Thank you for everybody for joining here. It's a great pleasure to be here with Amit Zavery, President, Chief Product Officer, and Chief Operating Officer, ServiceNow. Amit, thank you for joining us.
Yeah, thanks for having me. Hello, everyone.
We're back here a year on after what's been a very consequential 12 months, I think, in ServiceNow's history. You guys have 3 highly strategic acquisitions, launched Autonomous Workforce, wholesale repackaging under a new kind of scheme with foundation advanced Prime categories. Just had your Financial Analyst Day laid out, a $30 billion subscription target by 2030. Lot to dig into, but we can start off simply. Love to hear introduction of yourself, your background, and a little about what you focus on at ServiceNow.
Well, first out, it's been a busy, I'd say, 12, 18 months for sure. I've been at ServiceNow for the last 18 months. As you mentioned, I run the product engineering operations and product strategy for ServiceNow. Previously, I was at Google Cloud for six years, where I ran all the platform teams, including a lot of the strategic products and portfolio there. Previous to that, I was at 24 years at Oracle, ran various different groups. Before I left, I ran the cloud team as well as all the middleware and the platform team over there as well, which was substantial part of Oracle's revenue. Very excited to be at ServiceNow. Lot of things going on.
Great portfolio, great product, plans going forward, as well as great customer base, so really good time to be at ServiceNow.
Yeah. Yeah. I think we should start off with what was probably the biggest topic for me when I was talking to the partners and customers out at the Knowledge Conference, that's AI Control Tower. A lot of traction with it. Our checks suggest that customers are deeply concerned about, you know, their AI sprawl. They don't know what these agents are doing, shadow IT, not to mention the cost side of it as well. You know, they need something to bring in this all together. You can talk about, you know, what's differentiated, kill switches, all those pieces. I think one thing before we get into it that's interesting is, you know, this is a very contested space. Everybody wants that governance and control. Customers are choosing you guys to do that.
Can you describe why it's so differentiated and why you guys are the right platform for customers?
See, AI Control Tower, last year when people started talking about agentic, and even when I was at Google, the amount of AI work going on, and I was building a lot of the AI technologies, it was clear that customers are going to face a lot of issues managing the AI capabilities, the usage of AI, discovering a lot of things which are going inside the enterprise, and really making sure it's secured and governed. Last year, we launched AI Control Tower. One of the reason behind that is whenever we're talking about agentic to those customers, they were really getting worried about security, governance, compliance, auditability, as well as, just visibility broadly.
ServiceNow has this product called CMDB as a core foundation of our product portfolio, where we manage and monitor all the assets inside an enterprise, any IT asset, hardware, software. For us to do that and extending that to AI was very natural. AI agents are software. We are discovering a lot of other things for every IT systems out there anyway. We added the AI agents as a way for extending what we did in CMDB very quickly and easily, and then giving them so much monitoring and measurement as well as a cost management associated with that. That opened up a lot of conversation with our customers.
The reason it's kind of valuable for us as well as why we are differentiated, one, as I said, we already had the foundation for managing and monitoring a lot of the systems, AI was very natural. Second is, I think, we were connected to so many different systems out there. I mean, ServiceNow is kind of enterprise OS, the way you think about it, connecting various different system, east to west across different systems already. Very heterogeneous, very open ecosystem. For us to be more of a neutral third party where we can now not just track our AI agents, but also discover things coming from any different systems out there, hyperscalers, all the large language or frontier model companies, any AI systems or system of record.
Providing a full governance layer on top of that, just like we did for any asset, became much more differentiated because of that. The other part which we have been doing very well is we recently did an acquisition of a company called Veza, which has a patented technology called Access Graph. An Access Graph for non-human identity is becoming very critical element for monitoring and managing AI agents because their use cases as well as the identity changes so frequently, and you have to do that monitoring real time. They do around 30 billion different permissioning and parameters for non-human identities.
We brought that into ServiceNow AI Control Tower, and that suddenly changed the game for a lot of our customers because they can feel more confident about AI systems not taking wrong actions or doing wrong things and giving them the visibility. There's tons of stuff going on in our product portfolio, and that has been really well adopted and differentiated, and we continue to invest and provide that capability with ServiceNow AI Control Tower now.
