ServiceNow, Inc. ($NOW)

All right. We'll go ahead and get started. Thank you, everybody, for joining us. We have Amit Zavery from ServiceNow President, COO and Chief Product Officer as well. So Amit, thank you for joining us today. .

Thanks for having me. Hello, everyone.

So look, originally, I think the shape of the conversation was going to maybe be a little bit different. But given the speed at which things are moving and the focus on AI. I wanted to maybe just jump right into that. And I think there's a lot of questions, some I'd say some debates. But can you talk about how the analysis platform has broadened both in flexibility and capability over time. And then I have a bunch of framing questions or follow-up questions after that. .

Yes. So I think if you look at just an AR, it's just moving at a very fast pace, right? So we, of course, started with the idea of GAI and giving summarization, helping users get more value from the content they have or what they're doing at the day-to-day task. Over the last year, 1.5 years, we reacted what we've done with noises, specifically becoming more of a system of action, right? So the idea of doing things with genic and making it an genic platform. So taking different AI agents, how you orchestrate them, how do you work with them, how do you use AI agents to finish task and coordinating the full activity end-to-end. It'll be the next phase from Genii to more agent use cases. And that has been a big game changer because now you're getting a lot more value out of the investment in AI and you're also getting a lot more efficiency associated with and removing some of the complexity associated with that, right? And when we started doing a lot of that work, 1 of the big things which came up was around this idea of governance, security, compliance, visibility. And we build on top of our now assist platform, something we call AI Control Tower. That was a big evolution because that removed some of the barriers customers had in terms of adopting AI, especially a genetic as well as ability to do have visibility across not just our platform but third-party systems out there as well. So our gentex platform has become more this heterogeneous connecting different agents together, but with visibility. And then over the last many months, at knowledge, we announced this idea of AI specialists. So we have 20 different AI specialists, which do full end-to-end work. So it's really human-equivalent AI specialist, like a level 1 support engineer, HRSD, or Service Manager, things around FinOps, things around security ops, things like that. and 20 of these AI specialists now really driving not this idea of you have to manage all your AI agents, but we're finishing that work for them -- and that is a big change, right? Because now you remove a lot of the barriers, the work you have to do, but you're getting an outcome, which you can also now calculate the ROI against a human cost associated with doing the same task. So that has been the evolution. And now assist has gone from -- we use that as a term, but it's pretty much across all of our portfolio, right? So we're adding AI across our stack and making sure we have a tiering in terms of functionality. -- but also making sure that this kind of capability becomes much easier to use as well as adopt across the different kind of use cases which are happening inside the enterprise. And we've been adding a lot of more capabilities across the board in this area now.

So there's a lot I want to unpack there, especially on the technology side. But before I jump to that, you mentioned this idea of lowering the barrier. And I think 1 of the big changes that happened recently was putting AI at every level of the product portfolio. So maybe help investors understand what signals drove that decision and what it unlocks for the end customer. .

Yes. No, I think so if you look at -- we had this Pro+ SKU, which is the now assist idea of providing a premium capability for doing automation. And we had this hybrid pricing for the last 1.5 years already. So we have got a lot of signals from the customer that they like this idea of combination of flexibility and predictability of the pricing. They like that they need AI and they can get that full end-to-end in 1 particular offering as well. But 1 of the feedback we were getting is that why do we have always started the top, right? There might be some other use cases. I want AI as a table stakes. So we wanted to make sure that we bring AI not only in the premium SKU but AI capabilities all very, I would say, factored by functionality in different tiers, but available in all of our products. So we don't want to have a non-Ind mindset anymore inside the company. Our customers don't want it. They want to be able to adopt AI as part of the same products they buy from us, not just 1 of the products. So that kind of drove this. We knew the pricing has worked. The feedback we got from our customers were very positive, how we've approached this AI capabilities in our Pros. And then we tiered the functionality and gave the base capability in the in the SKU we called Foundation. And then we have advanced queue, which has little more ability to do take action on top of it and then autonomous at the top tier. So that's what drove it. And it allows us go-to-market to be much more simpler. -- for our reps to go and have this conversation with the customers. It allows us to monetize across our full SKUs as well. Our messaging becomes much more simpler as well. And also let me drive 1 integrated technology stack instead of having fragmentation in a product for no reason really. Over time, we had to get to an end to end. So we kind of took that accelerated path towards it based on the feedback we've received has been very positive so far. -- customers is like this idea that they can start anywhere and they can get the value of AI investments we're making. While we let them move up as they need to -- and we can preserve the top capabilities only on the top tier anyway. So we're not losing any of the revenue opportunity, but we're monetizing in other SKUs now as well.

