, are these customers getting easier or harder to move? And then is AI accelerating their decision to migrate? And are you seeing incremental competitive displacement as part of that motion?

So two or three things to comment. First of all, the customers that have yet moved, a lot of them are international. It's still in the U.S. as well. It's still the U.S. market. It's certainly a significant market. But a lot of them are international. Many of them are in highly regulated industries that have certain constraints and guardrails around the complexity. So they're not willing to just flip over. They're very thoughtful in their consideration. What is very clear is every single one of them have in the top 2, often top 3 or top 4 criteria is the AI capability. They are not prepared to move without a knowledge about what the AI role is in their customer experience. That is why 100% of our 7-digit deals have got an AI embedded because they're looking at us and saying, "Well, if I'm going to move to your core CCaaS platform, I want to leverage the core AI capabilities that you offer out of the box." If we didn't have that, candidly, what happened to us previously before we acquired Cognigy is we still would have won and tried to compete on the CCaaS, but somebody else would have won the AI and competed on the AI piece. They're combining it together. So I don't think it is getting more complex. I actually think it's getting sharper on the ROI expectations. I've got -- and it's not only new. I would highlight this. I am competing for customers that have already made a decision to move to a CCaaS. They haven't yet migrated because it's a multiyear journey. It's complicated, and I'm going in there with my Cognigy platform and saying, how about we pause that. We go in with our AI capability, and then we'll come back on what CCaaS you need left. So I'm trying to use it -- disrupt maybe existing company's ability to be able to do core CCaaS migrations where we haven't been the winner. And I can do that because we've got the core capability now.

Got it. And then as we think about the near-term demand backdrop, I think on the last call, you mentioned customers are becoming more astute about the ROI expectations for AI. Are you seeing any pushback on AI pricing or any elongation of sales cycles as customers try to validate the returns before committing?

I find this remarkable. I guess I've been in and around the enterprise technology space for a long period of time. My experience is enterprise software buyers are very astute. They know what they want. They know the ROI. In the AI world, there's been an enormous amount of pilots and POCs, an enormous amount. Now it's partly because the AI start-ups are coming in and we're offering -- and they're trying to figure out what the ROI actually is. So 2025 was an interesting year. They clearly saw the benefits around augmentation copilot. So where you've got an AI assistant working with a human agent in a CX scenario, and we were able to prove that. As the year progressed, Cognigy, but also its direct competitors got more and more data about how does that reduce handling time, how does that reduce containment rate, what are the use cases that work, what are the use cases that are more complicated and don't. And they're getting smarter about looking at that -- the sharpness of the ROI and the benefits. What I find -- so it is definitely -- I think we will move more away from let's pilot, does the technology work. We're beyond that. They know that these platforms work. I do believe, however, what will be interesting is how you're going to commercially put your value prop there. For my company, I do not want to be dependent only on the revenue of seats. So if it's an existing customer, and I know that I can automate savings and that will drive efficiency in their contact center, I will offer it in a single platform. For a noncustomer, I will then be able to offer the AI that -- and I've got proven ability with data that I know that I can reduce Genesys or Five9's or Amazon's seats in their own contact center. So I think it will move from -- I wouldn't call it outcome-based pricing. Last time I checked enterprises were pretty smart, benefiting for the savings that they're getting from their use of technology themselves. They don't necessarily want to hand that always back to their partners. But I definitely see ROI-based value propositions being the core way of being able to compete and win.

Super helpful. And so then shifting the discussion back to Cognigy, obviously, a very complementary asset. But can you update us on the progress of that integration? What's been done already? And what are some of the major milestones you're tracking towards in 2026?

