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

Hello, everyone. Welcome to our webinar, Revolutionizing HR with AI Agents. We're so glad you could join us today as we explore how AI agents are transforming HR and people experiences with ServiceNow. We have an exciting session lined up with some amazing speakers. First off, we have Kelley Steven-Waiss, Chief Transformation Officer here at ServiceNow, along with Allan Sabol, Senior Director of Product Management who are both going to guide us through the innovative aspects and practical impacts of all of these AI advances that you've been hearing about in the news for HR and people departments. So without further ado, I'd like to hand it over to Kelley to start this off. Kelley, the floor is yours.

Thank you so much, Abid, and greetings, everyone, wherever you are in the world. I wanted to start first by bringing us back to when we were little, and when our dreams were only limited by our imaginations, we dreamed really, really big about our professions, often dreaming up that we would be superheroes. What we could be and the impact that we have on the world, often describing ourselves as superheroes. I'm sure you can relate to that. However, fast forward enter this thing called AI Agents and the world of technology and somehow there were a lot of questions about our professional personas. For HR leaders how do we protect people from job loss, how do we ensure that they stay relevant and we enable them. We know that AI is on the minds of everyone. And in some cases, as always, it becomes, how does this impact me? And we're certainly used to that. So the concern with AI is growing alongside this level of awareness. So as people are becoming aware, their fears and concerns are growing at the same or if not a faster pace. So if you think about where fear actually comes from, it comes from a lack of information. The unknown is very scary, not understanding the potential impact this will have on humans and in the workforce. And certainly, in HR, this is something that we have to pay attention to. We know that everybody comes to work to do their best. No one wakes up in the morning and says, how do I come to work and do the worst I can do today. So this notion of agency or having control over one's professional destiny is really at what's at stake when fears around technology take over and really enter people's minds. So as HR leaders, we want to protect the agency of people as we enter this new really revolutionary time. I don't know if any of you are familiar with Dr. Fei-Fei Li, but she's a well-known entrepreneur and computer scientist who is also the founding Director at Stanford's Human Center for the AI Institute. And she says that AI must protect the collective dignity and self-respect of people. We need to make sure that AI translates into agency for people. And so this concept of agency becomes really kind of a part of what we protect as we move forward with AI. So the good news in all of this is that AI really isn't the evil empire. When used responsibly, it has the capability of powering a human renaissance and really protecting the agency of people and driving more innovation. In fact, a responsible AI strategy will do this by ensuring data privacy, creating responsible AI policies, producing unbiased Gen AI results, avoiding data hallucinations, which, of course, we've talked about and also increasing the productivity of people. So it's really making work better. I'll also say that some of those positive outcomes for people is that it enables us for hyper personalization. So in HR, we used to do one to many. Now we have the opportunity to really do one to one. We can reduce a lot of the manual work which is creating headaches and friction for people. We can unlock these new levels of creativity, and we can inspire some of these new ways of working. So it's certainly not this evil empire. But as HR leaders, we're sort of standing at the bottom of Everest. We feel like this -- scaling this transformation is a tall order and the landscape is getting increasingly complex. So we're often left with where do we get started. And so this for our HR at ServiceNow, this really became how we enabled AI Agents and certainly, this strategy. The first of these pillars was know AI agents. A lot of it was about educating people and understanding this impact around AI and certainly how it impacts them. How to use AI agents, what were the use cases that we could serve and we needed to teach people how this new world was evolving. Then we had to build those AI agents, so where could they make the biggest difference in our workflows. And then most importantly, as we looked at the number of roles that were changing as a result of agentic AI, what is the reskilling and upskilling that we need to do so that people feel confident and we're really focused on AI agents where they make a difference. So all of you are probably sitting there thinking about, yes, we're on this journey too. So I want to do a poll. And this question is, where is your organization in its AI journey? So I'll give you a second to answer this. It's a, I'm just starting to explore AI solutions; b, piloting AI or AI agents in select HR workflows; c, using AI or AI agents across multiple HR functions; or d, fully integrated AI in enterprise-wide processes. So go ahead and take a minute to respond and then I'll click over so we can see the results. [Voting]