I think the simplification makes it a lot easier for adoption. And I think that's important. And the other thing investors are really focused on, we hear it across the different platforms and software, who is going to be the AI control -- now I know the knowledge in the Financial Analyst Day, you unveiled it to investors, but help us understand what ServiceNow's platform, what allows it uniquely to be well positioned to be the control tower for organizations. .

Yes. I think you look at ServiceNow has always been this system of record for enterprises for any kind of assets, right, with CMDB, which is the core foundation of ServiceNow, which became kind of the way companies adopted ServiceNow was to really have visibility across every asset they have inside the company, any hardware, any software, any IT asset. And if you look at what AI agents are, it's really a software asset. So for -- we were already discovering everything a company was using from IT perspective and bringing into CMDB for many, many years. And if you ask IT departments in terms of knowing what they're using, what licenses they have, who's using how many of those licenses, what much you paid for it, all the stuff they used to go to ServiceNow CMDB to get that data typically. -- right? So for us, it's a very natural extension to now say that I will also discover and track and manage and give you visibility to AI agents. We discover them just the same way in the same architecturally. We, of course, build connectors and adapters to discover a lot of the next-generation AI systems out there. But for IT managers and IT system owners, this was like, okay, I already have all the other business, I don't want to go to a third-party system for only AI-related stuff. I want to go themto the same place where I can have full license visibility, all usage visibility, all cost ouvisibility. So that's what drove a I control tower. And second thing, we're always doing compliance management, auditing, risk management in the CMDB as well. So it was very natural for us to expand that into the AI domain as well. And the reason why we've been able to do very well is because it was not very difficult for them to implement this. It comes naturally as part of what they already have in the IT systems. And what we are thinking of it is that, one, we always been heterogeneous -- we look at everything inside a particular enterprise systems anyway. I can give you, as somebody managing the environment, full visibility control, while I integrate with third party. So it's not only about ServiceNow, always been about the third-party systems as well. And that's what's giving us the right to play, right to win, and we were winning in that area, right, because we are probably as neutral as it gets from all these things. We discover all these things. We give you the cost management associated with that. and really remove some of the barriers associated with this shadow AI projects or cost runaways or even security. And 1 of the reasons we did the acquisition of Vesa was that idea of nonhuman identities. right? How do you have visibility in the nonhuman identities, the governance associated with that? Any kind of security issues you run into? And what are these AI agents doing given the changed identity so frequently based on the role and request they get. So it became very natural for us to keep on expanding into it. It's been resonating. It's 1 of the fastest-growing products for us as we speak. And it really gives a lot of peace of mind for any operator inside an enterprise. right? So -- and our view and our vision is that we would kind of integrate with all these different things out there. And we are not just saying it has to be only about ServiceNow. And that's why our integration with Anthropic, Google, Microsoft, open AI, but also a lot of agents coming from Workday, Salesforce, others, we can bring that into 1 place. And nobody else has been able to do that today.

So earlier today, to kick off, we had the CIO of Jefferies on stage. He said in multiple different ways that we're essentially a service that shop that we -- that's not something we're going to create that we're going to continue to build on it. But he also mentioned this idea of the difficulty around on agents, right, that we didn't build for a world where you had agents, you had humans that were meant to work, right? And so you just mentioned with the acquisition, how does the recent M&A allow you to help companies monitor what agents are doing? Kind of what's the unlock there that other systems aren't designed for maybe speak to the M&A specifically how that adds to your capabilities? .

