ServiceNow, Inc. (NOW) Earnings Call Transcript & Summary

Welcome to ServiceNow's Financial Analyst Day 2025. Thank you for joining us today. Before we begin, I want to remind everyone that today's event will be webcast and recorded for future playback. Information pertaining to our forward-looking statements and a reconciliation of our GAAP and non-GAAP results are available on our Investor Relations website at investors.servicenow.com. As you can see, we have an exciting agenda for you all. Bill will kick us off and discuss our vision and opportunity. Amit and team will cover all of our amazing platform innovation and how ServiceNow was made for the Agentic age. We will have a short break. Then Chris will show AI value in action, and Paul will explain our go-to-market strategy to capture the massive opportunity in front of us. Finally, Gina will highlight how all of that flows through to our financials. So with that, let's get started. [Presentation]

Please welcome Chairman and Chief Executive Officer - ServiceNow, Bill McDermott and Vice Chair - ServiceNow, Nick Tzitzon.

Well, good afternoon. Welcome to Financial Analyst Day 2025. I hope you enjoyed the lunch. Bill, did you know that Darren Yip and the Investor Relations team actually made that lunch?

He did?

No, he did not. He obviously didn't do the safe harbor statement either. I'm not sure what Darren is doing today. But it's nice to see everybody. I thought maybe before we get to the content, you want to welcome everybody as well.

Well, I'd like to warmly welcome you to Las Vegas. Good afternoon. Also, really appreciate our Board members that have come today: Sue Bostrom, Teresa Briggs, Anita Sands and Larry Quinlan, thank you so much. I'm super proud of the trust and the transparency we built together the financial community, the management team of ServiceNow. It's really a great, great moment for us as a company. And hopefully, you see that as investors also. You're going to have a great day to day of wonderful presentations. You'll see how this team is really scaling, and I'll be back up later after they're all done to take your questions and get your feedback. So let's get it roll in, Nick.

Sounds good. Well, Bill, like you said, there'll be a lot of presentations today. I mean you could say from any number of different dimensions that we're entering this period of ServiceNow in a position of strength. And I know that you're now -- you made on those in your sixth year as CEO. When you think about the foundation that's been built and some of the metrics reflected here, what comes to mind for you in terms of how this has been orchestrated to date?

Well, I think da Vinci had it right that the ultimate form of sophistication is simplicity itself. And I came in here with a very clear dream and that was to help make ServiceNow the defining enterprise software company of the 21st century, what we affectionately call DESCO21C. And to do that, we had to set goals and have action plans and hold people accountable for delivering. And I'm very pleased to inform you that we've done that. We're building great products, and you're going to get an unbelievable overview of those products today. We're focused on providing a great service, presale, sale, post-sale, incredible expansion of the ServiceNow ecosystem. We're telling a great story. You saw Idris Elba, our amazing brand ambassador, take us to every corner of the office. And it's all built on a once-in-a-generation culture. We really have something magic going on at ServiceNow and a team that I could not be more proud of. And I hope when you see them present today, you'll get really inside of just how good they are. And ultimately, Nick, metrics do tell the story. We are our record. And of all the things I'm most proud of, it's Fortune's and Forbes' most trusted. In fact, Forbes rated us as the #2 most trusted company in the world behind only NVIDIA. And when you think of the relationship that we have with NVIDIA and Jensen, I'm okay living in that neighborhood, man.

We'll take that house. We'll unpack a lot of these over the course, not just at today's Financial Analyst Day, but obviously, Knowledge '25, which will be our biggest ever. So...

Yes, I think we're up to about 25,000 now and millions online. So we're really scaling the brand, the story, and that's because this is a platform like no other.

So one of those presentations that you referenced will obviously be Gina, who will be coming in as President and CFO. And let's hover on the financial performance for a second. I think most people in this room would remember the beginning of the Russian invasion into Ukraine and the corresponding impact on the macro environment, a lot of high-performing software companies sort of came to religion at that point on profitability and leverage. That's not something that ServiceNow had to learn because we were practicing that approach to the entire time. So when you see this how do you characterize what we've done to get this right?

Well, it was also important at that time that we had a no layoff pledge with our employees because we knew we hired with tremendous intentionality in the first place. And no matter what shock wave came our way, we would need the great people on the other side. And now we're up to 1.7 million people that are applying to ServiceNow annually. So it's really hard to get in here. And the other thing I think is super important is now on now. We drink our own champagne before we bring it into the marketplace. And we found all the jobs that our technology can do in every corner of the office. And that's why we're able to absorb tremendous growth and still give the leverage and the free cash flow margin that our shareholders truly appreciate. We know how important it is to do both. And so today, when you see this management team, I'm really, really proud of them. Amit has brought tremendous, tremendous engineering prowess to our company, and his team is lined up with him, and you'll see them present today. It's really beautiful. Paul Fipps and I know each other for more than 15 years. I was one of the first Board Members with a company called Under Armour and my friend, Kevin Plank, when I was Paul's mentor when he got hired into Under Armour, I just saw him doing an unbelievable job. And needless to say, Gina, shortly after I came into the company, we also hired Gina into the company, and I couldn't be prouder of the job that she is doing really scaling beautifully. And these people are extremely close with me with each other, with our Board and with the customer, and that's what we want. So Nick, what you're seeing here is 3 growth factors coming together. One is the core business. The core of the core, every great company has to have a great core business. As I told the Board when we first started this discussion, you're right, 6 years ago now -- it's time flies -- that we would expand the perimeter of what ServiceNow was capable of and we would build a once-in-a-generation platform. And recently, we added on data and we more than doubled our TAM with RaptorDB and the Workflow Data Fabric maneuver. So now companies can integrate those systems of record. They can integrate any data source, any hyperscaler cloud and any LLM into the ServiceNow platform. So I really like our positioning. The TAM keeps expanding. It's growing by the day, and we're just innovating at a pace I don't think any other company can match.

So we'll let Amit and the team do a lot of work on the platform. But I do want to play back one thing you said in our most recent earnings process that we were built for this moment. And again, I think speaking of everybody in the room, there's not a day that goes by where you're not reading about something that has the potential to be a disruption in the macro environment. What did you mean by built for this moment? And why does it say that we'll ultimately see the circumstances as a tailwind and not as a headwind?

Well, first, this is not our first macro disruption. We've been through many of them, and we really don't get shook up about it. I take it more as a weather report, then I do something we should be a little shock up about. So we're cool, calm and collected. And history shows in enterprise software, the platforms that matter, always come out of disruptions stronger on the other side. And I think that has never been more true than it is right now. I was speaking with the CEO of one of the world's largest and most successful companies the other day, and he said something very important. He said, "Bill, I need your platform to manage my OpEx and my margin profile and I appreciate that. "I need your platform to help me grow and institute new business model innovation and to meet my competition head on, I have to do both of these things in tandem." But more importantly than anything, he came to the realization that he's in a moment where change is coming at him so fast that speed is actually his most important weapon. And so his inclination was simply tell me what you can do that I can't do, and I want it because I want to move fast. So these CEOs that are running really important companies know that speed is everything right now. And so when I tell you we integrate with the entire stack, we took all of the objections off the table to bring in ServiceNow in as the central nervous system of company. And so think about this. You integrate with any system of record. Then you move any data into a workflow where you're automating things across all business processes. But then you apply Agentic AI, not fake silo agents that are going to a dead-end street doing U-turns, real agentic AI agents that are reinventing business processes and how companies run. So this is the AI layer. This is the real AI agent company. And when customers hear that, it clicks. It just makes sense. So we feel fantastic about the platform. And I think today, you'll see some illustrations that you'd be blown away by.

Judging by your increasing passion, I feel this is a risky time to get into competitive differentiation, but I will anyway. Our competitive position in the market has evolved over time as the platform use cases have expanded and as ServiceNow's market awareness has expanded. When you think about how we have been able to consistently operate at scale the way we have, what makes the ServiceNow platform and the solutions we bring to market different?

Well, the first thing you have to understand is any CTO, CIO, COO, CEO, when they think about cost-cutting business process innovation across an enterprise, they're not thinking of the ERP system. They're not thinking their CRM system. They're not thinking of their HCM system. They're thinking, "Wow, probably ServiceNow have something going on there. Let me learn more about that. And so if you just look at the great, Jensen Huang, himself, he calls ServiceNow the AI operating system of the enterprise, and that's how He uses us and that's how He thinks about it. And we've been jealously guarding this clean pain of glass to really simulate the iPhone for the enterprise. It's clean and it's beautiful. There's enormous complexity behind it, but the user doesn't feel the pain. And so at Knowledge '25, we're going to relaunch the ServiceNow AI platform. And so when I think about the customer and what they want, they want us to meet them where they are. They want to do business with a company that has empathy at mass scale. So when I say any infrastructure, any data and any AI model, all coalescent on one platform, ServiceNow, the AI platform for business transformation. That's the story we're telling.

So for anybody who walks the halls here over the course of the next 3 days, I think they're going to experience a lot of enthusiasm in the community for what's happening here. There's any number of different ways you could talk about where you're taking the company, where ServiceNow is moving forward. When you think about this positioning, you've chartered as the AI platform for business transformation. What's important for this audience to know about the growth vectors that are going to continue to power the company in the months and the years ahead?

Thank you, Nick. I think the most important thing is we're putting AI to work for people. And you have to realize the sole crushing work that most people are stuck with on a day-to-day basis is not actually the work they ever dreamed to doing. And in most cases, it's not even what they signed up for. Think about this. The destruction of time is like the ultimate enemy of humanity. On average, people waste 5 hours a day on that smartphone in your pocket. In the enterprise, there's a legacy tax of USD 10 trillion just for America as a country for these legacy systems that are not well integrated and don't talk nice to each other. That's equivalent to 7% GDP tax. So this is a massive problem. And therefore, when I think about this platform, we invented something we call Now Next AI. And with Now Next AI, we're going to make bold moves with lighthouse customers where we bring our team of black belts and the customer's best and our partner's best to get these customers innovating across the enterprise, get them live swiftly and push broad adoption. From a shareholder value standpoint, that's going to click the meter after all the free use cases are over. And for the customer, it's going to enable them to lower their cost, fix their margin profile, no matter what revenue environment that they're in, and it's going to let them dream again, grow again. And so today, when you see CRM and you think about configure, price, quote, sell and service all on one platform, you're going to see only one company in the world that can do it. So we intend to make a very bold move and go all in on CRM. With data, we have the world's fastest database RaptorDB, 27x faster than anything else we put against it. And now you're going to combine RaptorDB, Workflow Data Fabric and of course, the automation layer, fundamentally changing the way companies do business. And you'll see how we take this to every industry, every geography, and we put this together with our partners to get mass scale across the globe. And you'll see some amazing presenters today with Amit and his team, with Paul Fipps and others, and Gina, of course. So this is just an exciting moment to be with ServiceNow.

Anything we didn't talk about you want to cover before we get the program rolling?

Well, I think the most important thing is when you have a great platform, you have an unbelievable brand. It's really important to know that the humans in the company really care. Because of enough people care, and in our case, 27,000 of them do, you can change the world. So this is a company based upon elite level execution. We do not tolerate anything else. Innovation. There's an engine of innovation here that I've never seen before. The go-to-market machine has now hit a new gear. Our operating leverage, our free cash flow, our great board, our ecosystem, the platform, the team, it's unbelievable. This is our biggest knowledge event ever. And if you think about it, it's up way more than double digits on a year-over-year basis. I don't think there's too many companies that are resonating that way in the market under the current conditions where you're actually bringing thousands more than you had the prior year and online, it's unstoppable. Look, he's the greatest news of all. We're only getting started. And we're going to be the defining enterprise software company of the 21st century, I guarantee you.

Well, Bill, thank you very much. I think everybody is looking forward to getting your questions a little bit later, but a great start to the [ program ].

I'm looking forward to it.

Thank you very much. Thanks a lot, Nick.

Please welcome, President, Chief Product Officer and Chief Operating Officer - ServiceNow, Amit Zavery.