A couple more seconds. Okay. Let's look at our results. Okay. So it looks like the majority of you, and this is no surprise, are really just starting to explore AI solutions. I think, to a certain degree, that's because we're -- first of all, this is moving so fast. I mean, we were talking about Gen AI for 6 months, and we moved into agentic, and so we're all trying to grapple with what does this mean. So this is certainly no surprise. We hope today, we get a chance to share a little more about where you can start. But at the very basic, we are at certainly an inflection point in our journey. We have been on that journey for a while. AI is not new, but it's evolving so quickly that in HR, we're trying to figure out where are these use cases and where do we get the best outcomes. So HR's mandate is to really take the lead in adopting, enabling and governing AI to unlock that productivity that we talked about and really drive change. And driving change, given we talked about the fears that people have in order to get people to adopt it, they need to start seeing how this is making their world better. So we're at this pivotal moment leading the market in conversational workflows with our Now Assist, which is our generative AI technology, which is really our fastest-growing product we've ever had. Customers are starting to recognize the power of AI across the enterprise and they're starting to see these tangible impacts on business drivers. So our continued investment in platform innovation truly puts AI to work for people. And at ServiceNow, we're spearheading this shift with agentic AI, which really enables systems of intelligent agents to orchestrate those workflows and act autonomously on behalf of users. And these agents are critical within the take action layer of systems really preventing leaders from being able to make those critical decisions. So whether it's hiring, workplace operations, health and safety, complexity is costing teams our productivity and organizations their momentum. So the good news is it doesn't have to really stay this way. So let's talk about how ServiceNow really simplifies this and takes out a lot of the chaos. So the reality is that most of these experiences are super frustrating. So we have so many systems. In fact, managers have like 14 systems that are coming in and out of every day. So if they're struggling, it makes our talent planning and certainly for managers very frustrating to figure out where people can do their best work and certainly, what type of roles they need to support this. The workplace support is also inconsistent. So we have experiences that are very different whether people are hybrid or not. And so we have to have a way to really fix this. And the bottom line is that AI is really only as powerful as the platform it's built on as the systems and data it's harnessed to act on, which is why we've been laser-focused for 20 years on building a platform that unites all of our department and systems, a platform that's really ready for AI. So as we think about how does AI really go on steroids. It's really about connecting everything together across the enterprise, all the technology. And so making employees be able to work seamlessly across that enterprise and really effortlessly. And so this is our unique advantage. And it's why 85% of the Fortune 500 are actually running on ServiceNow. And the best part is that you can get up and running in months and not years. And so we're really optimizing a lot of these processes and the investments that you've made in technology across the enterprise. So now I'd really like to turn it over to my colleague, Allan from our product organization to take us a little deeper in how we make this all come to life in our technology. So Allan, I'll turn it over to you.

