The GTMnow Podcast

Inside ServiceNow’s $10B Go-to-Market Engine with Paul Fipps

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NEW: @Paul Fipps (President of Global Customer Operations at @ServiceNow) joins GTMnow to break down how ServiceNow built the customer engine behind $10B+ in revenue and 20%+ growth for five consecutive years.


From CIO at Under Armour overseeing a 300 million-member connected fitness ecosystem, to now leading global sales, customer success, field marketing, and partners at one of the most disciplined GTM organizations in enterprise software, Paul has seen what it takes to scale from both sides of the table.


In this conversation, you'll learn:

- Why complacency is a bigger threat than competition at scale

- How to detect churn long before it shows up in a report

- What a CIO cancelling 900 AI pilots tells you about where enterprise AI is actually headed

- How ServiceNow unified sales, customer success, field marketing, and partners into one GTM motion so customers never feel the org chart

- Why ServiceNow monitors customer health daily — and what signals their teams actually track

- How community became a core GTM advantage, not just a marketing channel

- How ServiceNow’s AI Control Tower governs agents across the enterprise stack

- Inside “Now on Now”: how ServiceNow generated $335M in annualized AI productivity gains using its own platform

- How integrating Claude into the GTM workflow cut account planning from days to minutes

- What DTC product thinking from Under Armour unlocked in enterprise GTM

- How ServiceNow shifted from 6-month product releases to monthly innovation cycles

- Paul’s advice for building a world-class GTM organization: put the best people in the right seats


Guest links:

Guest - LinkedIn: https://www.linkedin.com/in/paulfipps/

Guest company - LinkedIn: https://www.linkedin.com/company/servicenow/

Guest company website: https://www.servicenow.com/

Host links:

Sophie Buonassisi - LinkedIn: https://www.linkedin.com/in/sophiebuonassisi/

Sophie Buonassisi - X (Twitter): https://x.com/sophiebuona

Newsletter: https://thegtmnewsletter.substack.com


Sponsors:

HockeyStack - the AI platform that unifies GTM data to help teams convert, expand, and scale. Learn more at https://www.hockeystack.com/

Transcript available under the episode here: https://gtmnow.com/tag/podcast/

Subscribe to GTMnow for the latest episodes! https://gtmnow.com/


Highlights:

The GTMnow Podcast
The GTMnow Podcast is a weekly podcast featuring interviews with the top 1% GTM executives, VCs, and founders. Conversations reveal the unshared details behind how they have grown companies, and the go-to-market strategies responsible for shaping that growth.

Visit gtmnow.com for more episodes and other interesting content. 

SPEAKER_01

You have built one of the strongest go-to-market engines in the industry, the now past 10 billion in revenue.

SPEAKER_00

This year, our customers will perform 80 billion workflows. Imagine the trillions of dollars of value generated inside of a platform.

SPEAKER_01

Paul Phipps, president of Global Customer Operations, takes us inside ServiceNow's$10 billion go-to-market engine, responsible for over 20% growth for five consecutive years.

SPEAKER_00

At this scale and size, you're not necessarily worried about competition. You're much more focused internally around how do you make sure complacency doesn't set in.

SPEAKER_01

You actually own the entire customer lifecycle. Bringing sales, success, field ops, and partners together. Why unify these teams? He also shares how 900 AI pilots got killed.

SPEAKER_00

900 different AI pilots that are not governed. His only choice was to cancel those pilots because the security and governance threat was too large and it outweighed the benefit of the innovation that those may have brought.

SPEAKER_01

How does ServiceNow, such a large-scale organization, make the shift to be AI native?

SPEAKER_00

In this case, what we did was Paul, welcome to DGM Now. Hi, Sophie. Great to be here with you.

SPEAKER_01

Paul, you run global sales, customer success, field marketing at ServiceNow, a public company powering more than 80 billion workflows and now past 10 billion in revenue. So to start with, at that kind of scale, what gets much harder than people expect and what actually kind of gets easier?