Thank you, Bill, for sharing your inspiring vision. Good afternoon, everyone, and thank you for your time. Given this is my first time at this event, I thought I'll briefly share my background and what I'm excited about at ServiceNow. For the past 30 years, I've had the privilege of building enterprise software businesses at scale, creating billions in revenue across multiple technology waves at companies like Oracle and Google. And throughout my journey I've seen many technology shifts. This moment, the rise of Agentic AI is very different. It is not just a new technology, it's a fundamental reshaping of how enterprises will operate. So I've been following ServiceNow for some time, and have been inspired by Fred's vision of an easy-to-use powerful workflow automation platform, as well as builds ambition for ServiceNow to become the defining enterprise software company of the 21st century. And ServiceNow has an incredible talented team, an unrivaled platform, amazing customers, large partner ecosystem and now Agenetic AI is a force multiplier. So I strongly believe we are built for this moment, and that's why I joined ServiceNow. And after 6 months, I couldn't be more excited about the opportunity ahead and the amazing team I get to work with every day and learn from every day as well. So today, I'll cover 3 things: the real challenges enterprises are facing; how ServiceNow solves these problems like no one else; and I'll share some of our most impactful innovations. So let's start with the core problem enterprises are facing, fragmentation and AI readiness. Today's enterprises are at a breaking point, contending with siloed systems, very disconnected data and mounting complexity. Fragmentation directly impacts business performance. It hinders decision-making, employee productivity, customer satisfaction, revenue growth and so much more. And the speed of AI innovation is making it even more complex. Executives are under tremendous pressure to fix it fast. So how does ServiceNow solve these issues and what sets us apart from the competition? We have already led the foundation. For the past 20 years, we have been wiring the enterprise and have become the trusted operating system for business, executing over 60 billion enterprise workflows a year and building unrivaled expertise in end-to-end workflow automation, all on our AI platform for business transformation. And to do this, we have been very intentional and strategic about where we invest. We expand into areas where we can create immediate differentiated impact and we build interconnected solutions that extend naturally from our core strengths. And that's how, over the past year alone, we have delivered over 6,000 innovations. And CRM is a perfect example. We all talk about -- we all know that traditional CRM is broken. Customers need more than just a system of record. They need a deeply connected system of action. And we are delivering that by building on what we do best, simplifying processes and automating workflows. And with that, users can sell, fulfill and service on a single AI platform. And with the launch of CRM AI agents and they intend to acquire Logik.ai, of course, subject to regulatory approvals. An innovator in AI-powered configure price court solution, Logik.ai, we are doubling down on that vision. And it's working. Gartner now ranks us as a leader in CRM. Customer love our CRM. We help them resolve billions of customer cases and interactions a year. And it's the fastest-growing workflow, growing over 30% year-over-year. And CRM is just one example. The breadth of our innovation is vast across the whole enterprise. Our work on RaptorDB and Workflow Data Fabric means that customers will have the infrastructure, necessary to fully utilize their data at scale and with unparalleled performance. And within technology workflows, we continue to push the boundaries by introducing autonomous IT and autonomous security, aiming for 0 tickets and 0 outages. And we already execute over 7 billion service management events and helped close over 5 billion vulnerabilities every year. And our new AI-enabled core business suite quickly transforms core business processes such as HR, procurement, finance, supply chain facilities and legal. And it's already handling over 135 million employee request per year. And it connects employees, suppliers, systems and data in one place, enabling efficiency and faster time to value for organizations of all sizes. And when we closed our acquisition of Moveworks, subject to, again, regulatory approvals, our unified enterprise search experience will get even broader, letting our customers drive action across their silos through a single intuitive entry point. Plus customers with unique requirements can create purpose-built apps with our creator workflow on our platform. Now that they can easily now infuse AI agents with no code required transforming them into smarter agentic applications. And our innovation isn't just growing revenue, it's expanding our addressable market. From traditional ITSM, CSM and HR markets to new frontiers like risk and security management and industry-specific AI solutions. Over the last few years, ServiceNow's opportunity has more than doubled. We are positioning ServiceNow to be the essential enterprise AI platform for the new era. And today, ServiceNow is also recognized as a leader in 33 market segments. In 2024, 3 products surpassed $1 billion in ACV. By end of 2026, we'll double that to 6. In 2028, 4 products will cross $2 billion in ACV. So we have the credentials and the trajectory to accelerate our path to $30 billion in revenue. And Gina, of course, will cover our financial plans in more details. So our strategy is to solve real problems, deliver real outcomes, innovate at scale with elite level execution. And we're also delivering real outcomes for real customers with companies like Vodafone, CVS, Starbucks and thousands of others. More than 85% of Fortune 500 run the business on ServiceNow. A great example is our work with AstraZeneca. They are accelerating their innovation and transforming how they bring new medicines to market. 60,000 complex lab requests that relied on written forms and spreadsheets are now flowing through our 1 digital platform. And this allows them to save over 30,000 hours a year on that process alone. Siemens is another powerful example. They use ServiceNow's platform and automated their general business operation across 11 global locations leading into over 1 million hours saved across the company. And that's the power of Agentic AI, speed, scale outcomes. And Chris Bedi will cover more about other customer adoption and success stories. So examples like these are possible because our product platform architecture is purpose-built to scale and allow customers and enterprises to really perform. And it performs consistently whether you are automating a single business process or an entire business, and we connect every corner of a business. And now with Agentic AI taking center stage, that same architecture is the launch pad for AI agents that don't just exist -- assist, they act, their reason, they execute, they collaborate across systems and they finish task, which is very different than most of the other AI agents out there, all natively integrated in the same platform. This is important because we're entering an era with humans and AI agents will collaborate side by side. And to make this all real, I want to share with you 3 new capabilities we are announcing that enables agentic AI with human and AI agent collaboration within enterprises: AI Control Tower, AI agent fabric and AI agent studio. AI Control Tower provides customers the oversight and structure for the Agentic workforce. It is the command center for AI agents at scale where customers can manage, govern, secure and orchestrate every AI agent across the business. This solves one of the biggest barriers enterprises have when adopting AI. And to further improve connectivity, AI agent Fabric enables native collaboration for all agents of any kind across the enterprise. And we are working closely with companies like Microsoft, Google, Adobe, Box, UKG, SAP, Cisco and others to make sure it covers the whole ecosystem. We are also actively engaged in developing protocols like MCP, A2A as well as participating in various standard bodies. AI Agent Studio revolutionizes how AI agents are built. It provides a no code, business user-friendly and environment for anyone and everyone to create, customize and deploy AI agents at scale. And Jon Sigler will cover our Agentic AI innovations in a more detail shortly. So for customers who are looking at ServiceNow for strategic relationship and co-innovation as they embark on the Agentic AI journey, you heard about -- you heard Bill talk about Now Next AI. So we are launching this new offering for customers to be able to work with our engineers and be able to provide a lot more capabilities so that the Agentic AI use cases can be delivered very quickly as well as can get value out of it. So it starts with the CEO level engagement and us becoming a trusted partner to the C-suite. Our AI engineering talent will co-innovate and build and deliver specific high-value Agentic use cases, all under a simple enterprise-wide license. We're seeing a tremendous level of engagement and interest in this new offering and really excited about what this will unlock for us. And one of the biggest reasons for our momentum is clear. We meet customers where they are, any model, any cloud, any data, any system with predictability as well as flexibility through hybrid pricing, while removing friction, accelerating time to value and derisking AI adoption. And we are the only AI platform that provides this flexibility and choice. We build ServiceNow AI platform to be open from day 1. From our own domain-specific models to popular models like GPT 4, Gemini, Nemotron, Titan, Claude and open source models like Mistral and Llama, we support them all. Our R&D teams are working closely with this partner to ensure these models work great on our platform. We also do prompt engineering and fine-tuning to provide predictable and repeatable outcomes for our customers irrespective of any model they choose. But we don't stop at AI models. Choice extends to infrastructure. Customers can run a solution on the ServiceNow Cloud as well as AWS, Azure, GCP, private cloud, government and sovereign clouds or even on-prem. And they can also burn down their hyperscaler cloud commits using ServiceNow through hyperscaler marketplaces. So it gives our customers both technical and commercial flexibility. Our Workflow Data Fabric truly dissolves fragmentation, serving as the connective tissue giving AI agents real-time zero-copy access to data wherever it resides. So companies like Snowflake, Databricks, Oracle, Redshift, you name it, are working with us to provide that access, so you can do analytics on top. So no more popping data, no more delays, just instant insight and action. Finally, our flexible architecture and hundreds of prebuilt integration enables seamless connectivity with any system, package, bespoke, all legacy that our customers already own. Not only we can work with them but we can actually make them better by wiring them together at a workflow level. So as customers scale their AI workforce, ServiceNow scales with that. AI agents expand the value of our platform, driving higher ACV and creating durable high-margin revenue streams. With hybrid pricing, agent-driven monetization and platform extensibility, ServiceNow is leading the next era of enterprise value creation. Our approach is to help accelerate AI agent adoption and enable enterprises to start small and demonstrate value quickly while maintaining flexibility to expand beyond simple use cases and scale exponentially. And this is what today's enterprises want from their platform partner, infrastructure choice, model freedom, data and system connectivity with predictable and flexible pricing. However, it's not just about building the best tools. It's also about removing barriers to using them. So we continue making our products easier to deploy. We're also enabling partners like Deloitte and many others include regional system integrators to move faster. We have reimagined post sales engagement to reduce friction and expect time to value with our offering like impact product offering as well as services team, helping our customers get going very quickly. And this is also all supported by ServiceNow University, providing both partners and customers with a robust and free curriculum to open to anyone who at any AI content level, they want to scale up. Our goal is to reach 3 million learners by 2027 and enable a next generation of enterprise transformational leaders. So in just a moment, you will hear from our product leaders. They'll walk you through our exciting new innovations and the immense opportunity we are seeing of all our products. And to tie it all together, Amy Lokey will show you an end-to-end demo highlighting AI agents across all parts of the business and how enterprises are getting value. So thank you. With that, let me invite, Jon Sigler, to walk you through the details of our AI platform. Over to you, Jon.

Thank you, Amit, and good afternoon, everyone. Thank you for your time today. Over the next several minutes, we're going to talk about a few areas. And the 3 areas are our AI platform has been the differentiator for ServiceNow for decades. It will continue to be the differentiator for ServiceNow as we go into this Agentic world. We have led and we're going to continue to lead in AI innovation and our customers are already seeing success. And when they win, our business wins. So if we take a simple look at our platform, we can really break it down into 3 areas: AI. And the differentiator for us for AI is it built directly into the platform so that all the other services and all of the products can take advantage of that AI. And then AI is driven by data, whether that's data coming from ServiceNow, or that's data coming through our Workflow Data Fabric from other data sources. And then the third thing is workflows. As Bill said, we're an automation platform, a platform of action. And these 3 things, independently, they're pretty great. But you put them together, it's very hard for anyone else to replicate that. And we're going to talk about why. So as I said, the platform is the underpinning of everything that we do at ServiceNow. And so we continue to invest in the platform; things like performance, scalability, security, Workflow Data Fabric that I talked about, a RaptorDB continue to invest. We need more efficiency as we move forward. So we invest in things like process mining and task mining. And of course, our developers and that developer experience and that ecosystem and that store experience, all very important to the success of the AI platform. And then there's ServiceNow impact, and that's the digital gateway to customer success, getting our customers to value as soon as possible. And at the bottom, the $5 billion workflow executions that happen every single month on our platform shows enormous scale, but that's not why you bring it up. We actually leveraged those 5 billion workflow executions and can make them available to our AI agents, and that's how we get our customers to value so quickly. So of course, though, we are investing heavily in AI, and since March 12, just a couple of months ago, we delivered a lot of features around Agentic, and Amit brought this up. First and foremost, the evolution of AI agents in our platform and in our products, and we ship hundreds of out-of-the-box AI agents. But there are thousands in the ecosystem and we wanted to make that number go up as fast as possible. So we delivered AI Agent Studio, which is a declarative no code way to build agents. But how do you do that? How do you make that easy? Well, we deliver that through AI Agent Fabric. And not only do we use Agent Fabric to talk across systems, but it's all the tools that are made available to our AI agents so they can go off and execute. So they leverage that $5 billion, that's happening every month, and that's a head start for our customers. And the real magic here, there are other companies that say they have hundreds of thousands of AI agents, and those are all independent, and that's great. But the real magic for us is orchestration. How do you autonomously orchestrate across all of these agents, and we're going to see how that works in just a second. Then lastly, AI Control Tower, and Amit talked about this as well, and so did Bill. And we are in a perfect position to deliver on what that means for governance and visibility into what's going on in the system. So AI plus data plus workflows seem simple, hard to replicate, but it gives real value to our customers, and they're seeing that value even today. We have customers that are seeing up to 97% deflection rates leveraging our AI platform. We see increased productivity up to 71% for agents using our AI platform. And what that really means for our customers, you add that up and it's time saved. That time save equal dollars and that equals value. So our customers are winning. And guess what? That means our business is winning. We have well over 1,000 customers using our AI platform in Agentic AI, well over $250 million in ACV. It's the fastest-growing product family in the history of ServiceNow, and it will continue to be that. And as Amit said, it's a hybrid pricing model. And what that means is when we delivered Pro Plus on day 1, there was a seat-based license like we've always had. But there was also a consumption based that we built into that licensing model, and that's super important as we move forward. Here's why it's important. When we first delivered generative AI, I call it a request type of situation where a request would come from an end user saying, giving me a summary of a case or answer a question for me. Okay, that's great. That consumed assist. But then we expanded, and we said, let's use generative AI and LOMs to build out objects like code or flows or playbooks. And so we expanded the use, the consumption of those assists. And then as I said, the evolution of AI agents, an AI Agent Studio in our AI marketplace, more and more things in our system consuming assist. But as I said before, the real magic for this is orchestration autonomously. How do you bring these things together so you get true Agentic workflow. And then lastly, our Agentic Fabric, as I said, the $5 billion. Also, we need to talk to other systems. And guess what, when we're doing that, there's consumption of assists as well. We're seeing about a 50% growth in our month-to-month of assist, but that's going to skyrocket as we see more and more of agents come online and not only more and more agents, but orchestration of agents. And if we take a look at the magic behind the orchestrator, our orchestration is done by reasoning, planning and coordination without a human being. And when we take complex tasks or as Bill likes to say, sole crushing tasks that human beings have to do where there's hours, weeks, months, you take cybersecurity threats, where it's ongoing, 24/7. But what if we could use the orchestrator to assemble a team of agents to solve this problem in minutes instead of days or hours. And that's what we do. We use the orchestrator and the orchestrator has access to an army of agents. But as I said before, it does reasoning. It does planning. It does collaboration and coordination across these AI agents. And when it defines a problem and there's a request, it assembles a team. And that team of AI agents, they all do very specific things. They use the AI agent inventory that they have to solve specific problems. And the magic for us is bringing them all together to solve very complex problems. And we do that, as I said, through the AI Agent Fabric. And it gives them access to all of those things that we talked about, the 5 billion executions that are already happening in our system today. And that's how our customers get the value so quickly with our AI agents. They leverage the existing skills, the existing workflows and the information and integrations that we already have. And what that means for our customers is that they take and compress those things that we're taking weeks and months down to minutes or seconds. And we've unlocked an opportunity for our customers they've never seen before, where they can automate absolutely anything autonomously. And as I said before, these AI agents, they don't eat, they don't sleep, they go 24/7, and they solve complex tasks, but they do consume assist and they consume those assist 24/7. So that's great news for our business as we start to see and recognize both the seat-based license combined with consumption. Now I talked about the AI Control Tower. And what that allows us to do is give you insights into this massive system, that is AI. It allows you to manage and govern and secure this system as well as give insights to the value that you can get from our AI platform. And the reason why we could deliver this so quickly is we are leveraging the things that we already had, the assets we already have. Our platform, of course. Any digital AI asset can now be stored in the CMDB. So it's not just AI agents, it can be LLMs, it can be other things that are AI, and we expose that through the AI Control Tower. We've also taken our industry-leading risk and compliance and put that in our AI control tower. So you can see risk and you can see compliance in real time. And of course, this is a system of action. So our platform allows us to take action. These are not static dashboards. You can go in and onboard offboard. You can disable agents when there are problems directly from within the AI Control Tower. Lastly, visibility. We wanted to allow customers to see what was going on. The number of hours saved, the number of hours of usage that each AI agent had and as I mentioned before, risk and compliance. And we combine that with impact. I talked about impact before. Impact gives you a global view of what's going on with your product portfolio that is supplied by ServiceNow. And we have integrated that. So a customer can go into impact and now they can actually take the hour save, convert that to dollars and see the real value they're getting. So 3 things to take away. It's all about the platform. Platform will continue to be the differentiator. We continue to lead in the AI space, and we're positioned to win because our customers are winning and they're going to continue to win, and that means more consumption of assist. And with that, I would like to turn it over to Gaurav Rewari, who's going to talk a little bit more about data and analytics. Thank you very much.

Thank you, Jon. So you heard from Bill and Amit about a whole new world one where humans and machines team up to redefine work and accelerate business transformation. And Jon just gave you a glimpse of that very world. However, the grim reality is that for a lot of enterprises, the journey to an Agentic AI heaven goes through a data hell. And look, here's the uncomfortable truth. AI agents, like the ones you just heard about, are only as powerful as your data. But according to a Gartner focus group, just 4% of technology leaders believe that their business data is AI ready. And that through 2026, organizations will abandon 60% of AI projects because of a lack of AI-ready data. The good news is that ServiceNow offers solutions to accelerate the path to an AI-ready data estate, and we've identified 3 key requirements to get there. First, not if, but when the scenarios that Jon described are deployed, there'll be a lot more AI agents doing a lot more work 24/7, 365 days a year. And because the number of hours in a day isn't increasing anytime soon, the throughput of work flowing through an organization's veins will soon explode. And because AI agents will support increasingly more cognitive tasks, these workflows will be richer, more complex and more intelligent than ever before. So we need an AI-ready data infrastructure today that can scale not to millions, but to billions of complex transactions, and support both operational and analytical workloads where the same database helps AI agents generate insights and take action. All in real time and all with the security and governance that IT demands. And that AI-ready database is RaptorDB. It's available in 2 versions, Standard and Pro. Standard is included for every customer and supports all the core data operations that power the intelligent workflows on ServiceNow's AI platform. And Pro offers a vast array of advanced capabilities like column the store indexes, [ pallet ] processing, giving you unprecedented levels of scalability and performance. And thanks to RaptorDB Pro. You can now drill down to an unlimited number of dimensions in our platform analytics product, allowing for rapid root cause analysis. For example, you can now ask how many incidents were resolved last Tuesday? Group them by priority. And for the priority one, show me their category and state and, oh, tell me who are the last 3 people who worked on them. It's analytics at the speed of thought. And Raptor is performing in the wild. One of the largest U.S. mobile carriers relies on ServiceNow to support 120,000 employees. Facing the demands of over 130 million customer connections, the company upgraded to RaptorDB Pro and then the magic began 4x faster SQL response time, 73% faster report loading, 80% lower UI response time. Look, spread across 2 million or so monthly sessions, each 5-second improvement per session saves over 2,600 staff hours each month. That concrete, measurable business impact was made possible by the architectural breakthrough of RaptorDB Pro. Next, let's discuss the second essential ingredient, unified enterprise data. To get the most from your AI agents, to have them think and act on your behalf, we must enable them to learn what they need to learn so that they can do what we want them to do. They need seamless access to enterprise data wherever it resides, and they need to understand what that data means. That's why we built workflow Data Fabric. ServiceNow is data integration and semantic layer that connects all your data to drive intelligent workflows and Agenetic AI. With workflow Data Fabric, data can be structured or unstructured, static or streaming, internal or external, copied into ServiceNow or left in a customer's data lake, data warehouse or data fabric using our zero-copy connectors. And when that data stays in place, it still gets described in RaptorDB, allowing us to preserve the power of ServiceNow's single data model. And what that means is that you can treat a vast and checkered data landscape as if it were one. Customers of all sizes across industries are already realizing significant value from Workflow Data Fabric. For example, just this past quarter, a large European retailer is harmonizing and activating its enterprise data with Workflow Data Fabric to power AI-driven next best action use cases like stock replenishment, supplier monitoring, logistics tracking and more. To do this, first, they use Workflow Data Fabric to discover and consolidate data across disconnected systems, then they leverage ServiceNow AI agents to drive decisions, those next best actions and ultimately, measurable business outcomes. And that one-two punch is what sets Workflow Data Fabric apart. You see our fabric goes beyond just data integration. It is designed to spring into action and not just give you ivory tower insights that sit in a lonely dashboard somewhere. That's why we put workflow in our fabrics name. And nobody, nobody is better placed to bring together the analytical and operational words in this AI moment than ServiceNow. With its one-of-one architecture, as Bill likes to call it, and the ability of Workflow Data Fabric to power countless insight to action use cases across the enterprise armed with intelligence from any source. And to make this vision a reality, we are now scaling the reach of our fabric with a new workflow data network. So that all these magical moments of insight to action can truly happen everywhere all the time. This ecosystem of 100-plus integrations includes all the leading data platforms, applications and open source tools that you can possibly think of. With workflow data network, we're bringing the power of these insight to action capabilities right to our customers' doorstep by integrating with the data platforms that they already have. And let's hear from a few of our partners. [Presentation]