Yes. Let me start by saying up until us acquiring Cognigy, we were working with Cognigy and every other native AI player in the market, and we had done for a period of time because no AI player can deliver their CX requirements without the contact center data. Let me say that again. No AI player, no AI player can deliver the needs of the use cases without the contact center data. So every one of those players that you talked about before are an existing partner. They need the NiCE data or the other CCaaS vendor data. So we already had a prebuilt integration with Cognigy. It works seamlessly, no problems. What we have done initially was we have hardened and made more robust the orchestration of the data flows between Cognigy and the CXone platform. We are in the process right now of embedding all of the data that we had in CXone, which is our contact center, natively into Cognigy. So what it will mean is Cognigy, you will be able to not create AI agents, it will generate AI agents based on the data that you've got with all of the guardrails and context that you have. What we will have by the -- and that will be ready by midyear. By the end of the year, we will be complete orchestrated into a single platform where all of your data layer, your orchestration layer, interoperability between human and AI agents. I'll give you a quick example. We've got contact centers. Some contact centers have 20,000 humans sitting in the contact center. You're then going to have maybe 100 or 200 AI agents. Has anybody trained the contact center humans how to work with the AI agents? How it's going to interoperate? When do they hand off? What's the knowledge they use? All the rules of engagement around that. We've got a great history around workforce management. How do you manage the workforce of humans in CX? We're now embedding a single platform that manages your AI agents and your human agents into a single stack, so we can -- you can -- when you supervise and manage your combined workforce of AI and human, you can do it in a single platform. That will be complete by the end of the year. So all of the integration, the main -- the road map is on track, in fact, arguably slightly ahead. So we're tracking very well for our -- for that work to be done, which is critical, by the way, because it is competitively differentiated. No one else can offer it. And we have to do that at speed, which is why I had the targeted investments that I announced at Capital Markets Day that are largely first half, largely first half. So most of those investments you will see in the first half of the year as we get to the second half of the year, we will be -- start to be able to accelerate margin improvement.

Excellent. And so then on the go-to-market side, since you joined, NiCE has made substantial progress towards expanding its partnership ecosystem. I guess how should we think about the time line for these partnerships to more meaningfully begin contributing to improved growth?

Yes. I think there's two parts of partnerships that I would call out. There is perception and reality. Let me cover the reality first. The reality is most of those partnerships require technical, deep orchestration between our platform and theirs. So with AWS, the orchestration with Bedrock; with Salesforce, our orchestration with the Agentforce platform and prebuilt scenarios; same with ServiceNow and with Snowflake. That work is largely -- we will complete most of that early to mid this year, which means then in terms of combined offering. But when you're buying in the enterprise segment, they're not buying the product as it is today. They're buying the product that is going to be built out. So from a demand signaling and a go-to-market and an engagement model, we've seen material improvement around the way we're collaborating with each of those parties and with SIs, which I think we were not focused on to the extent that we should have been. So we're now -- we're already seeing the traction where customers will say, "Well, how are you working, interoperating with AWS or with Salesforce or with other key players?" And we are able to show clear proof, combined messaging from both parties, go-to-market plays around the joint value proposition. Too much gets made of the competitive overlap, and nowhere near enough gets recognized of the competitive synergies that you get. Yes, we will compete for parts of the portfolio. We've been doing that in enterprise software for decades and mature companies know that you can partner and compete at the same time.

Got it. And so then on the Q4 call and earlier in the discussion, you talked about record bookings performance in the fourth quarter. Even excluding Cognigy, you disclosed a significant increase in your cloud backlog, growing 25% year-over-year or 22% excluding Cognigy. Can you just unpack a little bit more of what's driving that strength and acceleration that you saw relative to 3Q?

Yes. So four things, and you could easily note that those four things will be the key go-to-market drivers for 2026. Number one, we were able to win as a stand-alone AI platform where we were not involved or even offered to participate with Cognigy stand-alone. Cognigy is a great product, proven capability, win and compete in a market that has a high demand signal, high profile. So we won in Q4. We've got -- and the pipeline generation is tremendous and being able to capture that. Number two, we already saw a large number of existing NiCE customers that have said, "We're going to make an AI decision. We trust you, we will work with you and then we will build that out." So we're winning inside of our installed base. I've got to tell you, I am frenetically pursuing that because we've got hometown advantage, and we need to make sure we capitalize on it, especially as NiCE is serving arguably the most complex, largest companies on the planet in their CX needs. The third is we had an improved win rate of our CCaaS jump balls. You asked the question earlier, Jamie, around how that's working. So when we've been competing with that CCaaS move on-prem, whether it's an Avaya or Cisco or Genesys on-prem, whatever, and they're moving to the cloud, because of our AI capabilities, we've been able to improve our win rates on those jump balls. I expect that to continue through '26 as well. And then last but not least is our international business continues to make great strides. We continue to have more wins, which arguably is in the CCaaS side. So between those four, that led to significant bookings in Q3, significant bookings in Q4, record in Q4. Our backlog is at record levels. You saw in Q3, our backlog was at 15%. Our backlog in Q4 was at 25%. I think the forward indicators are really strong. The only other comment I would make is backlog is great, bookings are great. It's amazing when you generate that much demand, you've then got to be able to execute it into live customers to ultimately generate revenue. You could appreciate that I'm putting a lot of emphasis on that because companies -- enterprises don't have patience at the best of times. But in AI, they definitely don't have patience. They want to be able to see the results and roll them out quickly. So it's created a good problem for our business.