All right. Great. Thank you, Kelley, and hello, everyone. I'm very excited to be here today and talking about my favorite topic, which is AI. Before we get into agentic AI though, I want to make sure that we talk a little bit about generative AI for a moment because it really is a foundational building block to be able to get our AI agents to work with people. So in 2023, we launched our Now Assist product in response to our customers, who basically said, look, I want a unified conversational experience from my employees, a single place for employees to go where they can ask a question in their own natural language and get the exact personalized answer they need, no matter where the data lives, where that answer needs to come from. And also, they can take actions to that same conversational interface so that they're not constantly required to go single sign-in to yet another system which employees are just about done with at this point. There's just too many systems. What we heard from our HR customers was that there's some specific things that really matter to HR. The first is it has to work for all personas across all different channels, right? We can't think about just chatbot because a lot of employees don't start with chatbot, they start with search. And we have deskless workers. And those deskless may not have access to tools and technology. But we make -- so we have to make the conversation experiences available in mobile, SMS and other types of channels. Also, we heard from HR that it needs to be integrated to have a unified conversational experience that answers all questions and allows all actions, you have to be connected to all systems. And so we've made it very easy to connect enterprise systems, and I'll talk more about Workflow Data Fabric in a minute, which helps you do that. We heard that it needs to be proactive, not just reactive, and very important to HR is that it has to handle sensitive issues like sexual harassment and other employee relations related matters. And it needs to be able to really make sure the LLM does not hallucinate when it's a moment that really matters like that. And then finally, it has to work across all different departments, right? This is not just about HR. It's really more broadly about employee experience. And employees don't know the difference between HR, IT, legal, procurement, workplace services. They just know they have a question that they need to have answered, and they want to be able to go and ask the question, right? So that's what we delivered in 2023. And ServiceNow is really uniquely positioned to deliver this unified experience for both HR and employee experience. Hence the reason, as Kelley mentioned, this is our fastest-growing product ever. Now as HR leaders and their IT partners start to think about how AI agents are going to interact with employees, with managers and with HR practitioners, it becomes even more evident that having Now Assist conversational experience implemented in their organization really does become a foundational prerequisite to have success with the adoption of AI agents at scale. Okay. Now if 2023 was the year of enterprise-grade generative AI for transforming HR employee experience, then 2025 is the beginning of this journey towards a truly agentic organization that supercharges employee and business productivity or the way I like to think about it, human productivity. And Now Assist really is the agentic AI platform for business transformation. Okay. But let's take a step back again and let's think about what is an AI agent because there's a lot of folks still trying to understand this. What exactly is an AI agent and what does it do? Well, unlike the previous scripted automations in traditional AI that kind of struggles to solve complex tasks and requires a lot of direct human intervention, AI agents are very autonomous. They are autonomous systems that are capable of gathering information, applying reasoning like a human would, taking actions and making decisions dynamically on the fly to achieve complex goals. That's the key. And also, it has the ability to interact with its surroundings to take those actions. They don't require -- AI agents don't require any constant human instruction or intervention. It makes them much more dynamic and effective to complete tasks on their own independently. And they're not just tools. They're really more digital workers. I think it's a good way, a good frame of reference to understand an AI agent. Imagine you have a digital worker that is deployable anywhere in the organization and can scale across the enterprise, and it just becomes part of your workforce, right, to help you automate and reduce the amount of those tedious manual routine tasks that today we have human beings doing. So organizations really can achieve unprecedented enterprise productivity when they use these AI agents. Okay. So I'm sure you're already hearing this. And if you've been to any HR conferences lately, I know you've seen this, but nearly every HR software company from startups to large systems of record, they're all feeding this hype cycle around AI agents, right? And you can expect the proliferation of AI agents in all of your enterprise systems over the coming years. But nearly every company that we speak with is trying to answer 3 really important questions. The CIO, organization is asking the question about how these hundreds and even thousands of agents are going to actually work across the enterprise, right, across all these different systems that are introducing more and more of these agents. How do they work together? That's the question the CIO is asking. CHROs are asking a very different question, which is how in the world are we actually going to govern all of these AI agents? If we're going to have tens and hundreds and thousands of agents running around our organization, interacting with sensitive HR data, how do we avoid data breaches? How do we protect employee experience? That's the question CHROs are asking. And nearly everybody is asking, who is the platform that we're going to count on and trust to help us meet both of these objectives. I think the answer is pretty clear. ServiceNow has been investing in this foundational capability that's required to get to this next stage of evolution of AI, which is AI agents. But we had to first organically build or acquire scripted workflows, predictive workflows, conversation workflows, RPA, these are all basic foundational pieces in being ready to achieve what your organization now needs to get to AI agent at scale. So that's something that we've been working on. Okay. So another thing to think about here is that only ServiceNow really unites the AI agents with data and workflows on a single platform with a single data model that brings AI to every corner of your business. So ServiceNow AI agents, they don't just assist, they take action, right? Teams of agents working together to orchestrate end-to-end business processes across IT, customer service and HR and employee experience. In order for these agents to actually be able to transform your business, they need access to the right data. So we just introduced this year Workflow Data Fabric, which is a really important capability that allows you to connect, unify and understand all of your enterprise data, both structured and unstructured, wherever it might reside, whatever enterprise system it's sitting in today. This is all done on our secure and trusted platform adhering to the AI and data governance standards that are required by local state and federal laws and regional laws. And importantly, this data security model that we have put together really does protect HR data in a way that no other system actually does. And then finally, you have the workflow piece, right? When your AI agents run on ServiceNow, they're leveraging the world's #1 workflow automation engine. So it's really this combination that makes ServiceNow the AI platform for business transformation. And it's why so many companies choose to run their entire enterprise on our platform. Okay. So we cannot expect every -- we can't expect if we want to scale AI agents, we really can't expect IT to be able to build every single AI agent that you need across your organization. First of all, it's not scalable. And second, it really -- it's unrealistic for us to think that IT is going to really understand how each individual team is operating, what Workday can get done on a day-to-day basis [Technical Difficulty] AI agents down to the lowest level, which is the team level where the work actually happens every day. And to do that, we need to start to onboard and train AI agents just like we do with human workers, so they can work seamlessly within our organization. ServiceNow has always been the leader in onboarding and ramping up workers within an organization, human workers, that is, and now what we're doing is the exact same thing for your digital workforce. By making it easy for your managers and teams to identify, onboard, ramp up and measure the performance of these AI agents, and then make them better over time, right? So the same thing you do with your human workforce that ServiceNow helps you with, we're now going to do with your digital workforce. Now there's still some confusion out there about chatbots versus AI agents, and they are truly different, right? So I want to try to clear this up a little bit. A chatbot, even one as powerful as something that's powered by like a large language model, is not necessarily an AI agent. So here's how to think about the difference between like a traditional chatbot and an AI agent. We're moving from a world where we had scripted decision-making with chatbots. We're moving towards AI-driven decision-making, right? Actual agentic intelligence, agentic reasoning that can make decision-making much better. We're moving from constant human intervention to human intervention only when needed because these agents are autonomous by nature, right? And we only have a human in a loop to make sure that things are on track when needed. We're moving from expertise in a single domain to expertise across multiple domains. And we're moving from an isolated view of some tasks to more of a 360 degree view across all tasks. So these are just some of the differences as we move into this new agentic AI world. Okay. So let's use a practical example of a complex business process that might be automated using an AI agent, which is interview scheduling. I only pick this one because every company faces this challenge. And I think it's very illustrative of how these AI agents can do something that previous chatbots could never do. Today, interview scheduling is a completely manual process, and in many organizations, it can cost millions and tens of millions every year to pay contractors to do this work, right, to basically manually schedule these interviews. Now imagine in -- sorry, imagine that a human worker who manages that interview scheduling process, right, is able to identify, onboard and train an AI agent to do that same interview scheduling work that right now contractors are doing. Once the AI agent is ramped up, the human manager can measure their performance, give them feedback on areas that need improvement. And as you can see from this example, the AI agent can then communicate with human workers as well as other AI agents to support and make a more efficient business process out of this interview scheduling function. So this is just one example of literally hundreds of places you're going to be able to automate and make more efficient HR processes, but also just things that employees need to get done every day. Just the way people work is going to change. And so let's take a look at some of the ways that that change is going to happen. This is actually one of my favorite representations, and this is a little bit forward-looking. So I'll tell you that this is kind of looking down the road maybe a year or 2 down the road in some cases. But this is really exciting because this is where it's all going. We see different levels of where you're going to have AI agents driving productivity across the workforce. Let's start with the basic level, which is our employees. All right. Individual employees, we will all within a couple of years, have a digital twin or a personal assistant, however you want to look at it. And the digital twin, its role is going to help us individually be more efficient. How will we train that agent? We'll use our natural language, and we'll tell the agent of what we wanted to do. So for example, I might say, hey, I'll go to Now Assist and I'll type in any conversational interface. I'll say, you know what, go to Workday, log in and get me my last performance review because I don't remember what I got. And it will go asynchronously take care of that and then bring it back to you when it's done. Or I may say, hey, go into Outlook and cancel all my meetings, reschedule my meetings after 2:00 p.m. today because I'm taking the rest of the day off. And it'll understand that and be able to go execute that action using Outlook as the tool. So this is where we're going with individuals. Then you've got that hiring manager or a team lead who's going to be training agents to help do work on a daily basis. A great example here is like you're a recruiter, I'm using another talent acquisition example, but there's so many across all of HR. But you're a recruiting manager and you got 10 recruiters, they're -- they spend 50% of their time reviewing employee referrals because employees just send anything over. Well, if you get an AI agent do some basic screening for some key qualifications, respond back to those employees, let them know when it's not a fit. And that way, they're prescreening and saving your recruiters time to work on more value-added tasks, right? So these are example of where individual teams need to be able to train the AI agent using their natural language because you really can't have someone up at the corporate level or IT who's training how to screen employee referrals for a given recruiting team that's focused on a certain area of recruiting, right? It has to be done at the team level. The next level up is your business owners or your process owners, your service owners. And this is where you're doing purpose-built AI agents to support parts of your enterprise. Think about talent development use cases, talent acquisition use cases, think about growth -- learning use cases. There are so many different areas in your business, you're going to be able to make more efficient by letting those business owners and process owners improve their processes and create better experiences. And then finally, you have that kind of level where you're going to invest in your own company architecture around things like governance and integrations and things like that. And that's where your IT developers are going to come in and really putting together the foundation of what you want to have in your organization to make things safe and effective across the ecosystem. And of course, ServiceNow is going to develop all sorts of -- and we already have developed all sorts of out-of-box AI agents to get you started. We give you these agents so that you can get a fast ramp up, get immediate ROI on some of the key areas I mentioned earlier, and of course, some of the foundational aspects of just your AI agent studio where you can build out these agents at scale. Okay. And so finally, just kind of looking at the key takeaways. How do we get our organizations ready for this new and more efficient way of working? It's going to be our responsibility as HR leaders and IT leaders to do 3 key things: number one, start by assessing all of your workflows and looking for those areas of the highest ROI potential, quantify and figure out the cost savings from an investment in AI because there is enormous ROI here. Start with the big wins, right? The ones that are going to give you the most ROI but then also don't forget about scaling to all those other areas where you add them up, and there's a lot of savings as well. So that's the first step. Where do we want to automate. Second step then is put in place the governance practices necessary to make sure you're getting responsible use of these agents. ServiceNow is investing more than any other enterprise software company and making sure that there is governance capabilities to protect employee data. I cannot emphasize the importance of that enough because it really is the most important thing for CHROs. And then third, faster closure of collaboration between humans and agents, right? So Kelley mentioned earlier, this idea, well, I'm a little bit nervous about people taking my job or about these agents taking my job -- I'm sorry. And the reality is we can't think of it that way because it's really about making us more productive. It's about augmenting the things we do every day that we don't want to be doing that aren't value-added so that we can focus our employees on innovation, on strategy, on empathy, human empathy and building connections and being great managers, for example, or working better with our teams. So we need to start to change the mindset that AI isn't there to necessarily take all the jobs. It's there to augment humans so that we can really work at our most productive and deliver the most for our business. With that, I'll go ahead and turn it back over to Kelley.