So you've just heard from Snowflake, Teradata, AWS and Cloudera and we have similar partnerships with Databricks, Google Cloud, Microsoft, Oracle and many, many more. So that brings us to the third requirement for AI-ready data. Over and over, customers tell us that they need to reduce data silos and gain greater visibility and control to ensure trust in their data. Because the success of Agentic AI hinges not just on the quantity of data access, but also it's quality. That's why we're going beyond integrating data to infusing it with a layer of meaning to help customers manage, harmonize and govern data at scale. And look, just as we've long managed our customers' IT assets, we will now manage their data assets too. So stay tuned. We will soon share some more on how we will empower customers to discover data, map and harmonize it to a rich metadata layer with meaning and power AI agents using data from just about anywhere. So there you have it, a blazing fast database for operational and analytical workloads, a fabric that integrates with customers' existing data assets and makes their AI agent smarter. Third and very, very soon, new data visibility and governance capabilities, so our customers can move fast with confidence. Three powerful ways. We will partner with customers every step of the way to get their data AI ready and their company AI ready for the profound business transformation that lies ahead. Thank you. Pablo?

So I'm here to talk about technology workflows. And I want to showcase some of the innovations that our teams have been working on. And what you're going to see today is stuff that some of our customers have already taken into production. So I think going to 3 sections. I'll spend some time in the IT world. We'll go into security, and I'll give you an update into operational technology, something that I shared with all of you last year. So starting with IT. You'll be very familiar with our IT products. We are leaders in the market segments that we play in all the way from service and operations and asset and portfolio management through to the service graph that represents the system of record for IT. And as we think of the space here, I come back to something that you heard a little bit earlier, which is that -- what we're really trying to do is put AI to work for people and specifically for people in IT. Now what does that actually mean? Well, if you think about the world of IT, what we really are envisioning is a world in which the focus isn't on incidents or outages or the stress of service delivery. We really want to give time back to people. We want to elevate their work, restore where the time is being spent and help technologists do technology, help technologists focus on innovation. So what does this world look like? Well, imagine in a world where you have no incidents because AI agents are helping taking requests for employees, they're diagnosing and driving forensics and they're driving remediation or those outages are getting reduced because not only diagnostics, but the planning, the remediation and the quick relief is all done by a set of AI agents before a customer actually sees that issue or building a service from how you take in demand, how do you do the planning, how you actually put that service out into production. All those tasks are being aided with AI agents all along the way, reducing the stress of delivering all those. This is ultimately the world that we see. And by combining knowledge in driving those digital workloads that have been at the core of ServiceNow for the last 2 decades, we believe we can deliver what is truly autonomous IT. A world in which we give autonomy on the terms of our customers, freeing people from the drudgery of all that menial work and giving time back to focus on what matters to focus on innovation. So what does this journey look like? And many of our customers that are here at Knowledge this week will know how it's all started, which is through human initiated work. You took those work -- that work and you built digital workflows. And for many of our customers, that started with service management, bringing the processes of IT onto the platform. And from there, they built out knowledge. They added the system of record, and they started digitizing workflows like operations and asset and portfolio management on top. And what this has done is, it has lead the foundation of digitized workflows and a knowledge repository of your technology estate so that today, as AI agents come out into the wild, they're able to take that knowledge. They're able to drive those workflows and they're able to drive autonomy across all of those use cases. And we're really excited about this because as of this week, we have AI agents available in all our IT products. And I don't just want to talk about it, but I actually want to show you what some of these AI agents can do. And we've got customers like USI that have these agents in production today and are seeing real material savings. So I'm going to go through a couple of examples. This is one that's live with customers today. And it starts with a view around a service desk agent, where that agent is working with an AI agent to drive a remediation of steps. And what that agent is going to do, if you click forward, is it's going to go through the steps of asking the question what it should do next. And not only getting the remediation recommendation steps but actually taking the action across each of those steps. And that's just the beginning, but it really does start turning this insight into real action. Now what I'm going to show you next is something we're really excited about and something we're going to be releasing a bit later this year. And so what we're going to do is we're going to follow Naido. Now, Naido is an employee, and he's having some issues with his applications. Now what Naido wants to do is he wants to pick up the phone and have a conversation to try to troubleshoot this. With now assist for voice, which is shipping later this year, we can actually do that. So let's listen in. [Presentation]

So not only was the issue transcribed, but what you actually saw was the AI agent knows Naido machines, knows where the issue is and can start doing diagnostics before anybody gets called in. So now as the service desk agent comes in, all that information is ready and available for them. And if we run the demo, what you'll see is that the agent can actually see each of the steps along the way and interface with the -- run the demo, please? All right. We're going to skip the demo. So I'm going to -- what you ultimately see is there are a couple of things that ended up happening there. And what we actually did was not only can you run through each of the steps of the remediation. But beyond that, we actually can go and take those steps and propose creating a dynamic playbook. And what that does is it actually enables you to not only resolve Naido's issue, but now when other employees have the same issue, what it lets them do is they can now get fully automated playbooks to drive full end-to-end self-service through dynamic actions that have been approved and put into the system. So now other people with app issues will start being able to drive that same resolution. And what that looks like is it converts tribal knowledge into living knowledge. It takes the knowledge that BI agents are doing feeds it back into the system and then helps resolve future issues, which for anybody in IT you'll know one of the biggest problems you have is the data that the systems have. We can actually reinforce that with the AI agents. Now the real magic here is you take that knowledge and then you combine it with the workflows, and that is what's helping build autonomous IT. I said I'd talk a little bit about security as well. Many of the folks here will know we have 2 main product lines in security. We have security operations and we have the risk product line. Now in those products, we serve the CISO and we serve a lot of security and risk organizations across our customers. But probably one of the best kept secrets at ServiceNow and in the industry is that we are the workflow leader in security. And what do I mean by that? Well, if you think about what we do in security, not only do we lead the market in security orchestration and response? Next slide, please. So not only do we lead the industry in the security orchestration market, which is basically the workflow market for security, we're in 1/3 of the Global 2000. We've been consistent leaders across analysts in the security and the risk market segments. And for many of the folks in the audience, you'll know we typically come to you and we say, look, as we break out in a category, we typically have a bar of at $1 billion of ACV. We really see ourselves elevated in that category. And later this year, we will cross $1 billion of ACV in the combined security and risk product lines. Next slide, please. So we are in this market. And one thing that we're going to start doing is really showcasing our leadership in this market and working across the ecosystem. So if you go to the next slide, you'll see something that Jon talked about a little bit earlier. AI data and workflows. And if you can bring this into what we do in the security space, we drive insights. We drive compliance, governance, Jon talked about some of the stuff that we're doing in the AI space there. We can drive remediation around some of the security incidents. But the real power of ServiceNow is taking that insight and combining it with knowledge. The knowledge that we have in the CMDB, bringing in integration from third parties like Cisco, Wiz, Palo Alto and Others, and all the threat information that you have, bringing that all together and then taking it into workflows. So we can go and drive remediation. We can drive actions and we can go and accelerate the strengthening of your security perimeter. So if you go to the next slide, in this space, we have a very, very analogous view to what we did in IT, which is we started driving workflows across security and risk outcomes. We've added knowledge. And now we have AI agents that are going to take that knowledge to take those workflows and start driving reasoning, automation and outcomes for our customers. And so if you go to the next slide, we have, as of this week, we've released for our customers AI agents in both our security and risk product lines. If you go to the next slide, I'll show you one of those use cases, and this is actually something that Jon talked about a little bit earlier, which is an outcome that we're delivering for security incidents. So if you play the demo, what you're going to see here is a security incident. And what we help do is, we help drive diagnostic of each of those issues and steps to go and drive that remediation. It looks like we may not have the demos working. There we go. So what you're going to see is we can actually take each of the steps, drive forensics, but we can take actions. And actions include taking a phishing e-mail out of the inbox or blocking a route at the router from a firewall perspective to remediate or provide relief on an issue. And then we go all the way out to drive writing and authoring that post-incident review and report that can then be reviewed by a human and save a tremendous amount of time, giving the SOC, a team of AI agents to go and drive some of their outcomes. So there's a tremendous amount that's coming here. A lot of it's live now, and we've got a super rich road map coming forward across everything that we're doing from an IT and a security perspective. As you see here, we have a tremendous amount of AI agents that we shipped in March, many more that are coming out now this week. And this road map keeps evolving and iterating. We're super, super excited about it, and it really is going to bring a world we're driving more autonomy for both IT and security. All right. I said I'd give you guys an update into operational technology. So let's dive into that. Next slide, please. So for operational technology, and for many of you, I gave an update a year ago, and so you'll be familiar with, it started with ransomware's tip of the spear around security outcomes. And the reason why customers want to come to ServiceNow is to bring together IT and OT into one system of record, into one CMDB, because all these environments have a lot of IT gear and operational technology gear together. And what we've seen over the past year is a threefold increase in the amount of estate that we are managing for our customers in these OT environments. And I talked last year about some of the OT products that we were releasing. We've released all of those, and we have a handful more that we shipped both last quarter and we're shipping this quarter, that's really filling out the portfolio of OT. And if you look at these, you'll be very familiar with those names because they're the same products that we have in the IT space that we're bringing over to OT. So we're really excited about this. We're also bringing AI agents to the OT portfolio, and we're really bringing the world of IT and OT together for our customers. So with that, I want to thank you, and we're going to go on to CRM with my friend, John Ball. Thank you.

Good afternoon, everyone. I'm excited to share what's going on in CRM workflows and why we're even more bullish this year than last. So let's go ahead and start by just recapping what CRM workflows is all about. And it's all about helping our customers deliver awesome service and sales experiences to their customers. And that's the core of CRM, which is why customer service is the largest discrete segment in CRM. And then when you combine it with sales and commerce makes up about 75% of the market. Now in 2023, we became the fastest player in the history of the CRM market to cross $1 billion in ACV. And in 2024, we continued that momentum growing north of 30% and ending with more than $1.4 billion in ACV. We accelerated in front office service. We expanded beyond customer service into the sales part of CRM with their launch of sales and order management. And we saw great momentum in GenAI with our customers like Zoom, TriMedx, British Telecom and more. So overall, it was an awesome year for us. Now before I go deeper into how we're accelerating into CRM I want to spend a minute to recap why our differentiated approach is driving so much success in this market. And the answer is pretty simple. The difference is that we go after the real pain points in the customer experience. That's true whether it's in service, in sales or in driving customer success and renewals. For example, in customer service, we deeply understand that you need more than just great omnichannel intake of a request. You need to automate and orchestrate the hard part which is the resolution and fulfillment. That's true whether it's a dispute in banking, whether you're ordering a new telecom service or managing the warranty claims process in manufacturing. These are all great examples of where the work starts in the front office that extends into other systems and departments, requiring both a system of record and a system of action. And we take that same approach in sales, renewals and customer success. Fundamentally, and this is really important to understand, we make it easier for a company to model the products and services they sell and support and the types of requests that a customer is entitled to and can make. And that allows us to drive much better self-service resolution, handle requests a lot faster and then also make it easier to adapt to a changing landscape, which is more relevant than ever. And in customer service, and I'll again say, the largest segment in all of CRM, we have incredible momentum in the front office. We're recognized as a leader by the analysts. We have awesome partnerships with the leading CCaaS players. But more importantly, we're winning in the market, and we're deploying at scale. We had a 62% increase year-on-year in front office transactions. So we've gone way, way beyond where we started in middle office service. Now I want to switch gears and cover how we're accelerating even more aggressively into the sales side of CRM. So last year we launched sales and order management right here. And we had a very fast start with over 60 customers signed in just the first 9 months with some awesome brands like you see here. And we primarily focused on 2 specific use cases. One was order to cash exceptions and the other is service to sales. And with all that momentum, our customers started asking us, hey, can you solve another critical part of the sales CRM process called Configure Price Quote or CPQ. And CPQ is where the rubber meets the road in sales. CPQ is where the buyer expresses their needs, and the seller establishes a quote, configuring the products being sold but also adhering to all the compatibility rules like what must be included, what must be excluded, the pricing rules like discounts and bundles. And this is a critical step in some key industries like manufacturing, high tech, B2B telco, medical devices and more. Yet this process is typically broken today. And it's broken for a couple of reasons that you see here on the left-hand side of the slide. First, it's hard to set up. And it's even harder to maintain, which makes it really difficult for companies to launch new products, new bundles, new promotions. But worse, it's slow and clunky. I would say that the quote line editor is the single piece of technology that sales reps hate the most. But they have to tolerate it because they don't really have a choice. And they end up spending their life in an Excel spreadsheet and e-mail, ping-ponging back and forth with sales ops. And because it's so slow and clunky, you can't open it up to channel partners or drive a direct-to-business e-commerce motion. Yet today, everyone wants self-service from a consumer buying shopping -- golf cart online to a business buying the telecom service, to a complex engineer-to-order product like a supercomputer or a powerful diesel engine or a forklift, customers want to start the process online. And that simply cannot work if the CPQ solution is not speed-like, speed of thought fast, speed-like would be even better, delivering an awesome consumer-grade experience. So we looked at accelerating our own CPQ efforts but we realize just how hard it is to build the C part of the CPQ, a configuration engine that supports products of any complexity and is speed of thought fast. But we were lucky to have the foresight to invest in and get to know a ServiceNow partner whose sole mission was to solve all that complexity I just mentioned. So we are extremely excited to announce back in March, our intent to acquire Logik.ai. Now we see this as an incredible better together story. We believe by combining Logik's lightning-fast configuration engine, with ServiceNow's ability to drive the end-to-end sell-to-fill and service process, we will get a unified offering that is highly differentiated and will accelerate our entry into the sales side of CRM even more. And there's no better way to understand this value and seeing it live in a demo, so please welcome up on stage Rohit Batra, VP and GM of TMT and Manufacturing. Rohit, take it away.