Got it. And so then to just follow up on international a little bit more, obviously, a standout year in 2025, growing 16% for the year and accelerating to 29% growth in the fourth quarter. How much of that comes from the sovereign cloud investments you've made over the past year or so? And what does the international pipeline look like as we head into 2026?

Yes. Sovereign cloud, look, I have to credit the prior management. There was a lot of emphasis around building infrastructure, CapEx and OpEx deployments that had -- that didn't have a fast return, I guess you could argue. You could look at more broadly the AI market and what's happening. We sort of did it within our microcosm with our sovereign clouds. So when you look at the U.K. wins such as the DWP or the Australian wins at the Services Australia; some other wins with key utility providers in Germany and in Europe; wins in Africa, where we have -- with financial, highly regulated customers; all of them were on the basis of those sovereign cloud investments, our ability to operate domestically. And let's face it, geopolitical uncertainty has meant that further localization of your data, your providers, your services in those markets is key. I wouldn't call it -- it's not only because of the sovereign clouds because we've deployed and invested in capability more broadly in the public market as well, not just in sovereign regulated environments, but they are a key prerequisite for us to be able to win, and we're now seizing on the opportunity.

Got it. And so you spoke to this a little bit earlier. But at the Analyst Day, you outlined the $160 million of incremental investments for 2026 across three buckets, cloud and AI delivery, research and development and go-to-market. Now that we're a few months into the year, which of those investments are already in motion? And what are the leading indicators we should be watching to assess whether or not they're working?

Yes. So first of all, I probably should have in Capital Markets Day explained this in a little bit more detail. But Cognigy, right now, it will be margin accretive within 18 months. But right now, it's margin dilutive, structural effect of bringing that into the business. Now you didn't see that in Q4, but in Q4, we have a seasonal uplift in terms of our product and other revenues. But in a full year basis, there is obviously just a structural dilution, which is a key part of why you're seeing that with some of the dilutive effect. The second then is what I described earlier, the faster I can integrate and have a single platform that covers my AI and my CX and all into a single platform, the faster I -- my ability to differentiate against either AI native players or CCaaS players through a single platform. So that is a key part. And Cognigy's ability, I mentioned sales and marketing, they're a great company, great business, but they only had 300 approximate employees. So the sales and marketing coverage to be able to get as many at-bats on the AI native play around the world and particularly in North America, I needed more capacity to be able to go win and compete because the market is frenetic right now. That is largely, largely first half. So what you will see when you think about is that the investments, very sharp, very targeted that will largely be delivered in the first half. And so you'll see from a margin point of view as we go throughout the year that the margin will start improving in the second half, and then that will obviously -- that trend line continues in 2027 and beyond. I'm very confident of our ability to be able to hit the margin guidance and be able to show the improvement of margins as we head into '27 and '28 as we guided in Capital Markets Day with those investments. Last thing I'll say is we made a significant investment on behalf of our shareholders and in part -- on behalf of our investors of Cognigy. We then made it through our use of capital. We then made the organic investment through the use of our OpEx. We've got to give return on that investment to our shareholders, and I'm committed to doing so and doing so quickly.

Excellent. We are out of time. Scott, thank you so much for joining us this year. And to the audience, thank you for joining the session.

Thank you, Jamie. Thanks, everybody. Appreciate it.