Yes. Thanks so much, Allan. As a former CHRO, I have a ton of empathy for this change. It's both exciting but it can feel daunting. I know just sitting there, listening to talk about having a digital twin, I was thinking about all the things like all the work I could direct that I may not want to be doing. And so I think a lot of opportunities. But let's go back to something we touched on earlier. And this is particularly important for HR leaders, which is what does a responsible AI strategy really look like? So while this new capability is moving at an astounding pace. We're approaching this with both expediency and care and keeping the trust and experience of our customers at the forefront. And our customers are certainly our employees. I mean that's how we feel in HR. So we know that it's critical to have the right guardrails in place. So one, and we mentioned it earlier, employee data and organizational IP is secure. Secondly, transparency. We're providing clarity and transparency from vendors and for end users. Third, security and infrastructure requirements are met. We absolutely cannot let down the guard when it comes to people data and custom fit to your organization's needs. So as we are looking at use cases and how those come to life in the enterprise, how do those work for your company and what's important to you. So thinking about the change itself, I love this quotes, which is about people are most reluctant to trade privacy and control unless the value they gain exceeds the risk they perceive to be taking. This is what we call a value exchange. So one undeniable truth is that to accept this new world of AI agents, people must see the exchange of value. We need to help them understand how AI agents will extend, augment and give them the freedom to create and contribute what is uniquely human. And there is so much that is uniquely human that people provide. And this is going to open up, as I said earlier, the human renaissance. So in terms of the AI-enabled organization, we talked through these 4 pillars. Know AI, use AI, build AI and reskilling and upskilling. And I just want to hone in on the reskilling and upskilling is so critical. As you guys think about what is first steps that we can take beyond engaging and getting the right enabling technology, and we hope that's ServiceNow, it is about looking at all the roles in the organization and where these AI agents are going to impact those roles and ensuring that you bring people along. So figuring out what your education strategy is to get people up to speed in this new reality because it's moving so incredibly fast. So let's do a poll and get your feedback. Which aspects of AI agents excites you the most? A, automating routine HR tasks for greater efficiency; b, enhancing employee self-service experience; c, gaining data-driven insights for better decision-making or; d, supporting personalized career development path. So lots of opportunity here. Take a minute to respond. We'll take about 45 seconds to give you time to respond to this. [Voting]