Thank you, John. Hello, everyone. Pure Storage is a $3 billion Storage-as-a-Service provider industry. They have one of the highest NPS and a majority of the deals today get done through partner channels, although they do have a website that they use for lead conversions, expansions and renewals. The demo that I'll take you through is a future-state end-to-end sales story across direct and partner channels. We'll do this demo based on 3 different personas: Adam as a customer; Jessica as a sales representative for a partner Alectri; and Jason as a fulfillment manager for Pure Storage. Let's start with Adam. Adam is the CTO of PlayFast, which is a gaming company and is just about to launch a new game in the market. And Adam, as a CTO, is in the market looking for a high-speed infrastructure and storage solution. Adam lands on to the Pure Storage website, where he's greeted by a virtual [ SCR ]. Adam uses natural language to talk about what his needs are in terms of infrastructure. And the virtual [ SCR ] is able to understand exactly Adam's needs and able to recommend to Adam a product line that makes sense for him. Adam approves the product line and then even provides his e-mail address, so he can be reached out by one of the partners of Pure Storage to continue this conversation. Now let's switch over to Alectri and Jessica, who's a new sales rep that's just joined Alectri. And this is Jessica's dashboard. Everything that Jessica needs is on the screen. She has the information of the customer, information of Adam. She has the entire voice -- entire transcript that she's exchanged with the virtual agent and also an AI summary that's at the bottom. We also present to Jessica a recommended product line that she can use to continue the quote for Adam. Now a screen like this is extremely useful for any sales agent, but especially for someone like Jessica, who is new to Alectri and just getting to learn about the Pure Storage products. So Jessica decides to accept the recommendation and she steps into the CPQ product. As you can see here, what happens is Jessica, based on the information that Adam has provided, we preselect the list of product lines that will make sense for Jessica to use. Now she can always expand this product line to look at everything else that might be in the catalog, but she decides to look at and consider one of the preselected items, which was based on what Adam had shared. As she selects the product line, she now steps into the configuration process. First, hardware. Now again, Adam had provided enough information for us to be able to preselect certain information onto the screen. But Jessica can always add optional components. She can add, for example, a power kit, some encryption, an adapter that might be needed. And as you can see, based on the selection, sub options also open up. As Jessica makes the selection, the pricing card on the right-hand side continues to get updated. Once she selects all the hardware, she's going to move over to the next step, that's a subscription view. And again, there's a preselection option that's already been provided to Jessica. The only thing Jessica does here is extend the term of the contract from 24 months to 36 months, and that gets reflected in the pricing as well. And then finally, she moves over to the advanced services, where she can either select the delivery through Pure storage or in this case, through a partner and she selects all the installation options that she needs. And finally, when she does all of this, she now ends up into the final screen of the CPQ. Here, she can see all the different line items that she selected, the configuration that was associated to it, the list pricing, any discounts that might be applied, and she can confirm that the code is as per her needs. She then finally submits it for approval to Adam. Adam looks at the code, verifies that everything is in order and then approves the code. We then move over to Jason, who's a fulfillment manager from Pure Storage. Now Jason is able to pull up the same order and sees exactly the same line items that Jessica has configured. But Jason is more interested in looking at the order time line. So he selects the order time line, and they can see the individual tasks of the order that are generated on the back end. He can look, for example, that the inventory is available, it's being shipped on time. And also because of the fact we have field service management on the same platform, we are able to associate the task with installation and able to make sure that the installer is at the right location at the right time to support what Adam needs. So to summarize, the 3 key takeaways from the demo. Number one, Pure Storage is able to connect across channels and across personalized in a single platform. Second, CPQ at a speed of thought, making sure that you can take away all the complexity on the back end. And then finally, the third one, which is that you can connect the front-end experience of lead management and opportunity management to the middle office of order management and field service into one single platform. With that, over to you, John.

Awesome. Thank you, Rohit. That was great as always. I think you did a great job of summarizing the key message, which I'll reiterate right now, same message, and this is the key message I'll leave you with. With ServiceNow CRM, you can sell, fulfill and service on one unified platform with no assembly required. And with that, now let me hand over to Josh for core business workflows. Josh, take it away.

Thanks, John. Good afternoon. So earlier this year, we created core business workflows by combining employee workflows and finance and supply chain workflows. essentially creating one organization focused on the back-office functions. That's HR, procurement, finance, facilities, legal, supply chain. Today, I want to talk about why we did that, talk about what's going on with our customers and how it's going to accelerate our growth. So when you look into these departments, there's really 3 types of work they all do. The first is servicing requests from employees and in some cases, suppliers. The second is a ton of manual work. And the manual work they're doing is really in preparation for the high-value work that the organization really needs them to do and that they love to do. Now with ServiceNow, our customers are already consolidating and shrinking that service layer through automation. They're also eliminating the manual work so that their people can exclusively do high-value work. And to understand how this works, I really want to start with what the customer environment looks like in a little bit more detail. So each of these departments has built their own tech stack, and they built it to serve their unique departmental needs. It tends to start with a system of record, sometimes there's a couple of them, and it has a lot of different point tools. So I talked to one Fortune 100 customer that used SAP in financials and Workday for HCM. In finance and procurement, they had 60 applications and only 6 of them were from SAP. In HR, in addition to Workday, they had 33 other applications and data sources. So all of these systems are what creates this manual work to stitch that data together and to move process from one place to another. Now we've already helped thousands of these customers improve the environment. So with servicing employees, we have the industry-leading case and knowledge management. So companies like Standard Chartered are able to deflect 85% of the inquiries they get. And organizations like Rivian, Bayer, Lloyds Banking, Dropbox are using Now Assist and our generative AI capabilities to accelerate that deflection rate even further. When you look at how they can improve the work and automate the actual work of the department, companies like PepsiCo are taking 8 different procurement processes and consolidating them into one process on ServiceNow and saving $5 million in the process. And there's a growing trend of moving all of these teams into an organizational principle at our customers as well. A lot of times, they'll call it global business services. And very often, there's a senior leader who's in charge of those global business services. Siemens is a great example of this. Siemens has provided one employee destination for all their employees to get the things they need. They put some of the core business functions into that, so they're able to operate at a higher level of efficiency, and they've saved over 1 million hours of productivity. Today, I'm really excited to introduce the core business suite. This is one place for employees to go to get the things they need. It's one place for the teams that work in these departments to automate their work and do high-value work that they love to do, supported by AI agents. And it's one place to manage the KPIs of these departments, driving them higher and higher and making a bigger and bigger contribution to the organization. Now the top layer of this is about enterprise service management. Employees have one place to go. If they need help with their payroll, they don't have to wonder, do I e-mail [email protected] or do I e-mail [email protected]. They just go to the one place. They say, "Hey, something is wrong with my paycheck and it gets solved automatically for them. It's powered by Now Assist, our multimodal capability where they can use mobile, web, chat, voice. It's got enterprise search, and it can do simple automations. What's my PTO balance, go get it from the system. Hey, schedule me PTO, go do it in the system. When you can't deflect it, the core business suite provides case and knowledge management and deeper automation to really drive that automation rate even higher. This is raising employee productivity, and it's providing a dramatic reduction in the staffing needed for these departmental help desks. What I'm really, really excited about is how agentic AI is going to transform the world of the knowledge workers in these departments. We're going to liberate them with AI agents to do all the manual work they're doing today so they can do the things that they truly love to do, the really human work in these departments. I'll give you an example of an HR business partner. So HR business partners do a process called succession planning for executives. They look at a particular executive. They look at that individual's team. They look at other people in the company that might be able to fill in for that executive and they look outside. That process involves going into Workday to get all the employee information from the direct reports and the executive. It involves going into the employee sentiment system to see how people in the organization feel both under the managers as well as under the leader. It involves going into the comp system -- into the executive compensation systems like Fidelity to see how solid each of these executives is in the company. It involves going to LinkedIn to look at their experiences and what external candidates are out there. It's a long description, but it's actually an even more arduous process for these HR business partners, so arduous that they actually typically only do it once a year, and they only do it at the senior executive levels. With AI agents, we're going to be able to do all that manual work in an instant, pulling data from all those different sources and bringing it together so the HR business partners can truly do the succession planning action plans. By doing that, they'll be able to do it deeper in the organization. They'll be able to do it more often than once a year. They can probably even do it reactively when a different agent senses a risk in a particular executive or department. Sourcing is very, very similar to this. Sourcing managers spend tons of time combing through contracts, then looking into the procurement systems to see what's been purchased, the finance system to see how it's going, the supplier systems to see how the suppliers are performing. Very, very arduous process that means they can only operate on maybe the top 10% of their spend a year to find savings. With AI agents, we'll bring all that data together, and we'll allow them to operate much further down in their spend stack. This is also an interesting case, the sourcing one because it shows you how combining legal and procurement together in one platform and in one application can deliver breakout value for the organization. This value proposition is a C-level value proposition. Every boardroom today is talking about tariff uncertainty, macroeconomic -- potential macroeconomic erosion, and they're looking for concrete cost savings. They're looking for concrete cost savings, and they think agentic AI is the answer. We're having phenomenal conversations about this in the C-suite, and that's helping us in every one of these departments. We're talking about driving better employee productivity, which is typically a very strategic objective for a lot of organizations, but it's not necessarily one where they see the path to the massive cost savings they need. But when you start talking about saving 5% of your indirect procurement spend, that's a very meaningful cost savings that can be redirected. When you start talking about -- one customer told me they saw a $100 million potential in this HR business partner productivity. So these are massive, massive ROIs that begin to put ServiceNow in a whole new realm in these departments. What's really exciting is we're in a unique position to win here because we have our core platform and we have the agentic platform. So let me give you an example in this domain to understand why that's so important. Employee onboarding, there's a deterministic workflow dimension of that. It has to happen in a certain way for regulatory compliance reasons and for other reasons. So you need workflow to make that work across all the different systems and departments. But when you add agentic, you can start doing things like building a custom development plan for your new employee based on their experience, their department, their location. You can start scheduling meetings for them before they arrive in the office because you know who their coworkers are going to be. You know who their manager is, and those meetings can be automatically scheduled. So workflow plus AI together is really an incredibly virtuous and important combination. You're going to hear from a lot of companies about how they're trying to solve the same problem. The systems of record will say, "Hey, we've got the data. So we're going to be the AI -- agentic AI platform." The reality is they only have the data they have. In the cases I talked about before of the company that had 34 different systems, one of which was Workday, if all you have is the data in Workday, you're missing a tremendous amount of the important data. You heard Gaurav talk about how we can bring all of the data from the enterprise in. They also don't have a true agentic platform. They're going to build agents, but their agents are going to make up for a clunky UX for their end users. It's not truly going to bring breakout cost savings like I just described because they don't have the orchestration and all the capabilities that John talked about. So when you look at ServiceNow, think about the fact that ServiceNow has the only platform in the market that is like it. And what core business workflows is going to do is build the AI agents to drive this transformation across core business departments. Thank you very much. And now I'd like to bring Amy Lokey up to show you what it looks like. Thank you.

All right. Thank you so much, Josh. I'm thrilled to be here today with all of you. So you'll see this week at Knowledge that Stellantis is one of the customers that we're featuring, and I am a big fan of their products. In fact, I recently just bought a new Jeep Grand Cherokee for my family trip to Tahoe this summer, and it should be delivered this month. I think I spoke too soon. It looks like it's delayed. So my anxiety just spiked. This would be a big [indiscernible] in my summer vacation. But I bet that ServiceNow and Stellantis can come together with a team of AI agents to solve this and make sure that my car arrives on time. Let's see how. So we'll start at the source with Allie, who's a supply chain specialist, and she ensures that car parts get to the Jeep factory on time and on budget. A deep research AI agent has proactively detected an issue. There's been an increase in the cost of battery cells. This could impact production costs by 25% caused by a recent tariff. AI agents recommend an alternate approved supplier that already is in the system and stays within budget. Allie clicks Explore and she opens the analysis panel to conduct deeper analysis with AI, ensuring that the new battery meets all of her production requirements and will arrive at the plant on time. This is made possible by Workflow Data Fabric, bringing together data from internal and external systems to power these comprehensive insights. This plan looks great and Allie approves it. AI agents do all the work while she watches and all she needs to do is confirm the delivery address. Allie resolved a major supply chain issue in less than a minute, making sure that everything stays on time and on budget. So one problem solved, but now there's a bigger issue. Jake is a network operations manager, and he always starts his day in the service operations workspace. His observability AI agents have detected a network issue at the Jeep assembly plant. Network transactions are dropping and if the plant loses network connectivity, production will halt. So Jake asked a question to understand how widespread the issue is. AI agents analyze the data and they find that the issue is isolated to network services. Based on those insights, Now Assist offers to create a resolution plan. Jake says, yes, and he watches the agentic reasoning in real time as AI agents are diagnosing this issue. Now this is autonomous IT. Jake is just keeping an eye on it. So when the analysis is complete, Now Assist recommends rolling back a change to a Kubernetes container to resolve this issue. Jake approves the resolution and AI agents complete the rollback. They confirm that network performance has stabilized, and they ensure that there are no anomalies in the connected OT factory equipment. So to finish up, Now Assist drafts the KD article and documents the fix, Jake publishes it and -- just in case this issue might happen again. Now this is real teamwork. So finally, Jake just has to notify the relevant teams that this issue has been resolved and disruptions to car flow operations have been mitigated. Crisis was averted. Car production is now full speed ahead. So now Jake's got a little more time on his hands, and he can get to work on some management work that he's been putting off. So he switches to his beautiful employee center, and he's reminded that the deadline for quarterly growth conversations is just around the corner, and he is not ready. He still needs to collect peer feedback for all of his direct reports. And if you're a manager, you know how time consuming this can be. Well, not anymore. So with Now Assist, Jake can get it done in minutes. AI agents start by tapping into the knowledge graph, leveraging data from sources like Outlook and Zoom meetings to create a personalized solution, in this case, finding the key peers and collaborators for each team member. Jake can review this, and he can add anyone that he wants to hear from. Next, Now Assist can tee up the e-mails to get all that peer feedback. Now writing these e-mails, as you probably know, can be incredibly tedious, but now it is so easy. He reviews these templates and he sends them out in one batch with one click. Next, Now Assist helps Jake prepare guides through these very important career conversations. AI agents pull in project objectives and personal growth goals from Workday, creating conversation guides and saving them to Jake's OneDrive directory. Outlook agents can even go ahead and schedule those one-on-one meetings, staggering them over the next 2 weeks. Now this is AI agent fabric at work. This powers the orchestration of ServiceNow AI agents and Microsoft AI agents collaborating across systems to compile information, create documents, save files and book meetings. So this is a unified team of AI agents working across multiple systems, supercharging employee productivity. So now that Jake has saved hours of work already, he moves on and he does one more thing. He plans his teams on site. AI agents start with finding the most cost-effective location based on everyone's location. They book a workshop space with brainstorming supplies and a Zoom touchscreen display, and they reserve the catering based on the team's past orders, even their dietary preferences. And given that Cinco de Mayo, tacos are on the menu. So once again, AI agents complete a number of complex tasks across several systems, all from one streamlined experience. Everything looks great, and Jake is ready to share the details of his team. His AI agents prepare an overview, pulling together a document with proposed travel plans and drafting an e-mail to get the team fired up. Jake clicks send and his on-site planning is complete. So Jake's productivity right now is on fire. In just a few minutes, he prevented a major manufacturing issue. He prepared for quarterly growth conversations and he finalized plans for a fantastic team on-site. That is a pretty incredible experience for Jake. But I'd like to zoom out for a moment and look at this from the big picture from an executive's perspective. So this week, we'll have Stellantis' CDIO, Chris Taylor, here with us. He currently uses ServiceNow to monitor the critical KPIs of how Stellantis is running on ServiceNow. He tracks everything from employee productivity to risk and security to manufacturing OT to car flow, making sure that cars are built and delivered on time from supply chain through manufacturing to vehicle delivery to dealerships and to customers like me. And he can also monitor the effectiveness of his entire AI investment. With the AI control tower, Chris will monitor all of his AI agents across the enterprise, tracking total usage and productivity gains. He'll dig in to see the distribution of AI agents across the entire business, keeping an eye on value creation, adoption and governance. It also searches its actionable insights that Chris can take to deliver more value with AI. With AI plus data plus workflows, ServiceNow enables Stellantis to run an AI-powered business all in one place, delivering employee productivity and customer happiness. In fact, look at that, my Jeep is back on track, is to arrive in time for my vacation. I am thrilled. So everyone, I'm headed out to Tahoe. You guys have a great knowledge. And Amit, back to you. Thank you.