SPEAKER_00

Yeah, you know, Sophie, we've been growing, you know, 20 plus percent since I joined ServiceNow, so which is five years ago. And so you can imagine the compounded growth rate there. And then all the teammates that come in when you're actually growing that fast who actually want to help. And so I think at this scale and size, you're not necessarily worried about and focused as much externally on things like competition. You're much more focused internally around how do you make sure complacency doesn't set in? How do you make sure that when all those fantastic people that you've recruited to do amazing jobs are really focused on the core mission of the company? And I think you have to constantly look out for as you scale and grow. And we've seen that, you know, uh at ServiceNow over the past five years, our teams keeping them focused on the customer in a very organized and methodical go-to-market motion, making sure that at the end of the day, we're making customers the hero of their own story. I think if you do that, that tends to get everybody oriented on the right things. And, you know, that gets harder. Now, what gets easier is at scale, you also see all kinds of industries and all kinds of customer segments at every single level. And so their challenges and their opportunities and also the trends inside that industry get easier to spot. So the pattern recognition becomes easier. So you can actually make sure that all the net new innovation coming from the product actually fits with where the customer is today, but also where she or he is going.

SPEAKER_01

Makes sense. And one thing you mentioned that actually gets harder is focusing on the customer internally versus competitors. And so this focus on the customer itself versus any competition, is that something that you feel like is earned at scale, or is that something that startups in earlier stage companies should actually apply earlier?

SPEAKER_00

If you start with a customer centricity approach, and I would say most startups that I've engaged with or been involved with or even spoken to, they're identifying unique needs, you know, with those customers in that market, which can be niche and small, but really powerful use cases. And they're building great companies on top of that. So I think that it's making sure that stays the North Star as you get bigger and as you grow in scale. And so I think, yeah, I think I think that that's whether you're a two-person startup or whether you're a 30,000-person company. Now, that gets harder because again, you have people coming in from other cultures and other other industries and other organizations. But at ServiceNow, we have focused on our core values, which is actually the fabric of our culture here. And one of those core values is wow, our customers. If you actually click below that, it really means end-to-end, Sophie. How are we making that customer the hero of their own story? And when you think like that, everything that you do then becomes customer-oriented and customer-centric.

SPEAKER_01

I mean, we at GTM Fun, we're constantly engaging with many, many startups. And I know you're you're actively involved with startups also. And a big shift that we're actually seeing now that we're in the AI era is a less, a lesser focus on competitors. Because what we're seeing, at least from our lens, is now your go-to-market motion is so unique. It's so different because you've got so much more data and context that makes your go-to-market able to scale individually, as opposed to having more of this cookie-cutter approach where everyone had the same signals, everyone had the same data. So you were transferring and so you're really competing in the same go-to-market kind of box and configuration, whereas now it is quite unique and different. And that just enables people to have that customer centricity at greater scale or earlier and earlier now.

SPEAKER_00

It's a great point, Sophie. And what we see is, I mean, AI had moved the needle on everything at this point, you know, externally, internally. But inside our customers, what they're really challenged with is figuring out what are the AI use cases that drive hard return on investment? What are the AI use cases that can actually drive complete differentiation in their existing business models? And then what are the AI use cases that can actually create new business models for those customers depending upon their industry and where strategically they want to go? And so I think that is the unique part about go to market now is really fitting into that customer in those three areas and understanding in depth what their biggest challenges are.

SPEAKER_01

And one thing that stands out about your role in particular is that you actually own the entire customer lifecycle. And bringing sales, success, field ops, and partners together at that scale isn't necessarily common. We see it sometimes at the earlier stages, but often there's a bifurcation. So why unify these teams?

SPEAKER_00

Well, it comes back to that customer obsession. You know, a lot of companies talk about customer obsession or customer centricity, but at ServiceNow, we actually are organized around the customer and we don't want them to feel our organizational chart. That's the worst thing you can do as a customer. But I'll give you some examples. Let's take large-scale transformational work that we do with customers, and we do that every day, and our teams globally do that. You may spend six, nine, three, pick the amount of months of investment and time together deeply understanding and identifying the challenges, the business value of those challenges, how your solution is going to map to the map to those challenges, and what the ultimate outcomes are are going to be achieved, going through the process of approvals and large capital allocation. And when you do all of that work, all that work then should be translated into actual action. So the post-sale part of that journey is really important. You know, I used to be a practitioner, Sophie, and in the days where I was a CIO, it would really upset me when I'd work very closely with a technology company, a technology partner. We'd go through that journey, I'd sign a contract on Friday, and then Monday morning, a new team would show up and say, Great, what are we doing now? And I would think, what? We just went through all of this process work. So having that seamless, frictionless experience from the pre-sale to the post-sale, so that really you're starting with the end in mind and making sure that customer achieves the outcomes and the return on investment that they made in the first place. So that that is why we have all together. I think the last part I would say is you know, we have one of the most robust partner ecosystems in the world. We're very honored by that. Our partners are part of our team along that entire journey. And so making sure that that frictionless experience applies to our partner ecosystem as well is super important. So in ServiceNow, we're organized with worldwide sales. We obviously have our partner ecosystem, and then our customer success team, which helps helps customers adopt the software, but also implement either with ServiceNow or with a front from our ecosystem.