Okay. So interesting results. So looks like automating routine HR tasks, very popular but the most responses came in at enhancing employee self-service. So this is no surprise either because I think that we are really trying to empower people, and that's where the exchange of value is, how do we make work better for them. And so if we can take a lot of the questions that might be coming in, the friction that comes in for people and they can self-serve and go find that information and have a better experience, that's probably most paramount. Okay. So just wrapping this up, HR has a critical role in this. This is our opportunity to absolutely lean in to this revolutionary time. One is that it's about the governance. So let's make sure that you all feel like you can lead here because in order to put the guardrails, in order to ensure that there's an exchange of value, and we think about the agency of people, it starts with governance. Secondly, we have the ability to drive greater adoption by ensuring that those experiences, whether somebody is working at home or working in the office have parity that people can self-serve, we can drive better adoption by ensuring those experiences are world-class. And thirdly and most importantly, about agency is how do we empower people to do their absolute best work? How do we unleash this human renaissance and really empower a lot of creativity and innovation going forward? So we have this unique opportunity to lean in here and lead. I know our CHRO, Jacqui Canney, has even changed her title to include AI enablement. So this is your opportunity. I really want you to encourage you to lean in, and this is just a really exciting time. So I believe Abid, we probably have some questions out there. So I'm going to turn it back over to you.