Maybe to double-click a little bit in there, you know, you have this product that's answering a lot of customer needs. You know, customers are in different parts of their AI journeys. At what point do they kind of hit that where they're like, "Oh, we need to do something that's like AI Control Tower"? Is it a cost function? They're like, "Oh, all of a sudden we're spending more than we expect," or is security the main function where they're like, "Hey, if we wanna push this into production, we need to have a way to make sure that it doesn't go rogue"?
Yeah. I think it usually starts with, when more usage of AI starts happening. Like, if they want especially.
where you have all these business processes and systems connecting various different AI agents together, and there could be a lot of shadow AI projects happening. Then you have no idea what's going on and who's spending what or who's using what. Last year, as we said, when the agentic use cases were starting to emerge, a lot of the worry customers had around was just control and visibility. What AI Control Tower conversation started was just peace of mind. Where you don't have this sprawl of AI without IT knowing what's going on, who's using what, how much they're spending. It really accelerates the AI adoption by having this as a central control plane and heterogeneous. A lot of the providers today, they do pieces of the technology for their own visibility.
They might connect into a few other things. The end-to-end discovery mechanism and the whole monitoring and visibility mechanism, it doesn't exist in the market other than AI Control Tower. I think it just removes that.
Yeah
for adoption of AI, because now IT team members as well as CIOs and CISOs start feeling a little more confident they can get going with AI without just random stuff happening inside the enterprise.
Yeah.
With enterprise, anything I mean, you've seen a lot of examples, I mean, you saw the recent PocketOS and others, where if you don't have visibility and control, things can go completely wrong, and you need to have some guardrails, and this is what it allows them to do.
Yeah. It's a gating factor so they can deploy more. If we go to something you already touched on, which is the acquisition, Moveworks, Armis, Veza. One thing that I noticed is, you know, I think investors have been kind of trying to digest, you know, what it means, why they're strategic. When I talk to the customers and partners, they seem really clear about what it brings together, why it's such a high value. You know, there's been a lot of companies that do acquisitions. This was one of the ones where they seem to be paying attention a lot and kind of see the vision that you have. What do you think that they're getting that maybe investors kind of haven't wrapped their mind around?
No, I think we've been very disciplined and thoughtful about what we acquire. Over the last, as mentioned, with the AI growth, there's an opportunity to really innovate faster, get a lot more domain expertise in some of the areas. One of the biggest areas we've seen a need for is around security and governance, right? The acquisition like Veza and Armis fit into this idea of how do you really monitor and manage the proliferation of AI systems, but also devices. Armis provides the ability to do OT, IoT, as well as medical devices, vulnerability management, and exposure management. Today, our business and security space is $1 billion plus, which happened last quarter.
Q3 of last year. That was organic business we built over a few years, and it continues to grow very, very fast. What we saw from customers was that you already manage all the IT assets. Why are you not able to now do also a security and asset and vulnerability management for non-IT assets like OT, IoT, and specifically medical devices? Armis fit in very well with that kind of mindset, right? We allows us to extend to any kind of devices out there, and also extends what we have in CMDB and augment that with millions, billions of devices into that system as well.
That as the growth with physical AI and other things come up, we see a lot of value for ServiceNow to provide that exposure management and vulnerability management on top of post-breach work we were doing already. Similarly, Veza is a little much smaller than Armis is, but this idea of patented AI access graph technology, again, augments everything we do for non-human identities, just like we use for human identity. The identity governance specifically becomes very critical. Our security business and the product portfolio roadmap got accelerated by this acquisition. We're bringing a lot of good domain experts in this area who are well-versed and have been doing this for quite a few years, and made our story much more powerful to customers as they think about AI adoption as well. We continue to do the integration with third-party systems, right?
This is not like it's replacing a lot of things we were not doing before. We integrate into a CrowdStrike for endpoint. We integrate with Palo Alto and network-related stuff and get a lot of signals. The whole exposure and vulnerability management with the idea of post-breach. Today, CISOs are second-largest buying center for ServiceNow already.