All right. Thank you, Amy, and thank you to our product leaders. I think that was incredible. As I close out, I'd like to reiterate, we are the only platform that unites AI, data and workflows across every corner of the business, east to west, north to south. If you take one thing away from our session today, let it be this. In the era of agentic AI, ServiceNow is the pacesetter. This is not just a technology moment. It's a leadership moment for our customers, for the people, for the future of work itself. And we are defining what innovation looks like in the age of agentic AI, and we're not following but leading the way. And ServiceNow is made for this moment. And our future is incredibly bright as the AI platform for business transformation. We have the platform, the team, customers, partners, opportunity and the ambition to be the defining enterprise software company of the 21st century, and the best is yet to come. So thank you. I look forward to connecting with you later today. We will now take a short break. Thank you, everyone. [Break]

Please welcome Chief Customer Officer, ServiceNow, Chris Bedi.

Thank you, and welcome back from break. So in the earlier sessions, you saw Amit and from our amazing product team, all the innovations that we're driving in the platform. across data, across CRM, across IT, across OT, across CRM, the list goes on and on and on. And that's why customers are so excited about standardizing on the ServiceNow platform for their biggest transformations. But I'm going to narrow our focus here a little bit to the topic of the day, which is AI and AI and how customers are actually getting value from AI. So to start with, I'm going to frame it a little bit in terms of value metrics that people are looking at. And you saw some of these value metrics in the demo. You saw John Sigler talk about it. You saw John Ball talk about it. You saw all the product leaders who are up here talk about it. And whether it's at an individual use case level, whether it's at a department level or an enterprise-wide transformation, really looking at these metrics of speed, how fast is my company operating and using AI, can I get it to operate faster. And speed is a competitive advantage. If I can outflank the competition because I'm bringing products to market faster. If I'm AstraZeneca, I'm bringing drugs to market faster, I'm going to do better than my competition. Productivity and cost reduction, whether this is minutes saved, hours saved or using agentic moving 30% to 40% of what a department does to AI, people are banking on productivity as a key outcome. Sentiment, sentiment of customers that boost brand loyalty and drive top line growth, sentiment of employees that boost engagement, driving higher retention, higher discretionary effort. And then finally, effectiveness, effectiveness of every single workflow, every process in the company and effectiveness of all the human capital in our customer organizations. And all of these value metrics ladder up to top line growth, margin expansion and improved revenue per employee. When you think about how customers are doing it, they're doing it in a multitude of ways. First off, using GenAI and ML, they're creating increased capacity. So existing work, taking minutes and hours off of those tasks, freeing up capacity to do more strategic things. Agentic has given our customers the ability to move 20%, 30%, 40%, 50-plus percent of what a department does, such as customer support, IT support, order operations using our CRM platform to AI agents. And it's these teams of agents, and you saw this in John Sigler's presentation, these teams of agents with our AI orchestrator that can take this work. And where they're all laddering up to is complete role transformation. As these agents and these teams of agents are working together, they can reimagine their enterprise in an AI-first way, cutting across siloed systems of record, different departments. And they can only do that. They can only do that on a platform, which has AI plus data plus workflows, which is why all of our customers are so excited about the ServiceNow platform and all of the innovation that we are bringing to market. So what value are customers actually realizing? Bill talked about this in his opening, we drink our own champagne. We leverage ServiceNow and our AI platform to run our entire business. Today, we are realizing over $350 million in enterprise value across our company. And for departments, which were previously leveraging GenAI, with agentic, they're seeing an annualized benefit, which is 30x what they were seeing with GenAI, 30x. And this is why customers are so excited about the agentic capabilities in our platform. We have over 400,000 agentic workflows running every year. And let me talk about a few examples to really bring this to life. So when one of our sellers closes a complex deal, let's say, it's with a multinational organization. And by the way, we use our own CRM platform that John Ball talked about to run our entire business as well. When that seller has a question, how much am I going to get paid on this transaction? They previously would using the ServiceNow portal, lob a question into a back-office department, which would get them an answer in about 4 days. Using AI, they are getting that answer in about 10 seconds. So when I talked about those value metrics earlier, I talked about speed as a key outcome. So 99% faster, but it's also delivering productivity. All those people in the back office can now focus on more strategic work, but it's also delivering effectiveness. Think about that salesperson. Instead of worrying about what they're going to get paid and having their own Excel spreadsheet, trying to do this that or the other, they're focused on serving the customer in bigger and better ways. And that's what we're seeing with our customers as well, that any given AI transformation, whether it's company-wide, department-wide or at an individual use case, it's not just one metric. It's typically hitting all of them, speed, productivity, sentiment and effectiveness all at once on a platform with AI plus data plus workflows. 72% customer self-service. Why is this important? Well, from a productivity standpoint, if we didn't have AI solving all these problems, we would have easily had to hire a few hundred more people in our customer support organization. And while we deployed AI to solve these issues for our customers, customer sentiment actually went up. Brand loyalty actually went up. And that's what our customers are seeing as well when they're deploying AI and their customers are able to solve their problems much quicker. And a lot of the examples that John Ball talked about, sentiment is actually increasing. In our AI maturity survey that we just did, we've seen this as well, the pacesetters are getting 83% better gross margin improvements, 100% productivity improvements versus the people that aren't adopting AI as aggressively, and they're innovating 60% faster. The QR code that you see on the slide will take you to the full report that shows all these details, but the takeaway is pretty simple. Customers that are adopting AI at scale with ServiceNow are doing better on financial metrics, productivity metrics and sentiment metrics. So this is us and how we're using our own platform. Let's talk about customers and one of those pacesetters. So there's a lot of logos on this slide. I'm not going to talk about each one of them. But let me start with Eaton, a $25 billion power management company. They deployed our AI platform, and they saw a 100% productivity improvement, 100% in their service operations internally. And not only 100% productivity, which meant the same headcount is doing twice the work, but the work is getting done 50% faster. And effectiveness of search improved by 70%. So again, those value metrics of speed, productivity and effectiveness. Let me take another example of a defense agency. They adopted our AI at scale, went live in 60 days across IT and HR for their 29,000 employees, seeing benefit metrics, self-service 50-plus percent, productivity improvements of 40-plus percent but they've taken that 60-day go-live and they said, we're going to do more. They saw the power of our platform across AI plus data plus workflows. They're using the data part of our platform, along with AI to look at all of their spend contracts, examining areas where they could optimize spend. They're using the AI in our platform to build automated workflows and they're using agentic AI. They've built agentic AI agents to go log into 11 different systems of record, so the human doesn't have to. So work is getting done faster, wasteful spend is getting eliminated and operational effectiveness is improving. And I recall a conversation I had with a federal CTO. And given the current demands of cutting costs, cutting headcount and improving operational effectiveness, this CTO at a federal agency told the administration this. He said, "I actually don't need any more budget. I don't need any more headcount, and I don't need any more systems. But here's what I do need. I will deliver to you better operational effectiveness at a lower cost and a lower headcount, but I want to standardize across the agency on ServiceNow because he saw the power of this platform with AI plus data plus workflows where he could deliver mission outcomes, operational outcomes, technology outcomes, all on the same platform. USI, leading company deployed agentic. They're seeing 15 to 20 hours of productivity per agent. 20 hours, that's about 40%, 40% of a work week. And those are some detailed stories. I'll just give you a few quick ones. Stellantis, the demo that Amy showed, they deployed our AI in their supplier management area. And think about an automotive company fielding thousands of inquiries from their suppliers every week, went live in 6 weeks, cut their inquiries by 50%. AI is doing that much work for them. Siemens Healthineers, 200,000-plus connected devices at hospitals around the world using ServiceNow AI. Wells Fargo went live with IT and HR for 294,000 employees, and they were so impressed by the results, they said we have to take this into the branch to help our employees serve the customers of the bank in a different way, and then we're going to take it directly to our customers. I don't have enough time to go through every single tile on this slide, but the take would be customers are adopting AI at scale, and they're adopting it with ServiceNow because of the power of the platform. So I'll conclude here and just say every company today is investing in AI to completely transform their company. The pace is only accelerating. And because of the innovation and capability in our platform, they are standardizing it all on ServiceNow. So with that, I'm going to turn it over to my colleague, Paul Fipps, to talk about go-to-market acceleration. Thank you for your time.

Please welcome President, Global Customer Operations, ServiceNow, Paul Fipps.

All right. Thank you, Chris. Every time I hear stories like that, I'm reminded why I joined ServiceNow. So good afternoon, everyone. I have the privilege of leading a global team who are not just hitting our goals, but are redefining what elite-level execution looks like in the era of AI. Now over the last few years, I've sat with CIOs in Tokyo, COOs in Melbourne and government leaders in Washington, D.C. and they're all saying the same thing. Help us move faster, simplify the complexity and show us results. Now over time, we've proven that's exactly what the ServiceNow platform does. So here's where I want to take you over the next few minutes: First, why the platform wins in the marketplace; second, how we are scaling across partners, industries with a spotlight on global public sector; and third, how our international strategy is fueling our next wave of growth. Now let's dive into what makes our go-to-market strategy so powerful, how our platform serves our customers. I was recently with the Chief Transformation Officer at a global enterprise, and she looked exhausted. And as a father of a newborn son, I can tell you what that feels like. And she said, "Listen, we're drowning in tools. It's all fragmented and every AI agent pitch I hear sounds exactly the same." So I pulled out this platform diagram you see behind me, and I said, what if you could integrate all those tools and applications, pulling that data into the cloud of your choice, then use AI powered by your data to drive intelligent workflows for every activity across every persona on one platform, all focused on driving your business outcomes and your success. Now at that moment, the Head of HR jumped in and he said, what exactly do you mean by platform? So I said, I'm going to start with what I don't mean. You see what I never hear is I'm going to take a point solution or a system of record and transform my company because that's not how transformation happens. See it happens when you connect everything front to back on a platform, on a true platform. I went further with the example, and I said one of our largest customers, a CEO who is known as an AI luminary said, he put it this way, ServiceNow is the operating system for the enterprise. Now we said that because that's what our platform delivers, intelligence that moves through every function, technology, HR, sales, finance and operations. And it doesn't just integrate systems. It connects outcomes to strategy. And when that clicks, when we do our job and it really sets in with the customers, they want to move fast to transform their business with the ServiceNow AI platform. Now let's zoom in on where the magic happens. AI, data and workflows coming together at scale. See, we are winning in AI because of how we've architected the platform. We are not competing in the AI agent race. Our AI agents are built into the ServiceNow platform and those digital workers that you've heard about all day today, power the intelligent workflows that drive customer outcomes like speed, increased productivity and reduced cost. But let's talk about traction because that's where the real story is. In AI, we have more than 1,000 customers using -- now Assist, the fastest-growing product in our company's history. We have 55 partners who are already building 140-plus agentic solutions leveraging 400 custom agents in just 90 days. On the data side, since launch, 350 customers have chosen our latest workflow data fabric to power intelligent workflows. And incredibly, customers are seeing 27x improvement in analytics with RaptorDB Pro. It doesn't stop there. Customers like Vodafone and Visa aren't experimenting, they're scaling. And Vodafone is going from a reactive to predictive operations while Visa is resolving a majority of their disputes through AI. This is not slideware, it's reality. And finally, in the workflow space, we are seeing strong growth everywhere, including CRM. Customers realize that only ServiceNow can truly connect the front, the middle and the back office to the extension into the CRM, it's natural. It's not some big leap they have to take. It's the next logical step when your workflows and data are already live on one platform. All of this, while we continue to innovate on the core solutions we are so well known for. Because when AI and data and workflows live natively on one platform, the flywheel is immediate and it's exponential. Now let's turn our focus to growth. A powerful part of that growth story is our partner ecosystem, where they are turning momentum into market creation. This isn't just about co-selling. It's about co-creating markets. We have moved beyond advisory relationships into deep, high-impact collaboration. Global systems integrators like Accenture, Deloitte, Cognizant, DXC are all investing with us, building solutions and accelerating time to value for our customers. Now let's move to the ServiceNow marketplace where incredible value is being created. We now have over 1,200 applications live with more than 900 build partners contributing real innovation for our customers. And hyperscalers, they're expanding our reach even further, helping us land new logos with access to new customers through cloud marketplaces while innovating on new capabilities. This is what it looks like when your ecosystem doesn't just support growth, but it creates it. Now that growth momentum is amplified by our focus on industries. This is where we have built real depth and trust. Over the past 2 years, we've made intentional, focused investments in our industry strategy. And today, it's not just part of how we go to market, it actually defines us. Now in our priority industries, we serve over 90% of the top enterprises. And that kind of reach only comes when your platform solves the toughest, most strategic challenges customers face. Let's take Bell Canada. Bell Canada has chosen to go all in with the ServiceNow platform to power their shift from telco to techco. Over 11,000 technicians will be enabled by the ServiceNow platform to serve nearly 20 million Bell customers. You see they're not just buying software, they're betting on a new operating model to fuel their vision for their employees, for their customers and for their company. And that's a bet we're seeing customers make every day in banking, in health care and in manufacturing alike. Now let's discuss one of the most mission-critical segments, public sector, where we are showing up where it matters most. In what can only be described as a volatile and complex landscape, we are uniquely positioned to drive high impact. We're not just growing in the U.S. federal space, we're expanding globally with real purpose. Now in the U.S., we're modernizing defense, civilian and state-level operations, and it's worth calling out our U.S. federal business remains incredibly resilient. A significant portion of that business sits in defense and in the civilian side, much of it supports mission-critical IT. Internationally, the momentum is even more dynamic. In Europe, defense readiness is unlocking new opportunities, while in Asia, we're powering national infrastructure programs. So from Ottawa to Canberra, governments are turning to ServiceNow to modernize how they serve citizens. We are becoming the trusted platform for global public sector across the world. Now our third arena of growth is our international strategy. We are now driving results in the world's most important markets where we see $1 billion-plus opportunities. Let me bring this to life for the customer story. Amadeus, a global travel technology leader, has chosen ServiceNow to streamline how they manage customers and employees in over 190 countries. Now you may say why? Because we invested early in local teams, early in local infrastructure and early in localization capabilities at scale. And this strategy is paying off. 35% year-over-year growth in $10 million-plus ACV customers and more than 20 5 million-plus deals in 2024. So from Tokyo to London, our international business is resilient, it's scalable, and it's winning in critical accounts. And the best part, we are accelerating. So what does all this add up to? Let me close with where we are and where we're going. Our platform isn't just differentiated, it's decisive. It's why we're growing fast in the public sector, deepening across industries and scaling globally. Now I've spent my entire career building high-performance teams in high-growth businesses, and I've never seen a moment like this. I feel incredibly lucky and privileged to lead this world-class go-to-market engine into its next chapter because at ServiceNow, we have our purpose, we have our team, we have our platform, we have AI innovation, and we certainly have conviction. And most importantly, we have an unshakable focus on our customers' success. And with that, I'll hand it over to Gina to show you how this leadership translates into durable, profitable growth.

Please welcome President and Chief Financial Officer, ServiceNow, Gina Mastantuono.