Sounds good, Kelley, and thank you so much to you and to Allan for a fascinating conversation and some really interesting insights. We've got some really interesting questions as well from the chat from the Q&A section as well. Let's start with one that came up a couple of times which is does ServiceNow have automation set up with other vendors...

I don't know if we have Abid online to ask some questions, but we'll...

Are you guys hearing me and seeing me?

Yes, we can. Kelley, your connection is suffering. So go ahead, Abid with the question.

Okay, great. Well, we're doing that. So Allan, let me ask this to you then. So do we have automations set up with other vendors and do our agents, AI agents work with other vendors' AI agents?

Sure. I'm happy to take that. So first of all, do we have automation? Do we have connection points to other vendors? Absolutely. We've built a lot of these out-of-box integration capabilities for our Now Assist generative AI conversational experiences because we know that to answer employee questions and let them take actions, we've got to connect to other systems. So we have that. We also have this new product that I was just telling you about called the Workflow Data Fabric that really does something quite important. It does zero copy integration with all of your enterprise systems. So for example, if you don't want all of your HR data in ServiceNow, you want to keep it in your system of record, but you want the AI agents to have access to that data real time to be able to answer employee questions or take an action, that's what Workflow Data Fabric does. So if you haven't learned about that, I really encourage you to explore Workflow Data Fabric to learn more about how that brings all of your enterprise systems together. As far as agents working together, the space is still pretty new, right? Agentic AI is really something that's only about half a year old in terms of it being mainstream and something that's out there in enterprise software. Right now, there's still some thought as to how will these agents work together across platforms. That's something we are squarely focused on is making sure that not only can you have AI agents from other platforms work with our AI agents and our agentic AI studio but also to make sure we do that in a safe and compliant way, right? Because again, the same guardrails we're building around our agents, we need to make sure that those also apply with other systems agents, right? Because any time we're touching employee data, we have a higher level of responsibility and due diligence that needs to be done. So I would say that that latter part is still a work in progress as we watch this new industry kind of unfold around this.

Fantastic. This is an interesting one. And Kelley, it touches against the second poll that you just actually ran. Where has ServiceNow seen the biggest value add being realized amongst our customers and clients to date especially amongst smaller enterprises?