Right? IT, CIOs were number one, and CISOs are number two. It was natural for us to keep on expanding into these new areas, not only increase our TAM, but also accelerate our roadmap and bring a lot of this expertise into our product. It has resonated very well with our customers. Our pipeline since the acquisition has grown for security portfolio very, very well, and we continue to see a lot of good traction with the product being integrated. The Moveworks acquisition was very much led with this idea of conversation first, AI native, experience layer on top of ServiceNow. We have a great set of technologies today for doing, actioning, fulfilling a task. On the requester, we wanted a very AI native experience, and Moveworks brings that.
That's now integrated into our Employee Center Pro product we had, the whole employee center, and bringing this thing together as EmployeeWorks. In the first quarter, we announced, I think in the Q1 results, we did more as a combined product than what the Moveworks has done by independent last whole last year. We saw acceleration because of the roadmap being integrated, able to deliver a lot of new AI-native capabilities on our product portfolio, and it's becoming our user experience across all of the offerings we have today, right? We've been very thoughtful about how we bring all this stuff together to really differentiate, accelerate the roadmap, as well as continue to innovate in all these areas.
Yeah. One of the debates out there obviously has been, you know, if AI is going to generate all this value, where is that value gonna accrue? You know, where is most likely gonna get captured? I think you guys have been pretty explicit that, you know, the moat is not necessarily the LLM. You know, you guys have the Context Engine, there's graph of graphs anchored to the CMDB, layered with Veza. Armis is included in there too. You guys have 100 billion annual workflows, 7 million, excuse me, 7 trillion transactions. You guys put it pretty simply at your Financial Analyst Day. There's no competitor that can do that, right? Help us understand, you know, in layman's terms, what the technical reasons are that others can't do that.
What do you provide through your platform that enables that differentiation?
Yeah. I think you have to remember, I mean, we have been doing this work for our customers for 20-plus years. The amount of data we collect, as you said, 100 billion workflows we run, plus 7 trillion transactions happen on our platform, which is growing at 20-plus%, 25%. So the metadata we create, the context we generate around why a decision was when made in a business process, why an exception was done, who made those exception, those are not available in any documents which our LLM can read.
These are all information we're collecting as you run these transactions. That's in a Context Engine which is distributed across multiple areas. Metadata is very hard for people to understand what to do with it if it is not done by ServiceNow as a part of our workflow, right? We build that. The CMDB, as I said, is really kind of the enterprise database today, right? Used by all the Fortune 500 and pretty large number of Global 2000 companies. That has become the kind of the underlying ways for large enterprises to operate on ServiceNow.
All the systems today, they operate the operational part of it, in terms of executing the workflows, business processes around for IT, employees, for security, what we do for customer service, FSM, and other things like that. It's pretty broad and deep for many years. That information allows us to now take some advantage of AI technologies like LLM, which is probably around 8%-10% of IP in our stack, but the rest we build and operate over this information we have collected, plus the efficiency we have gained. Everything doesn't require need to be an LLM driven, right? There's a lot of deterministic things we do which requires much more understanding of our business processes and not have to say it's land of spending money on tokens, but you can still operate that very efficiently.
We bring the deterministic mindset to a very probabilistic systems like LLMs and still give you a guaranteed outcome, because you can't make mistakes in enterprise systems. If you get the wrong answer, you instead of onboarding an employee, you de-board an employee or you have the wrong financial results, it's not going to be very valuable to you as an enterprise. The context we have gotten, the way we run the systems, the 20 years of experience, plus having our stack been very AI native now, right? We're getting the same advantages as AI companies have in terms of technology, we're wrapping and providing a lot of insights into these things. We also work in a very open ecosystem, right?
Customers talk in many different ways. You can't just say that there's only one way to operate today a business. Having that opportunity to integrate into lot different system providers, like system of records, integrate into any kind of hyperscaler, be able to also run or use any large language model, any data provider, any tool to build your workflows custom on top of our ServiceNow platform, and have the whole governance and security layer. One of the biggest issue you run into when you're building the systems out there or running a business application, a business process, is the security and the governance. I would say most of the time when we build our products, they have to be compliant.
We spend probably 50%-60% of our cost of engineering and R&D is around that whole security compliance and things like that, which are very hard to replicate from scratch. It takes years of hardening. The lifecycle maintenance around that is pretty long. Customers need a place to call when things go wrong as well. That's all the things we provide out of the box, working together with our customers, proven and operating at scale. The partner ecosystem associated with that, right? The go-to-market muscle we have for years and years of building that relationship with our customers. Those things all add up to really be able to provide that comfort for our customers as well as differentiated and innovative products long term.