Thank you so much, Paul, right? What an incredible leader of our sales organization. Well, thank you, and hello to everyone joining us today. You've now heard and seen the full gamut of where we're putting our focus, how we're wowing our customers, how we're leading with vision, strategy and relentless ambition. This is an exciting time for our business, and there are 3 things I want you all to take away with you today. One, our fundamentals are strong. Platform innovation and customer obsession are powering resilient growth. Two, we are shaping the enormous agentic AI opportunity. Platform innovation, agentic AI, delivering real AI with real outcomes. And three, we're executing with discipline, driving growth and profitability while generating meaningful shareholder value. Let's start with the foundation. ServiceNow continues to deliver strong, sustainable growth at scale. We've grown subscription revenue at a CAGR of 26% in constant currency from 2020 to 2024. Last year alone, we added $2 billion in revenue, all organic, bringing us to $10.6 billion. That's nearly double what we added in 2020. And the future looks bright. We ended 2024 with $22.3 billion of RPO, growing at a 27% CAGR since 2020. Nearly half of that $10.3 billion is current. That backlog is proof of our customers' commitment, multiyear partnerships, long-term road maps and larger deal sizes. This isn't just momentum, it's validation. In fact, 70% of our existing customers increased their investment with us in 2024, making up over 85% of net new ACV. For this, it means a more resilient, more predictable and more efficient business. Our long-standing cohorts continue to expand. Customers who joined us over 10 years ago grew their spend by 20% last year. Going back further, $100,000 customer in 2010 is spending nearly $4 million with us today. That's 40x where they started at an average annual growth rate of 258%. This is how we've sustained a net expansion rate of around 120% even at our scale. Customers of all sizes are realizing the better together benefit of ServiceNow. More ServiceNow products equals exponential outcomes. In 2024, 99% of net new ACV came from multiproduct deals and 86% included 5 or more products. That's not only strong product market fit, it's deep strategic integration. Customers are building on a unified platform and laying the foundation for durable long-term growth with us. Let's unpack this further. Our 5 million-plus customer segment continues to scale with average ACV up nearly 40% over the past 4 years. What's more, that pace of growth accelerates. On average, it takes a little over 4 years to go from $1 million to $5 million in ACV, just over 2 more years to hit $10 million, 1.5 years more to reach $15 million and just 1 more year to cross that $20 million threshold. What does this tell you? Enterprises are confident going all in with our platform, especially in the most complex scenarios. Here's how that plays out in the real world. Paul gave you a glimpse of our international and public sector momentum earlier. This is one great example. In 2014, we landed a federal government customer in APAC with a single agency using ITSM. Within 2 years, we expanded to 5 agencies with $1.5 million in ACV. Early wins and clear ROI opened the door to more. By 2020, we were in 19 agencies spending over $10.5 million in ACV on our platform, including HR, customer service, App Engine and IT operations management, solving mission-critical challenges from onboarding to citizen engagement to operational effectiveness. In one agency, combining ITSM with ITOM led to a 30% incident reduction rate and a 90% increase in knowledge-based usage. By the end of 2024, we reached 29 agencies and $28 million in ACV. This is a story of scale, repeatable value and strategic alignment. It starts with one win and quickly gains critical mass. Our teams engage every step of the way, tailoring solutions to the customers' challenges while expanding our footprint across all departments. And there's still more opportunity. After a decade of progress, we're still growth focused, setting our sights on the agencies still yet to benefit from the ServiceNow platform. Similarly, with our largest customers, we still have significant runway. Many of you will remember a couple of years ago, we talked about how our top 200-plus marquee customers represented over $17 billion in potential ACV just by adopting our existing products at the time. Since then, the ACV of that cohort has grown at a 23% CAGR to over $4.5 billion. The potential ACV has compounded even faster at a nearly 30% CAGR to over $28 billion in just 2 years. The data and analytics opportunity that Gaurav talked to earlier adds another layer of expansion even on top of that. The stronger the database, the more agentic AI can do, unifying data across the enterprise is paramount. RaptorDB Pro and continued innovation in Workflow Data Fabric pushed that opportunity with just our marquee customers to over $30 billion. These new offerings represent growth accelerators, scaling with broader portfolio adoption. So let's take a moment to focus on our core technology workflows. While ITSM and ITOM remains strong and foundational, we're seeing significant growth across the rest of our tech suite as well. In fact, since 2020, the attach rates of our non-ITSM products like IT asset management, security and risk have more than doubled. You heard Pablo talk earlier about the strength in security and risk. One of our other standout performers within technology workflows is IT asset management, growing at a 55% CAGR from 2020 to 2024. Customers are finally getting better visibility, cost optimization and governance across the enterprise, exactly what they need. With AI improving asset cycle management, we believe ITAM's growth trajectory is far from finished with less than 25% penetration. So even within our core, the opportunity remains ever strong. And the story doesn't stop with technology workflows. Since 2020, we've seen a fourfold increase in the average number of non-tech products adopted by new customers. 2024 also marked the first year where more than half of new logo ACV came from non-tech workflows. What does that mean? Well, we're officially busted out of IT baby, and this is ServiceNow unleashed across the enterprise. Our non-tech workflows are scaling rapidly and becoming increasingly strategic across the full enterprise. In 2024, you heard earlier, CRM and industry workflows rocketed past $1.4 billion as customers pull us deeper into that front office. Creator Workflows, which includes Workflow Data Fabric and Raptor, also surpassed $1.4 billion in ACV. Core business workflows, which include our employee experience and supply life cycle solutions crossed $1.1 billion. Clearly, our AI platform is penetrating further, further into more enterprise buying centers. In addition to cross-selling, customers are upselling to unlock more powerful AI capabilities. Our Pro SKU introduced machine learning, virtual agents and advanced analytics. Today, penetration in ITSM and CSM has exceeded 55% and they're upgrading to our highest tier to unlock even more AI value. The early momentum of our Pro Plus SKU is remarkable, already achieving more than 10% penetration of our Pro base. And we're also loving the average realized price uplift. Since launch, the move from standard to Pro has consistently seen a 25% uplift. Pro Plus is delivering an even stronger premium with a realized price uplift of 30% on top of Pro. What's more exciting is that some customers are moving directly to Pro Plus. In 2024, more than 15% of standard customers who upgraded went straight to Pro Plus. Clearly, the agentic AI capabilities are compelling. And these double upgrades makes for some really great math. We've seen average realized price uplifts of 60% for these double upgrades. I love that, by the way, just saying. As John mentioned earlier, Now Assist has surpassed $250 million in ACV, incredible progress in just 1.5 years since launch. With the potential for Assist's consumption to be layered on top, we believe this is just the beginning of a longer multiyear journey of AI investment. As customers continue to leverage our AI agents, they'll begin to add on assist packs, creating a pattern of usage and monetization that builds over time. This isn't a linear upgrade path. It's an exponential value curve. It's a model designed for expansion, scalability and long-term customer success. So let's talk about consumption. We have 3 key levers to drive Now Assist usage: one, increasing use of existing agents; two, the introduction of new agents; and three, the shift towards more complex tasks. As John showed you earlier, usage is already climbing. We've seen customers adopting and consuming at high rates, growing 50% month-over-month. We're also expanding our footprint with a steady cadence of new out-of-the-box agents to tackle more use cases for more personas across the enterprise. For custom workflows, AI Agent Studio empowers enterprises to build millions of bespoke agents on top of that. Each one of these use cases represents thousands of agents executing hundreds of thousands of playworks, workflows and tasks. Finally, workflows vary in complexity. Customers have a clear adoption path beginning with smaller tasks and gaining confidence as those AI agents deliver results. As trust builds, customers naturally deploy AI agents for more complicated workflows, expanding Assist's usage. Taken together, this creates a powerful flywheel of innovation. Increased adoption leads to better outcomes, which in turn accelerates adoption. There are over 5 billion angentifiable workflows per month on the ServiceNow AI platform. That translates into hundreds of billions of monetizable assists per year, a massive long-term opportunity. While the consumption piece matures, the move to Pro Plus will continue to drive significant growth. And now for the money slide. By the end of 2026, we expect our Now Assist contribution to reach $1 billion, a clear testament to the increasing traction of our AI products. We're also experiencing incredible AI outcomes at home. We're certainly walking the talk. Internally at ServiceNow, AI agents have reduced meeting prep time for sellers by 42% and driven 86% task deflection in areas like IT and customer support. As Chris illustrated earlier, the AI value we've realized has reached $350 million. This is driving $100 million of expected cost savings in 2025 alone. And as enterprises continue to expand and upsell into new capabilities like AI, our overall sales efficiency multiple continues to expand. It elevated to 4.6 this past year, up from 3.8 the year before. And as you all know, operating like this means more of our top line growth translates directly into profitability. In fact, last year alone, we increased our operating margins by 200 basis points and grew operating profit by 31% year-over-year. We also expanded free cash flow margin by 100 basis points, even with incremental cash tax headwinds. In 2024, we generated $3.5 billion in free cash flow at a 31% margin with year-over-year growth of 27%. In 2025, we will maintain this world-class execution. We will add over $2 billion in subscription revenue year-over-year with constant currency growth of 19.5%. Our commitment to generating robust free cash flow remains ever strong, reaching $4.2 billion and expanding to a notable 32% free cash flow margin this year. You all know where I'm going next. This all translates into continued best-in-class Rule of 50 plus performance. Based on our guidance, we expect to operate at a Rule of 52 this year while exceeding $12 billion in revenue. For us, this is just table stakes. We will ensure that ServiceNow remains best-in-class industry benchmark for excellence and performance at scale. Our strong execution, AI leadership and continued product innovation give me tremendous confidence in the future. We're reiterating our 2026 subscription revenue target of $15 billion plus, overcoming $200 million of FX headwinds since our last Investor Day when we were here last May. Our commitment to profitability hasn't changed. We're reaffirming the 2026 targets we previously shared, 100 basis points of operating margin expansion and 50 basis points of free cash flow margin expansion. But here's what's incremental. We anticipate holding our operating margin improvement of 100 basis points out to 2027, thanks in large part to AI efficiencies. This is even after absorbing any dilution from recently announced acquisitions. We're also raising our 2027 free cash flow margin expansion to 100 basis points, managing through another incremental 100 basis points of cash tax headwinds. The discipline we apply to our operating model holds true to stock-based compensation as well. We've made steady progress in reducing SBC as a percentage of revenue, which is on track to fall below 15% by 2026 and 10% longer term. We're holding firm to our annual target for employee dilution of less than 1%. As we've seen today and through consistent years of execution, ServiceNow is cementing its position as the defining enterprise software company of the 21st century. So what are the 3 things I want you all to take away with today? I said it earlier. Number one, our business is firing on all cylinders with consistent customer demand and robust growth across the portfolio. Two, we are seizing the agentic AI opportunity. Our platform strength uniquely positions us to deliver incredible AI outcomes for all of our customers. And three, this is elite level execution at scale. We're pushing the boundaries of innovation while maintaining operational excellence. Bottom line, we're a business built to last, and we are just getting started. Thank you all for joining us today. Please welcome back to the stage, Bill, Amit, Paul and Chris for Q&A. Thank you all.

[Operator Instructions]

All right. Who's going first?

Brad Zelnick, Deutsche Bank. Phenomenal presentation. There's so much to talk about. But I want to dive into go-to-market because Bill, right at the opener, you talked about heading into the next year. Gina, in your presentation, you showed us sales productivity in 2024 that is perhaps best-in-class for all companies that we look at. Something is really changing here. At the same time, somebody mentioned to me earlier today that you have over 250 SKUs to sell. The pace of innovation only seems to accelerate. How do you make sure from a go-to-market perspective that you're able to get through to the customer that they understand all that there is to offer and that you're not leaving anything on the table? It doesn't look like you are, but it just seems there's so much opportunity ahead.

Well, I'll happily start out. I think the most important thing with customers is tremendous level of empathy and intimacy. I think when Paul put up there that 90% of the marquee customers are running ServiceNow, that's a super intimate engagement with those customers. And I think the focus on industry, I think the focus on the globalization of the company and yet at the same time, constantly simplifying the company. And you're right, that's a lot of innovation, and it's a lot for folks to consume, which is one of the reasons why we invented the Now Next AI program. So if you think about the big picture here, if what you saw on stage is put forth for, let's say, the top 100 customers in the world, they could have no worries whatsoever about the numbers of SKUs. They would just buy into the road map and the future innovation cycle of ServiceNow. We would apply our best engineers, our best, best Black Belt consultants to work arm in arm with them to get them live and get them to a point where they're not only adopting, but they're extracting the value from the software. So we're making it simple to go big with ServiceNow, and we radically simplified the pricing and the SKUs and the manner in which we codify the value proposition. It could be industry. It could be persona. It could be Now Next AI if you're looking at the whole enchilada.

And I would just add on the productivity side of things. Where you're seeing a lot of that efficiency is in the operations side of sales and marketing operations. And so AI has really helped powering a lot of that efficiency, which is allowing us to not decrease headcount, but we're not growing headcount in those areas at that pace. We are 100% continuing to invest feet on the street, quota-bearing leaders to help drive sales across the board. And then the last piece, I think, is a great question for Paul on enablement for the field and making sure that they can all sell our incredible product portfolio. We have ServiceNow University that is very, very exciting. I don't know, Paul, if you want to elaborate a little bit on that.

Yes. That's a great point, ServiceNow University. And we also are really -- when we actually get the message to the field, what I showed you, the slide I showed you earlier is actually how we're actually coaching our field to sell, all around the platform, all around the complexity, building all of that up. And it gives you a lot of angles and opportunities to talk to the customer about all the offerings that you highlighted, Brad. So I think that's a really big part of the enablement. And then one last point is we're using our own AI agents to drive efficiency with the field as well. So our entire field right now can go into our systems and actually look at what's next best sell kind of capability and then generate content right away. So just the amount of time to actually prep for a sales call has been reduced by 42%. So that's how we're thinking about enablement and then obviously using AI to engage customers.

I'll just add one more thing. Working with Paul, what we've been doing also is rationalizing our SKUs. So we have done a lot of work to look at how we bring some of these capabilities together in solutions, right? So you heard about core business services. That's a good example of how we took so many different pieces we had going into different buying centers and bringing it together into one integrated suite, which allows customers to understand the full value proposition without having to go and talk about individual pieces. So this from Paul's team, they don't have to worry about now learning and going into every detail of individual areas. They look at the suite level conversation and then we bring experts as needed after that conversation as well, which is making it easier for customers to engage with us as well.

Right here, Mark Murphy, JPMorgan. Paul had asked me for softball questions only. But Bill, it goes back to something you had said. You talked about the intelligent super cycle playing out, I think, over the next 10 years. We heard of an AI deal being formulated that looks like it's going to be multiple 8 figures. And so my question to you is, how many companies do you think have that capacity, let's say, to spend 7 figures or 8 figures on ServiceNow's AI in the fullness of time if this intelligent super cycle plays out the way that you see it?

Well, I don't want to put numbers on the scoreboard here, but I think any company with 1,000 or more employees will have to go this direction. And even the small and midsized ones will need AI for survival. The greatest battle of civilization in this century is AI. It's the gateway to prosperity, but it's also the price of survival. Because if your competition does it and you don't and you're too slow, you lose. And so I think some of the bold examples, and Amit and Paul just touched on it a little bit, when you think about the personas in an enterprise, what's really good about our positioning with CRM. We could go in there today and collapse the industrial software complex onto the ServiceNow platform and take out hundreds of instances. So we could be taking millions and millions onto the ServiceNow platform but reducing the cost by even more as they collapse the stack. And that is going to happen. There's no doubt in my mind, that is going to happen. So I would say that we can do it by persona with CRM. We can go into the data world with RaptorDB and the Workflow Data Fabric story. We can go into the core business workflow story and build around the moat that was created in the 20th century that can't keep pace with today's dynamic AI environment. And what's really unique about us is you're now applying autonomous agentic AI. When I had -- it is unbelievable. I had the CIO of the company come up to me last week, and Paul gave the example. And she said, "Yes, when a sales compensation question came up, it used to be 4 days to get the answer back." Actually, Chris said it. And you said 10 seconds. Maybe she gave it a little to me, she told me 6 seconds, but either way, it's pretty fast. And so every single piece of this LEGO set, you can sell on a stand-alone basis and sell for big money because you're saving them big money and you're making them big money. But what's unique about this platform is in the end, everything ties together on an end-to-end basis on a common architecture with a friendly Workflow Data Fabric that participates with everybody, connects to the systems of record and then all the action in the hyperscaler clouds has already been integrated into ServiceNow. I just don't see any company with 1,000 employees or more not being willing to invest millions in this idea.