No, I think you're hearing the same thing as I talk to CIOs and all, right? One, they do depend on ServiceNow. It works very well and just because you can do something separate differently, don't need to. right? So I think that's been pretty much the theme I talk to every customer. And then the second thing is that our view always has been we need to keep on making sure we bring the value of AI or any innovation as a matter of fact, into our platform, the customers don't have to deal with it later. right? So we keep on modernizing my job at the company and what we're doing with our R&D work as well is to really ensure that we remain ahead and continue to innovate to give value to us. So if I look at the landscape of opportunities for us across AI and what we've been building, see the AI agents are going to be a new paradigm, and it's already starting to happen where they will interact with all the systems. So users are not only going to be going and pointing and clicking through UX. There will be also AI agents who will request some activity from third-party systems. Similarly, so 1 of the reasons we have opened up our platform, and we launched something called Action Fabric is to allow any AI agent to call into ServiceNow and allow us to do the actioning for the right? And we've been always a system of action in respect to whether you come from RUX or you come from copilot, you come from Enterprise Claude or co-work or whatever it is, we don't really care. But we also want to make sure that we also provide you the first-party experience if you want to choose to -- so our UX has been modernized drastically. I mean, if you look at the experience layer is as AI native as it gets with the conversational first mindset. The Move Work acquisition we did kind of led that to give this 1 unified modern experience across all of our products. And then we added this idea of conversational experience for voice and multimodal omnichannel into the same platform. So you don't have different stacks for different things. and it's completely modern going forward. And then underneath the covers, we're doing a lot of work around security, compliance, and visibility and giving that view to our customers so they don't run into issues when they're deploying AI and they find nefarious things happening into the system. And I don't know how many people realize we have a very large post-breach security business. $1 billion plus and has been growing very significantly. And when we now augment a lot of the cybersecurity vulnerability management, as well as nonhuman identity or devices, which is becoming big as well by devices are accessing a lot of the system as well. that's about the acquisition of RMS and Vesa fits in. RMS gives you full understanding of any devices out there in the system. Be it OT, IoT, medical devices, physical AI now, which is becoming prevalent inside shop floors and manufacturing environments and hospitals. So how do you bring -- just like we were doing any asset, we need to bring every device into this -- and now this idea of a platform, which has full visibility, full understanding, provides securely and then giving you the ability to interact with that through our UX, third-party or any agent -- you have a platform which is very robust, very end-to-end capable, very modern, but also in a very secured governed and compliant manner. -- which really gives you peace of mind if somebody is going to operate it. So I keep on modernizing while keeping the enterprise mindset always in a platform. And that's why a lot of customers love it because they can keep the same platform as we upgrade, they get new features. You don't have a re-platform, right? So our platform is still 1 platform. We add new domains on top of the same platform, but it becomes very simple for customers. That's how we've been able to get into CRM and other areas because it's the same underlying technology stack. And now you have it a very modern AI native stack under need the covers.

So I want to pull on some of the newer areas that you're moving into. But before I get there, I did want to touch on the M&A question, right? And if we zoom out, there happened to be a cluster of M&A in a very short period of time -- and so the follow-up question has been, is there a shift in strategy? Or how should we think about M&A going forward? So I figured as a technologist, like how are you thinking about the M&A strategy at ServiceNow? What led to the recent M&A? And then how do you think about it going forward? .

We have been very careful with capital allocations in general, right? So I mean we definitely want to make sure we feed our organic engine everywhere. I mean, everywhere we have opportunity, we need to make sure we build the best product, which are well differentiated, but AI also opens up opportunities to expand our TAM and areas where we believe we can accelerate our road map based on customer demand, where we can also build out -- continue building our differentiation and new opportunities for us. Our tuck-in -- ServiceNow has typically been doing tuck-in acquisition, and that all continues, right, where we want to find good IP or acquihires or good talent who can help build our teams faster and provide better delivery on the road map and new IP as well. In some areas, as you mentioned, in some of the acquisitions we did recently, cybersecurity, and I think the security space for me and for all of us is really relevant to AI. Without that capability in the platform, you really become just a feature provider without any kind of governance and security associated with that. So we saw an immense opportunity with the acquisition we did of Arms to augment what we did with CMDB with any asset now to expand. We've been talking about OT anywhere. So we've been doing IT and OT work. Now adding the security layer around that changes the game. They are -- they have a lot of good IP, very domain-specific capabilities and adding that to our security business, it really does 1 plus 1 is much bigger than we would be possible to otherwise, right? So that's really the kind of drivers for some of these things. I think we are at a point where we have all the assets we need at the size we're talking about. There will always be tuck-ins when we need to or where we find something unique. But beyond that, I think between what we've done with Arms and Moveworks, we cover what we need. Vesa is a smaller company, but it gave us this ability to do non-humanity with a patented access graph technology, which is very critical. You talk to any large company now, they want that. We had done another smaller acquisition of Logic to really expand what we can do with CPQ because that's a more AI-driven has capability, so you can do accelerated configure price and code. So we've been always finding those things so we can really get faster at where we need to go. -- and bring in people who have a lot of the domain expertise. And I think it has worked out well so far. But as your question is broader in terms of acquisition, I think what you should expect is the tuck-ins. And beyond that, I don't think that there's anything we really need to do drastic.