Yeah. That 50%-60% statistic's pretty interesting.
Yeah, a lot of people forget. The people think build is the only thing you have to do.
Yeah.
Build is itself is 20%.
Yeah.
The rest is all around everything you have to do around it.
Yeah. That's what it takes to be in the enterprise, right?
Yes.
Um-
Very boring, but painful, but important.
If we go up one level with this AI topic, Bill McDermott is in the Q1 call that the Now Assist target was being raised from, you know, $1 billion to $1.5 billion, 50%. I think in Q1 you guys were already around $750 million. You got growth in customer spending, 1 million+ on Now Assist, growing 130% year-over-year. You know, that's all real acceleration. Importantly, I think Gina kind of emphasized the methodology hasn't changed, even as if you guys kind of repackaged some of the some of the pricing. What's given you confidence in that revised figure as you move away from this kind of sidecar AI concept to help fuel that growth and, you know, maybe even kind of go beyond that?
I think we've been monitoring, of course, our pipeline as well as the customer interest and adoption associated with that and the renewal as well. As Bill mentioned in Q1, we'll be going from billion-dollar ACV to a $1.5 billion target this year. Our plan was $1 billion. We feel very confident with $1.5 billion ACV on that one, is because I think 1, with the agentic use cases and some of these things going production and people using it, we're seeing the volume of usage go up very fast. We're seeing a lot of interest to do multiple use cases than what they started with as with enterprises. That gives us the ability to say, "You know what?
We will end up using up whatever entitlements the customers had previously, and when they'll renew, they will renew at a higher, longer, broader entitlements, or they might buy us as packs early enough. That is one vector which we see happening. Second thing, as we think about some of the things we're adding around our product portfolio. Our product portfolio has grown drastically. We've added things like AI Control Tower, what we're doing with EmployeeWorks in terms of amount of requests coming into our system, which will land up burning down lot of the Now Assist and the request volume will continue to go up. What we're doing with security portfolio is pulling a lot of this conversation for monitoring and managing a lot of AI systems as well.
Suddenly we are in more conversations about AI than maybe previously we were.
Yeah.
I expect our renewal sizes to be higher, as well as we're seeing expansion into a lot of new cross-sell areas which we didn't have. We simplified the packaging as well, so we're bringing AI across all of our product portfolio, and that will drive a lot more conversations with our customers going forward as well. I think in general, just the demand is there. We're seeing a lot of adoption. We're seeing a lot of interest. I think the innovation cycle continues to grow, and we see a lot more capabilities now continue to be introduced into our portfolio, which will help our customers with their AI use cases as well.
Yeah. Touching on the, you know, some of the pricing and repackaging that you're doing. I know it's early days, and it's going to get phased over time.
Yeah
What has the customer reception been to that? Do they understand this new schema? Does it help them with that adoption friction?
Yeah, for those who are not aware, what we did, we had a product we have called Pro Plus, which is the Now Assist, the premium SKU, which was AI-driven, which we've been in the market for a couple of years. That has done very well. The pricing structure we had, which was a hybrid pricing structure, licensing based, but combination of seed, but also consumption, right? That has been in the market for some time, and we've seen customers understand that hybrid pricing structure. Gives them predictability as well as flexibility. They're not gonna get sticker shock or any kind of billing shock. Also they know what they're using, and if they're using it and seeing value, they'll renew it higher. They have predictability in that regard.
We also account for revenue upfront as well as we use that, just like any subscription. The model has worked very well. What we decided was, based on what we're seeing from our customers, to bring that same kind of structure to all of our SKUs, not just to the premium SKU. The idea is that every SKU will have some AI capabilities tiered by different functionality level. The top tier always remains most differentiated. The bottom tier will have some basic capabilities, but customers can start with AI as they choose to, and they can use the consumption model to see value and use it while we still have a licensing kind of mechanism. Given how successful we've been with Now Assist and the Pro Plus kind of combination, we are now introducing that across the product portfolio.
Also removing this nickel-and-diming way we used to structure where you had to buy every feature separately. We're bringing it together into much more structured across ServiceNow product portfolio.