And I would just add to that. I talked about it when I was in my presentation, for just our marquee customers alone, the 200-plus, the ACV potential on top of what they're already buying for us is up to $30 billion, and that's just the products we have today. And that's just 230 customers out of our 8,500. So the opportunity is just enormous.

Samad Samana from Jefferies. I really want to know where Darren's voice is being piped in from. But since I only get one question, I'm not going to burn it on. I guess among the things that resonated with me today was the view that AI is not just a technology shift, but a fundamental rethinking of how companies are working. And so I suspect many of us here work at companies that use ServiceNow. I know that Jefferies does. But what can you do to get that core employee that's used to working in siloed applications versus into ServiceNow as the action layer that you described? For instance, how do you get an AE or an SDR used to working in Salesforce or another application to start their day in ServiceNow, right? How do you get somebody in HR or legal that's used to starting in a different application into ServiceNow because that's a massive opportunity. Very few applications have cut across an enterprise where people start their day and utilize it every day.

Maybe I could just start and then I'd love to give it to you guys. But think of it this way. That's why we're here. I mean, seriously, that is really the reason to do a knowledge event because our goal, our aspiration, our dream is to be the knowledge company. And so it's an awareness thing. The soul-crushing work that goes on in these enterprises with a person having to toggle between 17 different application experiences per day in their job eats up 40% of their productivity, source PwC. So they've had it. And I always tell CEOs, why do you think they don't want to come to the office? Who would want to go to that office? And so this is the new frontier. And the idea that an autonomous agent works for you to make your job better is something that we're role modeling at ServiceNow. We're badging in agents into our org chart. They're already in the shared services employee numbers of the company. And so this renaissance, this movement, is in its early days, but it is really catching fire. And we'll have thousands of thousands of people coming here that are going to get initiated. There'll be millions online that are going to get initiated. You guys are going to write about it and tell the story that this is a different kind of company. So we've been punching above our weight class to get people to listen. And now agent AI has made it necessary for them to listen. And incidentally, the fratricidal environment that we participate in the global economy is going to facilitate the acceleration of ServiceNow, not slow it down because people are looking for answers. They've got to manage that margin profile. They have to anticipate different revenue models but can't lose the margin. So the OpEx is going to go down, and that is going to collapse the industrial software complex of the 20th century. They will not disappear. They will still have meaningful transactions. They will still have meaningful data that will go into the Workflow Data Fabric into the automation layer where true autonomous agentic AI can be enabled in the business processes across the company. It is as clear as day. And when you tell people that I think you said, Paul, they get it. They just get it. So that's kind of where it's at right now from my perspective. Guys, anything you want to add?

I'll just add one thing. What we're doing also is the employee -- unified employee engagement, right? So if you as an employee have to not start in multiple systems, what we provide you is not just finding the information, but the task completion. And once you can finish the task, which is where most of the employees really care about, instead of just finding information and handing it off to another person to go and finish that work is really where the value comes in. And we are -- at ServiceNow, our ability to integrate with various systems and to understand what the user intent is and what you need to do after you -- somebody is asking for something, we can finish all that work for you, then you'll see more and more engagement. So we're building this unified employee engagement layer, bringing all the various systems and all the different business processes and workflow through that one unified place. And then the engagement goes up and up because you are doing something valuable for the employee.

Yes. And the only thing that I would add in our customers, what we see is the executives are looking at the company. Bill, you mentioned all the different recordkeeping systems, and they have a choice. The choice is, do they continue to do what they're doing and have the employees log into all these different systems? Or do they actually make it easier for their employee and there hasn't been an alternative like ServiceNow before. And now that they have that alternative, they're making a top-down decision to say, I'm going to make it easier for all of the employees at the company to get work done, improve productivity, improve the margin profile. That's a top-down. Then bottoms up, because your question was why would employee -- how do you get employees to do that? If you recall Amy's demo that she showed, that Stellantis demo, when employees see the experience and how easy it is that they don't have to log into all these different systems and agentic is doing all this work for them, they're actually running towards this technology, not avoiding it like some other technologies that have been forced on them top down.

And if you think about Stellantis, think about John Elkann. That was important to John Elkann. So the top of the house is involved in the AI revolution. That has enabled us to have the CEO conversations. Probably 6 or 7 years ago, we were talking to the CIO minus 1 or 2. Now it's the CEO who wants to transform the company, has to transform the company with AI. And who would have guessed 6 or 7 years ago that Stellantis would have been using generative AI on ServiceNow to revolutionize the shop room floor in manufacturing. I mean who? And so I get the same feedback every time I talk to a CEO, which is every single day, which is, "I had no idea that you guys do this. Can you please have your top person talk to my top people so we can do this." And then we, "Yes, it's a turnkey process. It's already thought through for you. It will be in the mail in about 5 minutes." And that's everywhere we go. So it's really starting to fuel the global fire like never before. And AI, I think, tipped it in our direction faster than we would have thought.

Matt Hedberg from RBC. I think we've all seen you guys as the platform of platforms for a long time. But now with the proliferation of agents and agent sprawl and everybody has an agent, it really feels like your new tagline could be the AI agent of agents. So with that $1 billion analysis target, talk about like how you're helping customers simplify that, that orchestration, that abstraction layer to help really drive this delivery of AI agents that we all see happening?

I'll start, and then I'm going to turn it to you, but I want to -- this is a really important question. So let's go to the CEO's office. The CEO, let's go into CRM because that's a hot one. That's a big TAM, big problems there, too. The CEO sits back and says, "I didn't know you're in the CRM space. I'm already working with so and so, and I'm talking about agents and all this stuff." I said, "Oh, were you aware that you have 175 different instances of your current CRM installation." "What are you talking about?" "Ask your CIO, he's sitting right there. Am I right?" Yes, it's true. That's true. Okay. Let's throw some agents in there. How is that going to transform the customer relationship to throw agents into 175 separate silos. And that's a whole different conversation than order management, fulfillment and service on one common platform that goes across the entire enterprise globally that gives you a follow-the-sun strategy, and we care for the customer in every time zone the same way. And probably after 174 instances, you should have slowed down a little bit. And so that's where the conversation starts and then we go.

Yes. No, I think that's -- as you heard, I mean, from John Siegler earlier today, right, the idea that we can do orchestration across the different siloed systems out there. And everybody is building agents, as you pointed out. Every application has an agent, but the agents they're building, the AI agents are very specific to their own instance in their own vertical environments. We are the only one who goes across all these different systems, east to west, right, which is really the difference where we can orchestrate all the different interactions between different AI agents, be it ServiceNow AI agents as well as third-party AI agents through the orchestration engine we built as well as supporting a lot of different protocols out there as well to make sure we will be able to manage all those different AI agents, which are built by various different third parties and give you one unified experience. So that, I think, is the differentiation we bring in as well as we are the only ones who've been able to do this last mile of doing the fulfillment. A lot of the other AI agents are giving you data back. So they're like almost a wrapper on top of an API typically or they wrap around ChatGPT, if you want to go middle ahead. But they don't do the last mile of actioning. We are going and doing all the updates in the system. The human interaction is required, but AI agents can go and do that part as well in terms of finishing the task. And that's where the difference comes in. And that's why a lot of the companies are talking to us as an orchestration engine, not just an AI agent provider.

And this is where customers really get it is when we -- I talked about in my presentation, the AI agent race because there's a lot of noise in the marketplace right now. And so what happens is all that noise is coming at a customer, and they're asking the question, well, what does it do? But give me a very practical use case that drives real return on investment at scale and then what happens after that. And so that execution engine that Amit just talked about, I highlighted this concept of digital workers that actually power those intelligent workflows is completely differentiated. And it's really important for us as we talk to customers to help them understand that differentiation.

Joel Fishbein from Truist. Bill, amazing presentation today. There's a lot of innovation that's going on all over the world around AI. The question for you is in terms of how are you in this world thinking about your M&A strategy, right? You did Moveworks, you've done a few others. There's a lot of other companies out there that can help you accelerate some of these projects that you're doing right now. And I'd love to hear how that's changed versus when you came here 6 years ago, how you're thinking about the M&A?

It's a really great question. What's fortunate, thanks to our great engineering, is that we've been able to maintain that pristine pane of glass. No matter what little tuck-ins we've done, we always integrate them well and give the customer the same experience. So that's kind of been the hallmark of our M&A strategy. In terms of our focus, our focus is clear. Our focus is on AI vis-a-vis Moveworks, assuming all the procedures are properly followed, that should be in at some point. Logik.ai, same thing, focus on CRM. And obviously, we're focused on the Workflow Data Fabric. Not because we don't think there's enough data players out there, but we're the only one that can get the data from any source and aggregate it and move it into the workflow layer where autonomous agentic AI can be performed properly. So I think you should think about those 3 areas as our primary focus areas. It's also important to reference Gina, our great President and Chief Financial Officer, now has strategy. And within that is business development. And you couldn't find a better leader to oversee the financial scenario. So anything that we do is really carefully thought through from a shareholder value creation perspective, and that will continue to be the case. So think about the priority areas, think about the customer is always going to be first with us and think about the shareholder value creation where you have that durable, predictable management team that does things that are really smart and that are chasing very large markets, but doing it really responsibly. That's kind of where we're at. And if you differ that from 6 years ago, I said organic is delicious because I knew we were at the earliest phase of maturing the platform for a platform that would be the AI platform for end-to-end business transformation. We're kind of -- we're there now, and we're just building it out to be the absolute defining one for this century.

Raimo Lenschow from Barclays. A really exciting world that we're kind of moving into. Can I change the question towards pricing because it feels at the moment, we're almost like financially nitpicking? We're asking for the SKUs. We are asking for consumption. But if you go into this new world, we kind of need to almost think bigger about this. How do you think about that? And I try to leave it very open here as a question.

May I give you a little intro on this, Amit? I just want to give a little intro because I haven't had a chance to really talk up Amit, and I want to, because I felt extremely fortunate to have the privilege of recruiting Amit to ServiceNow. And when I met him at a conference room in a Silicon Valley hotel, I didn't let him leave. When he went to get up, I locked the door and put a door chair in front of it. But we have our President, Chief Product and Chief Operating Officer in Amit, and he's a technologist, technologist. And one of the real premium moments in that meeting that we first had together was pricing and packaging and solutions. And now with Paul, our unbelievable President of Global Customer Operations, these guys are going to just change the world together. But I do really want to intro that to you, Amit, and show you that professional courtesy because you have done a great job. And everybody believes and trusts Amit, and he's made such a difference here. So Amit, over to you.

Thank you, Bill. That's really nice of you to say. And, of course, we had a great meeting, and I'm glad to be here, of course. But I think if you look at pricing, we've been very thoughtful about how we take our products, one, create solutions, as Bill was mentioning. We're taking a lot of different SKUs and creating end-to-end capabilities in one offering. So customers don't have to go and buy individual pieces, they license for everything, and then they can start using as they need to. So that's a subscription model that all continues as we've been kind of growing in that area. Similarly, in some areas around agentic, and you heard from me as well as from Gina and John and everybody else, we also started to be very thoughtful about how we bring the idea of consumption, but in the subscription model, right? So it gives us a guaranteed revenue stream, customers some predictability as well as flexibility. So we are providing, as part of our offering now, the idea that you can consume pieces of the agentic AI use cases and burn down what you have subscribed to and then buy more as your usage goes higher. So they get the chance to start get going and then go and land up getting more subscription SKUs as well with some amount of, again, agentic AI calls. And that has been working very well with the customers we've spoken to. They like this idea of having the subscription with some kind of usage-based ability to understand what they're using and then scale up as they go and start using more and more. And with agentic, what we're seeing, also the usage goes up very, very fast because some of these use cases are pretty complex and you break down the calls, the volume required for that to solve that particular use case can be pretty high and the burn down happens very, very fast as well, depending on those different use cases. So that model has been now -- we're starting to look at in many areas as we go forward and think about what other use cases might make sense from that hybrid perspective. And we're working very closely with customers, Paul, Chris and everybody else and Gina and everyone else to think through how we bring this thing in a thoughtful manner so that we can lead the way while still guaranteeing revenue as well as predictability for our business.

And I would just add -- sorry, I would just add that the importance of customer value, we've always been a company that priced on value for the customer. And that will not change regardless of how we monetize. And so we work with customers, we talk with them. And this hybrid approach right now works really well. It may very well be different 5 years from now. You can count on ServiceNow to be leading the way in how we're thinking about pricing in this transformation that AI is bringing.

Alex Zukin with Wolfe Research. Truly elite level execution here with the Analyst Day. Maybe piggybacking off of Raimo's question on consumption, you guys shared some really interesting numbers. The $250 million of Pro Plus that, I think it's another $50 million on top of where you ended the year, the $1 billion in fiscal '26 on Assist. Maybe dovetailing on that question on consumption. We were all here probably 2, 3 years ago, pressuring you on P times Q, how many seats are going to be left after AI. And it feels like we're now asking the opposite question, where both P and Q are going up exponentially. How do we factor that into the financial model? That $1 billion that you mentioned, how much of that do you intend to be consumption? And how much of that is organic versus maybe the less delicious portion of it? And that $250 million, is that part of the $100 million? Just help us kind of square the circle on some of those numbers.

Yes. So the $250 million is the current run rate growing to $1 billion, so it is part of, it's not on top of. So $250 million grows to $1 billion by the end of just next year alone. I would say it's mostly delicious organic, but there might be a little M&A tuck-in, Moveworks is an incredible acquisition that we're really excited about, all AI. As you think about monetization going forward, right, I think just think about the fact that in 2026, there'll be some of that assist consumption in there, but those billions of workflows that are identifiable, right, that we talked about, it's early, early innings on that. And so what I'd say is the opportunity longer term of where AI is going to take this company is pretty remarkable. I think at the end of the day, we're not giving you much more than that at this time. It's super early days. But I think what we're trying to say is, look, we see 50% monthly -- month-over-month increase in consumption, right? This is really going to drive powerful monetization over time. I'm super excited that 2.5 years out, it gets to $1 billion. It was the money slide. I know you all liked it. We're super proud of it, but you're exactly right. There's only more opportunity on top of that. Once the consumption really starts to layer in and that flywheel, right, because you consume, it goes well, you consume more, you build more agents. And that's the exciting part of where AI is going to take ServiceNow.

And Alex, the one thing that might be also delicious is just to think about growth. Growth is delicious. I think that's where we're at, at this phase of the journey. And I think what is really unique is our strong position. And so when you think about the dynamism of our options, it always starts with the customer. Is there something we can do in an autonomous agentic AI world that gives us permission to help the customer on an end-to-end process basis. And already, we've proven that the organic machine works. And so is there something that gets us there more quickly? And you saw that in Gina's reference to Moveworks, where it's highly complementary to what we're doing. They were already built on ServiceNow at the integration layer. So it was based on the great team here, it was what I would say, a no-brainer, plus it also gave you enterprise search, which is quite unique for the example Chris gave on the employee experience. But that also could be transferred to the customer experience. So we're always thinking about what one thing does to affect another thing and then think about those priority areas I gave you and think about the end-to-end vision. And that's what I would be excited about sitting where you're at right now, Alex, in that question, which is if they do it, they think they're going to grow it faster than it used to grow no matter what form they got it in.

Peter Weed from Bernstein. Super impressive. Obviously, love the $1 billion in AI that's coming up here. I think we've even chatted a little bit about this, Gina, and I promise to follow up with you here about this. So I mean, I think there's a couple of parts of this. One is, in addition to that, is there an opportunity to see some reacceleration in the adoption of Pro that could further juice that number? And where are you seeing early indications of kind of that type of power as part of this? The other is incrementalism. One of the challenges, obviously, as you get to the scale you are and the success you are, you can get some top-down budgeting. Is this an unlock that actually allows you to escape some of that top-down budgeting and actually generate true incremental growth as opposed to just getting some of the share shifting that you could see in some other organizations?