SPEAKER_01

I love the point of customers not actually feeling the organizational design. Makes for a much more seamless experience. And if you think about just that line itself, that really guides how you how you structure, how you run the organization, everything kind of as a North Star.

SPEAKER_00

Absolutely.

SPEAKER_01

And now, I mean, a lot of companies realize that there's problems with the customer far too late. It's much more reactive than proactive, and they'll see it through turn in reports. And that's that's just far too late. So from your vantage point, like what are those early signals that tell you a customer relationship is is quietly starting to, you know, fail or disintegrate long before the reactive turn actually shows up?

SPEAKER_00

From our perspective, having close and deep relationships with our customers is super important. And we all know what a happy customer looks like. They're pulling you into new use cases, they're leveraging, in our case, the ServiceNow platform to drive more and more value for their existing investment. I think one of the early warning measurements is adoption. So is a customer actually adopting your software for the job they hired it to do? If that is true, then they're getting the return on investment because if you've done all the business case right, increased adoption should actually drive increased value for your customers. So you can measure and monitor that from a data and a dashboard standpoint. But I think the trust part of that relationship is really important. You know, many customers, and we talk about this all the time at ServiceNow, they may be betting parts of their career on the investment they're making in the platform. And so we have to make sure that that trust that we've earned is never lost. And that means relationships up across the entirety of the journey for the customer. So I think one is you have some early warning sides and dashboards. In our case, we we look at adoption almost weekly. Uh, many of our teams are looking at it daily, actually. But we also then the relationships that we build with customers, and particularly with those large transformational projects, making sure they're successful throughout. When they start to disengage or not show up for meetings, or they don't come to the quarterly business reviews, or there's something happening there that you need to really get under the hood on. So there's a human element, and then there's obviously a data element, and you need to combine those two to make sure you have healthy customer relationships, which is all about value for them.

SPEAKER_01

And you mentioned daily for some teams, when you're combining that qualitative and quantitative data to best understand where the customer stands, how often is that done?

SPEAKER_00

If you're a team on the ground, you know, we have a product called ServiceNow Impact, for example, Sophie, which is a customer success product that many of our customers invest in. You have a combination of technology, but you also have highly skilled people to help you along the transformation journey. So if you're one of those team members, you're actively engaged with a customer and looking at that data every single day because it's it's really telling you what the health of that customer is. If you're you know at a more senior level, you know, we have rhythms inside the company that are looking at these things every single week to make sure are the implementations going well for customers, are they adopting software? Where are the escalations happening and the entirety of their experience with ServiceNow? And whenever you see something happen, those escalations happen fast, and I look at them every single week.

SPEAKER_01

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SPEAKER_00

I mean, from our perspective, we have so many customer touch points, Sophie, you know, and we we orchestrate them really well and we try to engage with customers at different moments. So I'll give you an example. One of our more key events is our knowledge 2020, knowledge 2026 this year, K26 is what we're calling it, but it's our knowledge event. We'll have 22,000 customers in person, engaging with products, engaging with our teams, engaging with each other, most importantly. So I think an active and thriving community around your products and around your company is really important. And it's a and it's a macro measurement of what the relationship is you have. But it's also a measurement of are you driving enough interest through innovation that actually gets customers to come to those events so they can learn more, so they can think about both how they solve their existing problems, but what are the future challenges that companies or customers like them have? How can they leverage service now to actually solve those challenges? So I think a healthy, thriving community is what you have to build inside of the company because these challenges are complex, but they're not necessarily unique. And so when you have customers who are like each other really deeply engaging in those challenges, and they're coming up with new and innovative ways to solve those problems, leveraging Service Now, it also gives us insight in terms of how to generate new and innovative capabilities inside the platform. So I think that's really there's a qualitative metric of engaging customers. That's just one. We do we also do world forums across the globe, which are smaller knowledge type events. We have a whole community of now customers who actually engage with each other uh online through portals. So I really believe in a healthy, thriving community. You know, I used to years ago, Sophie, I was on the board of directors for the America SAP user group, and it just gave me insight. We had 150,000 members. Now, this is going back probably 15 years ago or so, but we had 150,000 members who were actively engaged solving problems at that time around leveraging the ERP system and the integration and all the things that all the opportunities and challenges that came with that. So just really opened my eyes up to the power of community and uh and being able to measure that from a company standpoint based on where that community is.