I think 1 of the things that underpins all of this is when the company rolled out Raptor DB, which I think, allowed a lot more workload horsepower. Can you just help us understand how that underpins all of this and maybe what adoption of Raptor DB Pros look like? .

Yes. I think it's another area where probably a lot of people don't have understanding like we have a very large now, very fast-growing data analytics business. The core foundation -- a couple of core foundations to it. One is Raptor, which is post Gres database, but we rewrote it to be more of an HTAP. So basically hybrid, both analytics as well as transactional processing database. And all of our products now underlying that it comes automatically with the rated standard. right, so that you have a good scalable, highly performant product available to all our customers. Given the size of ServiceNow deployments have grown quite a lot across customer. We wanted to make sure we have a very full proof and balanced database under the cover before we used to use some open source technology we didn't steal to the level we need. But beyond that, what we're discovering now is that customers want to do a lot more with the information they have ServiceNow as well as bring in other information through the zero-copy adapter or any other way. So what DDB pro does is, 1 is much more highly performant and scalable. Performance is like 17x or what would the standard would be. Plus, we've been able to now do a lot of analytics workloads on top of it. So you could do insight to action, you can understand what your incidents happen, where happen, what you need to do with it, also connecting to Databricks, Snowflake, big query and really do a much more -- a very detailed analysis associated with that. So we've been able to sell that. It went to $100 million in a very short amount of time in the last 4 quarters. And we continue to see that expansion happen because there's a whole thousands of thousands of customer service now who do have that, and we can easily go and talk to them the value of going to Pro. But on top of that, what we build is the idea of workflow Data Fabric, the connector as well as the integration into 300 different data systems. And then we are layering on top of a semantic layer and a data catalog to do analytics apps which we can now monetize by different domains as well. So this portfolio and the platform has grown drastically to be now providing a data stack. And using that stack, we did a knowledge graph. We have a context engine. -- all built on the same stack where customers can now use a lot more capability from ServiceNow than they could typically before they used to extract and move everything around. Now they can do inside ServiceNow and they get more idle because they're touching so many different systems anyway. So that's really the Raptor DB as well as the workflow data fabric and the data analytics stack. I mean we have said openly that's our next big growth engine. It should be getting to $1 billion plus and continue to grow beyond that because it really changes platform can be used and to a different use cases than we were monetizing before.

Helpful. And you mentioned now different growth opportunities, and you mentioned moving to different areas. I think 1 of the questions we get commonly is maybe around the right to win in categories like CRM. And I think it would be helpful maybe even to explain just what is ServiceNow focusing on in these newer areas? And where do you see maybe existing vendors as competition versus you're just offering something that isn't addressed. Can everybody play silence their phones, let's just all do this at once. .