Yeah.
Giving them the AI Control Tower capabilities, the experience layer, the data connectivity in this kind of a tiered structure. Every customer I've spoken to so far really like it because this gives them the ability to take AI if they choose to in all the SKUs, but they do it by consumption, so they only use it if they choose to, and they will have associated entitlements. It simplifies our go-to-market. Our sales teams can really pitch this very simply and easily, and customers can move up the tiers as they choose to based on functionality they like as well as the adoption they see value from. I think it's very well-liked so far.
Yeah.
The hybrid model has worked already. We're not experimenting with new pricing structure. It's just now adding the same pricing structure which has worked into all of our SKUs and simplifying our go-to-market as well as customer conversation. We're very excited about how this has evolved. We announced it at Knowledge, which was just a few weeks ago, which is our large customer event. Everybody seems to be feeling comfortable with the way we are thinking about this and how we will go. There's no forced migration. They can do this at renewal. The ProPlus and the Prime, which are the new version, the top version in this new structure, is equivalent, so there's no pricing change for those customers.
Yeah.
The rest will go through the license changes whenever they renew if they choose to. Customers like that message, and so far we feel good about where we are.
If we touch on the less positive aspects of AI, I think it's created a lot of confusion out there. I think you guys said in your last earnings call that customers don't know what to do. They're somewhat confused. We kind of hear the same thing. I've heard more people than usual who aren't in finance talk about terminal value risk. It's getting out into the ether a little bit and probably creating a little bit of reluctance, right? When we think about that, what does that look like? How is it impacting decision-making from your perspective? Maybe the other important piece is this an issue that's gonna persist for 3, 4, 5 quarters? Is it something that'll be resolved in a few quarters?
How should we frame it that way?
I guess maybe if I understand your question, one, there's definitely AI there's a volume of messaging or AI in the market is large.
Yeah.
Customers don't know in many cases what is real, what is not real, where to go and where to do things, who to work with and how to get going, right? That's why I think our goal always has been about talking to customers about how to get started and where to get started.
Yeah.
Right? Some of the most of the times the conversation is the use cases, what makes sense, and we are very prescriptive now than maybe a year ago about which use cases for a particular customer makes sense. We provide them POC capabilities. We provide them the FDE help, engineering capabilities as well as needed in a short amount of time, but get them the right use cases identified so they can get going. That has removed a lot of the barriers for us at least. Having said that, I think customers also are cautious about security and risk and the whole visibility as we talked about earlier. That's why I think the investment we're making with AI Control Tower again resonates. Even if they don't might want to use anything from AI from us.
Yeah
they can still use AI Control Tower to have the central control plane. Suddenly we have a conversation even if they're thinking about something else from AI perspective. Similarly, the security around devices are becoming very real because there is proliferation of physical AI and other things coming up. We now suddenly have many at-bats than probably what we had before, right? If you look at where we were at 2 years ago and where we are now, the volume of conversations we can have with a customer, we can start from so many different angles. The EmployeeWorks is a very good example as well. Any kind of conversational interface you want to provide to customers to do things across the enterprise, find information, ask for tasks or getting work done, again, we provide you an option.
Same thing with what we're doing with AI-driven omni-channel intake with CSM or FSM. I think that is really opening up a lot more senior level conversations for ServiceNow. IT always loved us. They continue to love and invest in what we're doing going beyond with autonomous AI, and other things like that.
Yeah.
Same thing with CISOs. Suddenly you have a lot of supporting structures inside the company for ServiceNow. AI, irrespective whether you use AI or not from us, there's always a product available to you.
Yeah.
Right? The AI part, I mean, again, you know, we'll see how in many years. I don't think you use large language models or frontier models for everything.
Yeah
Very costly over time probably, or some things you don't even make sense to use. We give you this flexibility and the ability to really do the right thing to run and operate your business. Eventually you want outcome, cost savings, and a lot more efficiency, and that's what we are driving towards. The idea of autonomous AI and AI specialists is that.
Yeah.
That I'm giving you an agent, the whole autonomous worker who replace a human worker at a much cheaper alternative, but guaranteed outcomes.
Yeah
instead of just having this thing do something which might not be really productive and then have to redo every time. We're trying to improve that situation with outcome-driven mindset at least.