SPEAKER_01

Love it. And it is hard to measure, but it's definitely one that at least we're seeing emulated across the startup landscape, is really leaning into the knowledge side. And ServiceNow has really paved the way at scale of doing this incredibly well because it is this interesting period where everybody's at a reset and everybody's kind of learning a first principles approach to AI together. So being able to not only educate on the product itself, like you mentioned, the actual industry, what's the future look like? We're just seeing tremendous success.

SPEAKER_00

And you know what's interesting, Sophie, is when you actually get in there with customers and you start to engage them, they're gonna pull you into more use cases. But one of the things I always tell the teams is as you scale and get big, one thing that can happen is you do a lot of talking internally, a lot of talking to each other, a lot of meetings, a lot of presentations, and your best time is spent talking to customers. And so, even like even someone like me, I take a percentage of my calendar every single week and allocate as much as possible to meeting with customers one-on-one. And so it just gives me real perspective, what's happening on the ground. And the first question I always ask is, how are we doing for you? And, you know, they're gonna tell me exactly how they're feeling about the relationship, about the product, about the outcomes, about the capabilities. And then it's our job to respond to that as fast as possible. And we do that always within 24 hours.

SPEAKER_01

Within 24 hours is an incredible turnaround for such bespoke asks, I'm sure. And the challenge that we hear is actually taking that data and feedback at scale and putting it into almost a central repo so that it can inform your roadmap. When Paul is sitting on some customer calls, and then we've got other individuals on customer calls too, and other execs, how are you actually bringing that data together to best inform the roadmap, not only for that bespoke customer, but for your whole customer base?

SPEAKER_00

Yeah, it's a great question. You know, again, now this is the benefit of scale. We actually have experts in the company who are customer advocates who can actually synthesize that data, particularly when executives are meeting. Because I think what you're pointing out here, Sophie, is we can go from one meeting to the next and lose some of that intelligence, which would be really, I think, a missed opportunity, and also an unmet customer expectation. So we harness and capture that information across the advocates, and then they centralize that intelligence. We feed that into our customer intelligence group that does two things. One, they do all of the NPS measurement externally every single, they actually do it twice a year. We take all of that feedback, but then you combine the more qualitative intelligence based on those meetings and you bring that together so you actually have as much real-time information from customers on the ground as possible. We also capture all that sentiment. Our marketing team does an amazing job with all the events that we have around the sentiment, particularly around parts of the platform, but also in other areas around success, around support, how we're actually serving those customers.

SPEAKER_01

That's fantastic. I mean, a model that I'm sure many companies want to emulate too, as they're typically running this in some kind of customer success and RevOps combination, but it really is what's the feedback loop at the end of the day and how quickly can you execute against it? That's right. Now, Paul, I want to zoom out on yourself because before ServiceNow, you were actually at Under Armour. You joined in 2014 and spent over seven years there. And it's a very different environment from enterprise software. So in the D2C world, customer feedback is fairly immediate usually. But in B2B, it's oftentimes slower, like we talked about. We're going through systems and customer intelligence groups. It's much more complex oftentimes and is filtered through multiple stakeholders. So, what's one kind of D2C direct and consumer practice that you've really internalized and brought to service now?