I mean it's a great question. At the end of the day, Peter, you're exactly right, the Pro penetration that I talked about earlier, right? So last year, we were here, Pro penetration was 45%. We got another 10% up to 55%. So AI is pulling folks from standard that we never thought would actually upgrade to Pro. A couple of years back, when I gave you the percentages, we said that we expect 25%-ish to stay on standard, right? You remember that. I don't think that's the case anymore, right? We're seeing folks on standard. 15% of the standard that upgraded last year went straight to Pro Plus because everyone is realizing in this new AI world, you cannot stay on the base. You have to have AI-enabled workflows in your workforce. So 100%, we're seeing a real pull into Pro and then an even larger pull into Pro Plus. And so I 100% believe that the opportunity to not just incrementally grow for ServiceNow, that's what this whole day has been about. I think you heard it in a red thread through each one of the presentations that my peers and the team did exceptionally well is that ServiceNow is so uniquely positioned to help our customers really advance and transform in what is 100% a renaissance. We're back in the Internet age of 2000. The change that's coming to enterprise is going to be that large. And we are so well positioned that we absolutely all believe here that the ability and the strength of this company to continue to accelerate growth is stronger and better than ever.

Kirk Materne with Evercore ISI. My question was really about one vector of growth I don't think you've talked about perhaps as much as I might have thought, which is on the commercial side. You guys, we all know you're an amazing enterprise company. You have tons of growth within the high end of your business. When AI starts unlocking value for midsized businesses, it could almost be more exponential for them. They don't have the data complexity. So what are you doing? Why shouldn't in 3 years, Bill, you have 20,000 customers, not 8,500? I understand for a while, it made sense like you got so much opportunity at the enterprise level. But it seems now with AI, product rationalization, SKU rationalization, this is the time to sort of make a bigger push into the mid-market. So I was wondering if you and Paul could just talk about that a little bit.

Sure. I'll let you start it off, Paul.

Great. So I think what we saw -- I mean even earlier this year, one of the things that we did is we actually put together an AI starter pack for our customers. We went out very rapid with it targeting our commercial customers, and we saw a great adoption of AI starter pack right out of the gate. And so the idea there is to start to seed ServiceNow's Pro Plus capabilities with some of the agentic AI in those -- in that commercial sector. That's one. I think the second is, we really doubled down the sales teams to actually accelerate growth in that section of deals. We focus on the deal band size, but it was really targeting commercial customers and getting the message out that you could either upgrade or you could actually add new capabilities because you already have the platform. We saw great success there in Q1 as well. So you're going to see us continue that throughout the year on both of those plays.

And I would complement the question really. I think it's the right challenge. What you focus on in life expands. And so we focused on the Global 2000, and you see the results. It's exponential expansion. The coverage model in commercial under Paul's leadership will be refined. We'll have better routes to market, and we already have new ideas that we're working on, on how we can scale that. And there are some smaller competitors that have talked a lot. And we'll see when we meet them head on how much they talk after we see them more. And we haven't seen them enough, and they're going to meet us head on.

And I would just add our commercial business is actually quite strong and doing quite well. And I know under Paul's leadership, it will continue to grow. And so it continues to be an area of investment even though we didn't specifically highlight it today.

Yes. But I'm convinced some of these companies, they only exist because we're not there enough, and that's about to change in a very, very substantial way. And I think AI, the coverage strategy, Paul's leadership and focus, the ecosystem that we are developing is going to come down market some while not giving up anything where we've been the strongest. But there are more intelligent ways to go after the mid-market. And next year, we'll talk a lot about that, actually. It's a good thing.

Keith Bachman from Bank of Montreal. I wanted to drill down a little bit on the CRM market or the front office market. And A, Bill, one of the things that was highlighted was CPQ, which is a part of the front office, but it's sort of a smaller part. Where do you think about the boundaries? Like where do you want to win within the broader front office, not just CPQ is a great example. And then the part B is, data is obviously important, and you guys don't have data in the systems when you think about front office. You mentioned east-west traffic, but I'm just wondering when you think about your competitive positioning, how do you overcome the data residency part of it? And then the C quest part of it is, I sound like Brad Zelnick. But the C part is, when you think about just gloves off, you want to take away from the leader in the market is Salesforce. Like where do you attack further from what you're already doing to one of the strongest competitors in the market?

I mean I think with the era of autonomous agentic AI, innovation is the only thing that matters and size can actually work against you. And so I think that if you look at the front office, which is traditionally thought of like SFA or I market to you, this market is pretty saturated and the system of record has data in it. I think what some people have forgotten is, it's the customer's data. And so the customer gets to do what they want with the data. I think there will be the system of record. Microsoft has Dynamics, excellent system of record. We use it. We partner with Microsoft. So the data can flow into the Workflow Data Fabric and everything can be automated in terms of not just the order management system on configure pricing and quoting, which is especially important in many industries like manufacturing, high tech, health care, government, other things. Just think about the complexity of regulatory security, compliance, configuration rules. It could take 8 days to put together a bill of materials and an order agreement for a supercomputer. With autonomous agentic AI, it's 8 seconds. So did it help that you were entrenched with a lot of instances in the enterprise? Or did it help that autonomous agentic AI just changed the entire game? And therefore, the data getting into the system of action where you can order, you can fulfill and service all on one platform. And that to me is the winning strategy. It's also the winning story, not to try to do what was already done in the 20th century, but actually rethink the whole process, the whole frontier. And that's what we're doing. And when you think about the customer experience in every channel and meeting the customer where they're at, whether they're online, they're in wholesale, they're in retail, they're in some kind of a direct establishment, they're working with you in any form they want at any hour in any theater, it should be as easy as ChatGPT on your living room couch on a Sunday evening, looking something up for you. And we've done that organically. And in some cases, we have Moveworks on the horizon. All of those channels now will be synchronized back to this one platform. And there's no doubt there's going to be other companies out there as many companies in the SFA space, not just one, but I think we have a very compelling story and one that companies surprising to me have been looking to hear. And it's because it's a line item that they're paying a lot for and they're trying to figure out what they're getting out of it. And that is where we come in, to help them figure that out with a better way to do things. We don't talk poorly about anybody. Everybody has got a good company. They wouldn't be big if they weren't good. This is just a different era, and it gives you more opportunities than ever before because we went for agentic AI first. And that first mover is really hard to deny because the customers, they see right through a "story that's not going to transform," but they see transformation. If it can take cost out, bring value in, they're hungry for it, especially now.

And maybe if I could just add from a customer perspective, it's sort of a pretty narrow point of view to think that the front office is simply a sales forecast or getting a quote out and things like that. If you look at the customers' organizations, there are a plethora of applications, Excel spreadsheets, all of this to make the front office work. And what John Ball is doing on our platform is really reinventing the category. As Bill said, with agentic first, with a workflow-based approach first, and when customers hear it, it's a very refreshing alternative. And it's an alternative they hadn't seen before, and they're adopting it at scale. And so when we explain to them that our platform can simplify life for their sellers, help customer service work better to serve their customers, reduce the cost to serve and make their customers happier all at once on the backbone of an agentic workflow-based approach, they're flocking to it.

I've got to give you one example. Think about a company in Europe selling, let's call it, some kind of a dishwasher or a washing machine into the American market that doesn't have a fully formed wholesale or retail value chain. What does autonomous agentic AI do? It enables you to go direct-to-consumer. You're going to go in on a direct-to-consumer basis and you're going to have to be highly competitive in your pricing. So you're probably not going to be able to make a ton of margin doing that compared to the entrenched one. But if you think about labor arbitrage and using agentic AI to manage a workforce or a service force, now with AI, I can actually do 5x more service with 80% less headcount. We actually have this case study. So now it doesn't matter who the entrenched competitor is or who's in the market. What matters is there's a new way of configuring a completely new business model where a company can generate a net new business idea and create a new franchise. So those are the kinds of questions that AI puts on the table versus mine's better than their's, which is pretty dull at this point. I think people are done with all that, and they want to work with the ones that are going someplace with agentic AI, not making a discrete system of record for a discrete department work better for 20 people. They want to make it work for 20,000 people. Just think about software. If you have a downsell or you have a cancel, we have engineering involved. We have presale involved. We have sale involved. We have post-sale involved. We have ecosystem involved. You might have legal and finance involved with terms and conditions and contracts. That is not the CRM that's in the marketplace today. That's a whole different CRM. That's the autonomous agentic AI CRM, where it is a platform play. So I think this is really a once-in-a-lifetime shot, and we're taking it.

Arjun Bhatia with William Blair. A question for Gina on how you're thinking about the cost structure and the business model as AI and agentic become a bigger part of your business because clearly, that's going to happen. You have $100 million of cost savings this year. But if that number grows over the next several years, how do you think about redeploying those efficiencies or passing them on to margin and profitability?

Yes. So first off, the efficiencies are real, and we're really excited that we're driving it. As Bill talked about, we have badged AI agents badging in already. And the fact that we are monetizing $100 million of cost savings in '25 alone, I think, is pretty staggering so quickly. As you think about the future, that will continue to grow. And so the ability to see more leverage in the model is clear. The big question is, what are we going to do with that leverage? And I would say, first and foremost, we're a growth company. There's so much opportunity here. So we will continue to invest for growth, first and foremost. Now how much we need to versus the level of efficiencies? We'll continue to model that. I'm not going out past '27. I said that we would continue with the 100 bps. I really want to make sure as does -- and by the way, this isn't just Gina. This is a leadership team that is fully aligned and they back me 100% on how much do we need to reinvest to continue to drive that growth to continue to be the leader in AI for our customers to grab value. We will always be focused on growth first. But yes, is there the ability to continue to drive leverage? 100%. How much of that will flow to the bottom line? You'll be the first to know as soon as we do.

I'll also add. I mean, Gina has been an amazing partner. I mean I think when we think about how we invest, where we want to invest, it's really a collective conversation. And the thought process around growth as well as being very thoughtful about all the investment priorities while making sure we return money back to the investors wherever it makes sense. So it's been a great, great partnership and there's been -- we've been really doing very thoughtful things around that.

Brad Sills here from Bank of America. Congratulations on another really successful Analyst Day. I wanted to ask about that team you referred to, Bill, early on, the Now Next AI team that you referred to them as Black Belts, responsible for driving adoption of agents throughout the customer base. Could you just help us understand where you're finding this talent? Who are -- we all know there's a shortage of AI talent out there. So what does that organization look like? And then what are they trying to solve for? What are some of the hurdles here to getting customers over the hump to really start driving adoption? Is it process mining? Is it just even awareness of these agents that can go after that 5 billion workflows that you've identified? Is it the data management getting more customers on RaptorDB? Would just love to get some color there.

Sure. Well, Brad, thank you very much for the question. I'll start and then the colleagues can jump in. I'll just tell you how it really worked. After a day in New York City of meeting the top executives in 2 different industries, I mean, they're very top, the best in the world, it became very clear once they heard our story that they loved it and just needed to get started and told me in these meetings all the challenges that they were having. And I realized, man, these CEOs are really against the wall here. There's so much going on geopolitically, tariffs, how their clients are being impacted. What are we going to do to help them? And I really appreciated the first question where it was like, "Hey, you guys got a lot of innovation, but 250 SKUs. That's a lot of stuff." And so how do you simplify the whole thing for those marquee clients that we just want to help them grow. We want to help them win. We want to help them take cost out so they can win. And I landed back in Silicon Valley from New York City. I called Paul up on a Friday night. Were you in on that one too, Amit?

Yes, that call.

You were in on that, too. Yes. I got them both on the line. It was late in California. And it was like, we got it. It's now next AI. And the idea was to simplify it for these great CEOs where it's in their self-interest to cut through the red tape, bring their executives to the table, line up on a strategy. We're there to work for them. Our road map is there to work for them. And we're going to put our best presale, sale, post-sale and ecosystem partners based upon our engineering domain expertise, which is where Amit and Paul came up with the Black Belt idea. So I'll let them take it further. But just think of it this way. We're not putting a CEO or the management team in a situation where they got to go through a phone book to figure out what it is they should start moving on. We're making it really easy for them. And we're going shoulder to shoulder to immediately get them live, immediately get the adoption going so the consumption model that Gina talked about kicks in. And remember, it only kicks in because they're deriving substantial value from the platform. We wouldn't want it any other way. We want to build the defining one. And that means we're building a company for the ages, not the next 4 quarters. So this plan is really all about that. So guys, do you want to fill in the blanks?

Yes. I think what we did after we talked to Bill about this and kind of thinking through, where we have good AI talent across the company? I mean we've been doing a lot of AI work, as you know, between Chris' team, they're doing a lot of implementation internally. Paul has a lot of good solution architects as well as presales people who have been doing a lot of AI use cases at customers. And we have a lot of good engineering talent who have been building a core foundational pieces around AI. So what we did was tap all those different resources and created this AI Black Belt team, which will now go directly focus on doing customer work and figuring out what kind of use cases they want help with and then supporting them through that journey. We're also hiring, of course, externally, bringing in a lot of good AI talent. So it's just starting the core of the team first. And depending on the individual customer situation, we're bringing the right kind of resources between various different groups and making sure that they're all equipped with the right kind of skills to go and help the customers and make them successful.

If I could build on what Amit said. Now Next AI has access to the platform where you need it, combined with 4 deployed engineers for innovation. So there's a lot of innovation use cases, a lot of scrum teams thinking about new capabilities inside particularly large customers and also the experts, the AI experts who actually work inside the customers to take use cases and roll out in production in 30-, 60-, 90-day kind of agile sprint cycles. And so there's a really unique both investment on the forward-looking innovation as well as just driving core capabilities inside the customer. Chris and I actually are working with one customer where we're testing this model, and already, they've been deployed for the past couple of weeks and seeing really great value very quickly. So we're super excited about Now Next AI, and that was a great fight in that call, Bill.

And Chris Bedi is like the silent hero here. I mean this guy is everywhere. You heard them today talking about those customer examples. He doesn't need slides to tell you about them. He lives them every day. And what's super unique about what we're doing here is we're also building this into the ecosystem concept, where the ecosystem is going to have to be Black Belts too, and we're upping the game. So the ones that want to partner and go shoulder to shoulder with us need to know the platform as well as our engineers do, and that will unlock tremendous market opportunity for them. And then finally, you'll hear in the keynote tomorrow, I'll talk about ServiceNow University, we're not charging people to come to ServiceNow University. What we want is to create a network effect here that scales across the global economy. So we will train in autonomous agentic AI 3 million people in the next couple of years, we will certify them. They will have a diploma. They will be able to leverage that on LinkedIn for their career. And we're going to bring out the greatness, the superpower in all of them. So they lift themselves up, they lift their careers up, they lift up the world, and that's going to be announced tomorrow also. So this is really a movement. And I just want to say -- it's a great question, Brad. Thank you. And I also just really would be remiss if I didn't thank this team because this is the best in the business. And what we really have going for us here after all the tech talk and AI and the stories are done is a culture that has a will to win and a will to fight against all odds and ultimately prevail. And you can't teach that. That's either in the culture, it's in the hearts and minds of the leaders or it's not. And it's kind of like the old story, right, about lions and sheep. You'd be more afraid of one lion leading 100 sheep, right, than 100 lions being led by one sheep. So it's like these are the lions. And the people that report to them are really fired up. And I just want you to know like you're showing up for us today in these great numbers with this amount of interest and passion is just going to fuel our fire even more. So really thank you all so much. Thank you, team, and really grateful to everybody in this room. Thank you very much.

That concludes our program for today. Please return tomorrow for another full day of informative sessions. Have a great night.