Yeah. Let's follow that thought of, you know, the LLMs out there. We've seen a little bit of leapfrogging, right? One day ChatGPT is gonna take over everything, then it's Gemini, then it's Claude. Who knows what'll be next? What is your view on that? I mean, do you expect that cycle of the leapfrogging to continue? From the customer perspective, are they, you know, dedicating themselves to one or the other, or they just want whatever gets the job done the best?
Yeah, no, I think it's still early days. I mean, there is huge amount of leapfrogging as well as, I would say, equivalence or commoditization.
Yeah.
There's a lot of between the large language models, and we work all with all of them, and we work with a lot of open source models as well. We try to be more effective about what will give us the right result, irrespective of which one is the model. I think customers, same thing, right? Underneath, as we said, we also have a large language model in our stack. Customers get to choose, but a lot of time they just take the default.
Yeah.
Most of them don't care, right? A lot of them wanted to get a guaranteed outcome as well as secure environment. As long as we can guarantee that, we can choose and change the models underneath the covers, they would not even know or care.
most of the time. There are some who will because they might have standardized on one or something like that, or they might have a license or commit agreement which they might want to burn down. They'll be trying to do large language model trying to do something similar to what Claude do, where your commit model you can burn down different of your AR usage. Over time, I think there will be a lot more commoditization going on there as well. There'll be tiering. I would expect in some of the use cases you want to use an older or cheaper or even non-differentiated model.
Yeah.
In some very complicated use cases, you might use the most latest one. Over time it just becomes like chips.
Yeah.
I mean, you don't really care what chip you are using in your application. I think it'll be same thing in this infrastructure layer. It's going to be cost driven, less differentiation. How many times you want to keep on testing them? See what happens with every version, you have to do prompt engineering again. You have to redo your work, that's the problem I think a lot of customers are realizing when they say you want to build something completely brand new on a large language model. Every time the new version comes out, you have to retest. It's not backward compatible. It's not feature is not future-proofed. A lot of those issues we have to take away.
Yeah.
That's what we're trying to do with our software stack, is to remove that barrier of usage without customers having to deal with it. We deal with it for them. We extract it out enough, we give you the value and outcome or a solution on top of it. I expect a lot of these things to change over time.
Yeah.
Many of these model companies will start having to figure out how to solve some of those problems.
Yeah. Let's look out a few years. You guys laid out the $30 billion-$32 billion 2030 subscription revenue target. You know, a lot of pieces in that, but what people noticed was it's like, you know, high teens, 20%+ CAGR between now and then. You know, AI 30% of ACV at that same timeframe. This last quarter you guys You know, if you think about the CRPO kind of growth curve, you know, it's kind of in that high teens area as well. Kind of implies that, you know, you guys are gonna be able to sustain that level of growth, maybe even inch up a little bit between now and then. Help us kind of frame some of those components that are in them. You guys have talked about it and what gives you guys confidence?
I mean, you know, Bill obviously sounded very confident about it, but help us maybe kind of get closer to where he is maybe.
Yeah. I think at Financial Analyst Day, we wanted to lay out a plan for till 2030.
Yeah.
I think there are base cases, and I think there's a lot of upside cases here, right? We all see there's huge amount of headroom available for us to grow. What we already have, we want to make sure that at least there's a clarity in terms of where we will definitely be there.
Yeah.
The $30 billion-$32 billion is our base case, and we'll continue to focus on accelerating more of that going forward. The reason we feel very confident, one, I think our innovation cycle, the product we're building is resonating with our customers. We are still the proven and most adopted enterprise kind of workflow as well as the whole idea of bringing AI, workflow data, and security into 1 platform. I don't think anybody does that today end to end, right. We give you that confidence level for our enterprise customers and it also unlocking a lot of new things for us. I think if you look at the growth engines we have, security and risk growing at a very significant rate.
As you said, we kind of crossed $1 billion. We'll talk about where it's going, but it is 1 of the fast-growing areas. The roadmap has been accelerated. Second, if you look at data, platform, data analytics. The Workflow Data Fabric, we talked about RaptorDB, which is our Postgres HTAP database. $100 million ACV in less than a year. It's like a very fast acceleration path. This is just untapped market. It's all available to us. You add the Workflow Data Fabric, the connectivity with the Zero Copy Connectors, the data analytics and the AI platform, the data platform we're building out. That's 1 of the fastest-growing areas. We talked about 1 potentially very fast, a billion-dollar business for us.