SPEAKER_00

So I was at Onar for seven years, great brand. And during that time, we were growing so fast, Sophie. I had many different roles while I was there. I was very privileged to work for the founder and CEO, who, even to this day, I think has some of the greatest insights around brand and consumer and product. And so we spent a lot of time thinking about consumer experiences, but but building them based on the actual problems. And in 2015, we actually acquired a company called Map My Fitness, and then the following year, a company called My FitnessPal. So I was privileged to lead what we call Under Armour Connected Fitness, which was, you know, at one point we had 300 million people who had downloaded one of our apps globally. We had the largest health and fitness ecosystem in the world. And I share that with you only because we then could use that for intelligent insights around what challenges or problems were athletes having that we wanted to go solve. One of them was, you know, this constant conversation kept coming up around how do I run. Now, many of us would think that running is natural and you know, we're kind of born to do it, and we should all just naturally be great runners. The reality is it's not true. And so we spent a lot of time figuring out what are the what are the simplest ways for us to create solutions to help our athletes and coach them into better running form. Because if you're in a better running form, running actually becomes easier and you actually get better at it as you're more conditioned. And what we learned from those insights and inside of the Underarm Connected Fitness Ecosystem was that cadence and stride length were the two most important things around running. So we then built uh a chip into the shoe. That chip then was connected to MapIFitness, and we used machine learning to actually coach you into better running form over time because we could measure your stride length and your cadence through the shoe, feed that back into the app. That app then could personalize, give you personalized coaching insights to actually most people need to shorten their stride length and pick up their cadence. And so you can measure those things in real time while you ran. I share that with you because that product became very successful, the shoe and connected to Map My Fitness as an app. And so we called it, you know, um, this connected shoe experience that actually gave you a better outcome as a runner and it took off. Now, the insight came from the data and lots of those community members posting information about how they ran and giving each other insights in terms of what was making them better. And so I, but it was not necessarily an articulated need when we were developing footwear products as an example. So I think bringing those insights into that experience, into those product development really made that shoe and uh that entire experience very successful. So inside of B2B, I find two things when I joined. One, there's not a lot of personalized engagement in a B2B enterprise software company. And the reality is if you're a buyer, and I spent a lot of my life buying software, you're an individual with unique needs, just like when you're a consumer, whether you're buying enterprise software or you're buying, in this case, a connected shoe. So bringing those insights into service now and really helping helping the teams think about how do you engage uh Sophie as an individual in a B2B enterprise, not just sales motion, but actually solving her problems based on where she is, you know, in her persona, in her company, in her industry. And that's a unique thing. And I will tell you, we are still working that out because traditionally that's not how B2B sales models work, but we've got A lot of progress with some of our products, engaging those customers in unique and personalized ways. That then brings up those unarticulated needs that I was talking about, and you start creating products that wow the customer because you're thinking about steps three, four, and five, not just steps one and two. So that's the insights from that industry. It was a great experience at Under Armour. And uh it's also been great to see some of that, not as much as I like yet, but some of that translate inside of ServiceNow.

SPEAKER_01

What are the blockers to actually translating on the B2B side?

SPEAKER_00

Well, you know, most people who work at ServiceNow or any other enterprise software company come from enterprise software. Yeah. So, you know, and so there's a method and a way that it's always worked. And and and by the way, they're complete professionals and they've built careers that are amazing. And these things really do work in B2B. But I think as the world changes, I think, you know, you and I started talking about artificial intelligence at the beginning of this. I think the expectations of a B2B consumer are changing as rapidly as a B2C consumer. And so we have to be there for them at those moments. So I think we're evolving rapidly. We've done some really great things, but we have a lot of work to do there.

SPEAKER_01

Well, now with so much more data too at our disposal, we can actually do those personalized experiences that we couldn't before. So I think we'll actually see a lot more B2B companies hiring leaders like yourself on the D2C side because that's truly best and breed from a customer experience and like really infusing those knowledge and and perspectives on the B2B side quickly.

SPEAKER_00

I agree. And I've actually done it here. I've brought some leaders also from those from those spaces. And what's great is you have the enterprise B2B experts combined with some of those D2C experts. And when you put those together, the ideas just explode, Sophie. So it's really, you know, building a team that has different perspectives and and has different experiences really does lead to better outcomes.

SPEAKER_01

So interesting what you said on the running side too. Just a few months ago, I ran my first marathon. And I gotta say, the technique was something that I did not anticipate as heavily. Because when you actually are running consistently in a fair amount, you start to feel in different parts of your body. And then you realize just the minute changes of like where your actual foot is making contact with the ground or what shoes you're wearing, or any small detail can just make such a difference on the actual motion of running. So that was uh an eye-opener. Did you get into running yourself when you were testing the product?