Yes. No, I think our right to play has always been about really doing actioning across multiple different domains. And the heritage has been IT no doubt, but case management. Like how do we resolve an issue somebody has. So that we did the IT, we do that for HR. We do that for finance. We do that for procurement, we do it for security now CSOs the second largest buying center for right? Because any incident happens, somebody needs to help you resolve it. And then you need to coordinate across many people, there's a workflow, there's a resolution plan, there's triaging. Same thing applies to customer service. . So when we look at CRM, it's a natural extension of what we did inside the company. I can do it for outside the company for enterprise. -- right? Because what we're trying to do there is like somebody has an incident with customer service. They need help. Somebody needs to answer that either on a chat or a phone or whatever other mediums is and then triage that and help other people resolve it. and get the result decision back to the end user. So when we look at CRM, it's really about expansion in areas where we're good at. So it's customer service. You're not doing like full-blown SFA, marketing automation, things like that. CRM is big enough space. The largest TAM is customer service, and that's an area where we are very good at. naturally, we are starting to win there. We -- as you see the numbers there, 1 of the fastest-growing area, a couple of billion dollars now and heading forward. So that has been -- but the core of it is really the complex orchestration and with an outcome mindset, not just giving you an information, but taking action. So if you look at customer service, taking action by resolving something. You look at what we're doing with CPQ, same thing. You're configuring something, you're taking pricing associated with that, then in getting a code. So it means you're connecting various different systems together and now making some decisions for them. helping you orchestrate that getting an outcome, which is a code, not just like, say, tell me what is my forecast because that's just information gathering. How do you do these various steps, which we've been very good at for years and years. That's really been the heritage of ServiceNow for 20-plus years. So this idea is where is applicable for us, we go. And we started with, of course, IT, but very naturally, we moved into other areas because the same platform, we don't have to rebuild everything. It's the same technology and the need coverage. So the customers love it because when they add new domains to us, new workflows on it, it's on the same platform. So you're not replatform every time you want to add this particular use case versus what you find with most of the other vendors is that every use -- every domain is a different platform. different stack. Marketing is different stack, sales is different stack, services, different stack, IT is different stack, which is painful. So that's why customers and IT love us because we are able to do this thing on the same -- the same way is very modern and able to do this thing very quickly. So that's our right to play, and that's why we win. So yes, there will be natural worry that there are a lot of other vendors in every space, but we've been multi-vendor competition for every space we've been in. Is this that we have to make sure we out innovate. We build the best product, make our customers happy, and we've been doing that, and we feel that we will continue doing that because we have that ability to do it.

Well, I think the growth speaks for itself, right? It's been very durable because you guys have been making customers happy and adding a lot of value. As I think forward to the 2020 -- 2030, I cannot believe it's going to be 2030 in a few years. But as I think about the 2030 targets and the growth to get there, can you maybe just help us think about what you think is going to be the biggest engine to drive to those 2030 targets? And I have a couple of follow-ups.

Yes, yes. So 2030, I mean, you saw the numbers we're talking about. Our base case is $30 billion, right? And a very good growth rate as well as improvements continued improvement in the margins. free cash flow while absorbing some of the acquisition plus also a lot of the innovation we're doing, right? The growth drivers are straightforward, right? One, our AI stack and the agenetic is going to be what we're seeing with our already increased guidance on top of what we're doing with -- now assist this year, and that continues to grow. So a lot of the use cases we're doing in that area will drive a lot of that growth associated. Second growth driver security space. I think security risk is becoming a very key element of our portfolio and the assets we have, the differentiation we brought in and the innovation we're bringing in there is a great adoption happening already, plus also solving a lot of the critical problems to remove the barriers for AI. . The third driver is workflow data fabric and the data analytics stack is 1 of the big growth engine for us, and we're already starting to show that acceleration. -- and the more investment we make in there to continue bringing a lot of the data and the ability to do analytics on it, it drives a lot more value of our platform. And the fourth 1 is CRM, right, customer service, the CPQ and CPQ is leading a lot of the conversation with the customers to really improve how they deal with their end customers. So those are the growth drivers, the platform broadly touching everything around IT, HR, the employee works which we released recently between the combination of Moveworks and what we do for HRSD, just bringing that thing into the platform end-to-end and then have the AI associated with every product. And then you layer the data, the security and CRM, suddenly, you have a portfolio which is very robust, very fast growth and differentiated in the market. And that's what will get us to the -- beyond the base case as we expect in the future.

Helpful. So I want to end on a curve ball that I didn't prepare you for, which is I love asking technologists what they have found to be either. I'll let you define how you want as Rohrschach test, whether whatever cool means, but what has been your coolest experience using AI tools, whether that's as an employee at ServiceNow or whether that's in your personal life, what have you found to be the most interesting thing in terms of your AI utilization.

Me, I should be really look shoudn't care is AI. Why do you care AI or what it is, right? If we can help me solve my day-to-day job, and make me more productive and make me better. That's how I look at AI. So I'm not really looking for AI tools anymore. I'm saying like how has my product improved by it's using AI -- so I think the AI special -- I'm really excited about what we're doing inside service now with the i specialist because it really changes -- it does what you need to do in a short amount of time with better outcome and solve the customer problem. And eventually, what you use underneath the covers as an end user don't care. As the technologies I love it because I'm using a lot of this technology to learn how we can do better with our products, but end user when I look at customers, I shouldn't worry about it at all. .

Super helpful. Thanks for joining us. Great to have you and wish you the best of luck.

Thanks for having me. Thank you, everyone.