Similarly, if you look at what CRM is. Our customer service, one of the fastest, business to billion-plus. We are on target for 2, I think, what we shared at Financial Analyst Day. That is getting continued to accelerate. We've done a lot of modern work with AI, voice, and capabilities of SFM. CPQ acquisition of Logik.ai is really driving a lot more conversation with the customers like NVIDIA and others who are using that for CPQ today. We have a large growth engines, which are all substantially invested in, innovated, differentiated, while we have a very good base platform, right? It's completely AI-driven, but also it's very deterministic in terms of it can get the work done, guaranteeing an outcome.
Our, the domain expertise in IT, HR, CRM security allows us to really go into a lot of those conversations and give us the confidence that we can really accelerate growth in each of these areas. All these technologies are pulling in more and more of our products. What you look at with ITOM, ITAM, ITSM, what we're doing with portfolio management, what we have capabilities in our enterprise architecture. I mean, it's just a, it's a source to pay. We have a very substantial capability, but it's on this 1 platform. You don't have to keep on replicating every time you want to add new features.
That's why we're able to innovate faster, which is very hard for many other vendors out there, where they have to keep on rebuilding a lot of things because they're not built on the same platform.
Yeah.
That's why we feel very bullish, about the headroom we have in front of us, and the pipeline and the customer traction is proving it out, so far. I think our base case is laid out, which we feel very confident. I think Bill mentioned at FAD that he has a lot more expectation, and I think we all know we will be there, so.
Yeah. Bill seems like he has very high expectations. Very quickly, just on CRM, you hit on it a little bit. I think the quote you guys had was you're gonna blow through $2 billion. When you're seeing success with that product, what does that look like? Are you displacing other CRM, you know, systems out there? Are you kind of coming in in areas where, you know, there's a little bit of greenfield and growing from there? What does that look like? 'Cause, you know, a lot of enterprises have pretty robust CRM solutions.
Yeah. I think CRM is a broad market. I gotta be very clear. We are the space which we have been seeing a lot of the investment we've been doing and seeing growth is customer service.
Yeah.
Which is very logical for ServiceNow.
Right.
Right. Because we are doing case management, we understand incidents, we understand issues and how you resolve it. That has driven the early growth of CRM business for us. Associated with that is field service management in terms of how you operate all the people who help you. You add layer on top of that all this complex orchestration work. Like CPQ is a very complex orchestration. It's not just asking for information. You're going to do something, which is, again, very much action-oriented, like ServiceNow has been always. Same thing with some of the things we're doing around distributions, like order management. The portfolio we build is in areas where we know we have expertise, differentiation, and the credibility and the capability building the platform.
That's why we feel very confident of blowing through $2 billion, as you heard at Financial. It's a pretty large number already in a very short amount of time. We are displacing people in some cases.
Yeah.
I think, in customer service, there are many incumbents. I think a lot of the what's happening in customer service, given that most of customer service products out there, customer has been very fragmented.
Yeah
Very old architecture. People are rethinking voice, for example. They're rethinking how omni-channel intake happens. People are not just calling people on the phone for support. They're doing it in multiple mediums. For us to build that in a platform, because AI platform is what is supporting our CSM product, is very quick.
Yeah.
Today, we have customers who now are using this multi-channel way of interacting with our systems and replacing what they had, or sometimes consolidating. The opportunity is to really modernize, make it more efficient, and get into this technology stack, which allows them to get into many more areas for customers to do much more efficiently. That's why we're displacing or interoperating in many cases.
Yeah.
It's just a modern stack that, and proven capability allowing a lot of people who are running CSM, we're also running the IT systems.
Yeah.
They're used to our platform. For them now extending that into CSM become much more natural because they're not redeploying a completely new stack. It's very easy for them to now add CSM from us or CPQ and other things like that, given it's built on the same platform.
Yeah. Very insightful. Thank you for coming here and giving us your wisdom. I think we'll all be watching ServiceNow very closely.
No, thank you all for your interest and support as well. Thank you.