SPEAKER_00

I do run, Sophie, but I don't run 26.2 miles.

SPEAKER_01

So that's probably for the best. I wouldn't recommend it to everyone. Cool. I mean, we talked about AI at the beginning a little bit more, and you just mentioned it. So everybody is talking about AI, inevitably, but some teams are really stuck in pilots, you know, the whole narrative and discussion around experimental revenue and actual ARR. So, from your seat, like what separates the teams that are really converting this experimental pilot revenue into paid and shifting that revenue to true ARR?

SPEAKER_00

Well, let me talk about it from a Service Now perspective, Sophie, because obviously that's that's where I'm closest. Please. I I actually had a CIO of one of the largest healthcare companies right before the holidays. He and I were talking and he said, listen, I have 900 AI pilots happening inside my organization, and I am killing them all. And the reason he was that at that moment is because if you think about a regulated industry like healthcare and you know, 900 different AI pilots that are not governed, that are not necessarily secure, that come from different software companies or different, you know, probably really innovative use cases. But from his lens, how does he actually govern and manage those 900 pilots? So his only choice was to cancel those pilots because the security and governance threat was too large. Uh and it and it outweighed the benefit of something like the innovation that those may have brought and put a whole new process in where we can actually leverage uh a platform like ServiceNow to actually govern all those AI capabilities across multiple systems. So one is we are seeing customers who started off very rapidly doing pilots start to actually take a different approach, particularly in larger companies, and I would say increasingly in regulated industries, which makes total sense, right? I mean, if you're if you're in financial services or if you're in healthcare, uh you just have, or public sector, you just have different requirements and different governance models. So that's one is I we're just starting to see that happen. I think two is a lot of customers are at that hype cycle moment where they're just not seeing the return on investment around AI. And so inside of ServiceNow, what we've done, and we've been at this, you know, we launched our first generative AI features uh 10 months after Chat GPT, you know, kind of lost in late 2022. And the idea was now we're full agency, obviously, on the platform, but we've evolved rapidly with our customers. You have to have AI inside of where the work is happening. And so I'll give you just some data points from a Service Now standpoint. Today or this year, our customers will perform, start to finish, 80 billion workflows inside the ServiceNow platform. So you can imagine the trillions of dollars of value generated by 80 billion workflows inside of a platform. And so when you then take agentic capabilities and put it inside the workflows, whether it's on technology or employee experience or customer experience, what happens is now you have this opportunity to pick and choose which of those workflows need to be autonomized through agentic. And so uh you can pick the highest value and ROI use cases so that your investment actually pays off and has hard ROI. You can also pick and choose which tasks you want humans to do and which workflows you want uh, in our case, the agentic AI to do. So I think there is just this evolution of, you know, we've gone through this moment, there's lots of capabilities out there, and now it is how do I actually drive real return on investment from the AI capabilities? So I think that's a really important point of where customers are today. And the way we see it at ServiceNow is look, we've got 20 years of integrating systems across, you know, uh across the board. We we find customers today have this, I would say on average, but this is a small average, 367 systems inside their landscape. So imagine, Sophie, how much swivel chairing is happening between if you're in procurement operations or if you're in human resources or if you're in any function, how many different systems. When we measure it, uh, typically people are using about 17 different systems, what we call swivel chair work to get their jobs done every single day. So always the ServiceNow platform has been one that cuts across all of those ERP, human capital management, customer relationship management. And now all that data is in one place. Either you've left it in your data lake or you actually bought into ServiceNow, and you can use intelligent workflows to autonomize across those systems your core business processes. So it's dramatically different in how we think about it. But I think that's important because as other companies innovate on leveraging large language models and all the great capabilities out there, it's thinking about from a customer lens how do they actually drive hard return on investment. I think it's why you see coding going so fast because you know, uh, those software developers and engineers are really getting exponential productivity growth, which has real return on investment. In our case, it is autonomizing the workflows that you already have and the ones you want to do in the future with the more complex business processes that drive real return on investment for you.

SPEAKER_01

You are truly at the forefront in seeing so many different companies adopt AI. And you yourself, you've adopted AI too, but really you were ahead of the game. So your first, like you said, you your first launch was actually shortly after Chat GPT launched. How does ServiceNow, such a large-scale organization, make the shift to be AI native and AI first?

SPEAKER_00

Yeah, it's one thing I love about ServiceNow. It's one of our other core values, Sophie, is win as a team. Okay. And so when a challenge like that arises, you see a company like ours, even at our size and scale, rapidly get some of the smartest and I would say most motivated people, you know, organized and energized around a topic. In this case, what we did was, you know, later that year, we created what we call the AI Lighthouse Program. It was actually a partnership with NVIDIA and one of our large GSIs that we launched. And we took those capabilities to some of our largest customers to solve the immediate problems leveraging generative AI. So very early days, this is this is probably August, September of 2023. And we learned enormous amounts from that. Like we really, those lighthouse customers in the early days, we had 15, we had across multiple industries, very large companies, some smaller companies, but we learned a tremendous amount that then fed back to our product roadmap and our engineering and product teams took very rapidly, started to iterate and innovate. And what that led to was, you know, up until that point, we had a pretty good cadence, which I think for an enterprise software company is great. Every six months we would launch a new version and upgrade to Service Now. That would have 150 to 200 to 250 points of innovation. So if you think about a customer, you can go to the next version. Somewhere in the platform, you have 150 to 250 points of innovation. We are now innovating uh in monthly cycles, so if we inside the platform. So you just think about uh less than three years, what's happened in terms of really shrinking that time to innovation and how many new capabilities we're rolling out for customers now every single month.

SPEAKER_01

That is truly incredible. And I've seen firsthand, I mean, companies, I'm sure you have too, but like truly dying, if you will, by not being ahead of that and the cycles of the time to be ahead of that required a lot of foresight and belief in AI. So that's fantastic that ServiceNow made that shift. And, you know, you're enabling teams, you're adopting AI at such a rapid rate, but you're also internalizing it in your commercial engine, your go-to-market engine. Like you recently shared that the company is seeing roughly, I believe, 335 million in annualized revenue value from its own use of agentic AI. What have been the most impactful internal use cases so far?

SPEAKER_00

We obviously, Sophie, uh at ServiceNow, we actually use our software to run ServiceNow. We actually call it it's a brand new program called Now On Now. Love it. And it covers everything from how we actually hire new teammates to join ServiceNow and how we onboard them is, by the way, now completely agentified. We have no level one help desk anymore at ServiceNow. So all of our level one tasks from a technology standpoint are taken care of by by ServiceNow agents. So all of the things that it takes to run a large company inside of ServiceNow, we are leveraging the agentic capabilities that I was talking about to autonomize that work. And what's that's what that has done is it's allowing us to grow at our scale and size, maintain our headcount in certain parts of the organization outside, and then reinvest those headcounts where we want to actually grow. It also gets rid of work that people don't want to do, the stuff that we call soul crushing work inside of ServiceNow, and our customers have it as well. And so eliminating that work, freeing up people to really do the higher level tasks inside of their functions or inside of their daily activities has been a huge unlock for ServiceNow. So you see a lot of that$335 million of just pure productivity gains. Now, in a go-to-market, from a go-to-market standpoint, what we've done is we actually partnered with Claude Anthropic recently. We brought Claude in and we actually integrated it with our own ServiceNow AI agents. And so from a pure go-to-market standpoint, we have all 10,000 people in the go-to-market organization, which includes our success, our customer success teams, have access to this to actually engage customers in a different way. And I talked earlier about the faster innovation cycle coming from the product organization. We can't have a natural enablement cycle inside of the go-to-market organization. We have to get those innovations out faster so our customers understand the value that those innovations will create. And this new what we call the AI, the Service Now AI sales coach does all of that work. So you can now go and do account plans that used to take hours, if not days, and do them in minutes. You can actually get the latest innovations and how they're actually solve problems with a business value assessment done. And so customers can move faster inside the platform because they're aware of these capabilities, but also can figure out how they're actually driving ROI. So we're using it to drive productivity across the ServiceNow platform. We're also using it to drive not just productivity, but the way that we engage customers in a different way to get those net new innovations out inside the go-to-market.

SPEAKER_01

That is incredible. And we can see the impact in the revenue. ServiceNow recently released its Q4 and full year financial results significantly beating expectations and exceeding top line growth. With this momentum behind you, can you share what's next for ServiceNow?

SPEAKER_00

I think, you know, we uh we just had our sales kick off, Sophie. So we did that in uh Las Vegas. We had everyone there. It was amazing. The team did an incredible job. And I think what we're what we're really excited about are a couple of different areas. The first is those 80 billion workflows that are that we're we're honored and privileged that our customers actually complete every single year through the platform. We want to help them autonomize those workflows. Okay, so that's one. We think the productivity gains there will be exponential, leveraging both out-of-the-box use cases, but also more custom use cases where our customers have more complex uh challenges. So that's that's one thing that we're very excited about. And we think 2026 is the year to do that. The second thing is what we call the AI control tower. If you really think about AI agents and you think about them as you know assets to be managed, whether you have agents in your CRM system or in your ERP system or in your uh uh HCM system, those things may be doing purpose-built work inside those islands of automation. But if you're a CIO or CDO or CTO or a CISO, you need to actually see across all of your agents inside of your organization, even the custom ones that you create. And so how do you govern those agents? How do you make sure they're secure? And by the way, how do you actually make sure they're performing and performing uh based on what you expect them to do to drive the actual ROI that you expected in the first place? So we have what we call the ServiceNow AI control tower. It because we already do those integrations, we can actually surface those agents and give you a view by function or by business area, what's happening in your entire organization. And I think we're the only ones that can do that at this point. So that's so the ServiceNow AI control tower is super important for us, and we're very excited about it. It actually that business is growing very, very rapidly for us because of the obvious uh implications. And then the third thing I would say, you know, listen, we we made uh we we announced three different acquisitions at the end of 2025. One is MoveWorks. Moveworks is now complete and in the house. The demand for MoveWorks is incredible. Bobin, who's the CEO of MoveWorks in that team, fully part of the ServiceNow family. And what we're seeing is what they do really well is the what we call the front door. So the the AI experience from a from a user interface standpoint, this conversational AI that can then deeply integrate with the ServiceNow platform is exploding. So we're super excited about MoveWorks. And then you know, we've expanded our security business. Uh, our security and risk risk business has been growing exponentially over the past couple of years. And we expanded that with an acquisition with Besa and an acquisition of a company called Armist, which we are incredibly excited about. So if you think about ServiceNow, you think about the ServiceNow AI control tower for what we call business reinvention. Those are the workflows I talked about, but also the ServiceNow capability around governance and security as we extend out. So that is what we are excited about in 2026, and I think that's what's next for us.

SPEAKER_01

Amazing. Well, it sounds like it's already forward-looking, similar to your speed of adoption of AI, because we've been in this adoption phase of AI in 2025. We're continuing into it in 2026. But really, what's next then is the measurement phase. And it sounds like that's already on your roadmap ahead of time. I love it. Paul, to bring this full circle, you have built one of the strongest go-to-market engines in the industry for this era. If you had to leave listeners with one piece of advice around company building and go-to-market, what would that be?

SPEAKER_00

I think the best piece of advice, Sophie, is it it's it's tried and true, but it is about getting the best people and putting them in the right seats. And that's from every leadership level to frontline salespeople. And and the best people are gonna fit within your culture. The best people are going to be energized around the customer, and the best people are increasingly going to want to, they're gonna be intellectually curious around the technology. You know, from a sales standpoint, increasingly the sale is more technical. But great client executives, great account directors, great whatever you call them on the front line, they're always incredibly curious about where the technology is going and how it helps customers solve problems. And you need leaders that think that way all the way up. And when you have the right team in place, I don't think no matter what happens externally, no matter how fast the change is happening, those teams can move really fast, adopt, and change, and make sure our customers are taken care of and they're successful.

SPEAKER_01

Brilliant. People first always. And one last, last question is are there any books that have made a particular impact on your career?

SPEAKER_00

I get asked this question a lot. I like to read a lot, Sophie, but the one that always comes to mind around impacting my career is uh is an older book called Execution. It was written by Larry Bossity and Ram Schuran. I highly recommend uh everyone reads that. And the reason is it ties strategy to operations to finance to outcomes. And it just does it in a really methodical way.

SPEAKER_01

That's fantastic. And I find some of the best resources that leaders are actually recommending are the tried and true things that do not change with AI. They're the fundamental principles, just like that. That's right. Well, Paul, appreciate the time. Thank you. It's been wonderful picking your brain.

SPEAKER_00

Thank you, Sophie. Great to see you.

SPEAKER_01

Great to see you too.