So that's a good question. I think it's certainly the orchestration of some of the more simple tasks in HR, which gets to a lot of the self-serve. So it's the closed loop on a lot of the questions that people have and agents running what we call the last mile on getting those things done.

And I would also add just one other thing too. I mean, there's certain experiences that we know suffer today because there aren't agents there to kind of help us get through them. I'll give you a good example. Posting a job requisition right, as a manager, right? I'm like, hey, I need to hire somebody? How do I post the job right? We are right now about to roll out our manager job posting AI agent. Why is it important? Because it takes managers 45 minutes. It's frustrating. They don't know their cost center. They don't know what the job code is. Like AI agents can help them automate a lot of that and do a lot of the work for them and really improve the job posting itself and even sometimes educating managers on new skills that may be necessary in jobs that wasn't there maybe a few years ago. So that's a good example. Another great example that we have an out-of-box agent for is this idea of how do we promote talent development? How do we promote good growth conversations for our employees, right? That's something where it's very difficult today for managers to be able to do something like that. They have to collect 360 feedback, which is extremely time intensive and then half the time managers end up not doing it. But if we have AI agents that can automate all of the preparation work, scheduling the growth conversation, collecting the 360 feedback, summarizing the top strengths and areas of opportunity -- areas of development, these are things that are going to transform the way managers have growth conversations. So anyway, those are just some examples of where we see the most interesting customers implementing AI agents as examples.

Great. That's a great connection to the next question, which I think a lot of folks are also sort of scratching their heads on, which is, how do these AI agents differ from the traditional automation that's sort of seen in the HR space currently? And what unique value does that actually bring to the overall employee experience?

Allan, don't you think it's really about explain how you were talking about the closed loop. The taking -- agents able to talk to other agents and pass over as opposed to just a question being answered from a chatbot.

Yes. Yes. And I think -- again, I think the important thing is to start shifting our mindset to think about these AI agents as digital workers. And what do digital workers do the traditional automations don't do? Well, they reason, they problem solve, they experiment and they try to accomplish goals, right, whereas traditional AI is very fixed kind of like it does this one thing. But with an AI agent, as long as it has a goal, and that goal might be something that's been given by whoever built it, it could be something that's given to it by a user who's interacting with it. But once it's given a goal, it can then go out there and use agentic reasoning, which is much like human reasoning in many ways to try to figure out how to achieve that goal, and it can experiment and it can interact with different systems as needed and choose which systems are most appropriate to make that engaging experience happen. It also has the ability to work with both humans as well as other AI agents to try to deliver that outcome, right? And that's something that, again, like traditionally, AI couldn't do any of these things. So these large action models, as people are calling them now, they have the agentic reasoning and when they're connected properly to systems, enterprise systems, they really do become a virtual part of our workforce, a digital part of our workforce.

Great. Great. This question also might be more towards you, Allan, and a couple of folks have asked about it. Right now, what languages are supported in these agentic workflows and AI agents and will ServiceNow be supporting multiple language in the future?

Yes. Look, our strategy is always to be able to support all languages -- all major languages. So from the very beginning of our Now Assist product, we had dynamic translation, and then we continue to invest more and more in organic language support within different models within the Now LLM. And each of our features is at different levels of maturity when it comes to that, but they all do have that multi-language support.

Great. Kelley, you talked about at the end of the conversation about the AI-enabled organization, those 4 sort of pillars that are needed to kind of get to that point. I think it touches on another question that came in here, which is with the evolution of AI happening so fast, how can HR leaders make sure that they're building the right skills and competencies within their own teams to maximize the use of these AI technologies?

Well, I think it's sort of on 2 levels, right? So first is to understand their own business well enough to where AI agents are going to make a difference. And then it's mapping out what are the use cases that have the highest return within their HR organization. And third is, okay, what rules are going to play in that loop. So if someone has a digital twin or we put a talent acquisition process in place where we're going to use these digital agents, how does the person performing the role today going to have to train those agents? What's going to change about their current role? And how do we level them up, that's the reskill or upskill in that role. So it can feel like boiling the ocean if you don't really consider the prioritization of those use cases and where the use of AI agents are going to make the biggest difference.

That's a great point. And it touches on what I'm seeing as another question coming in, around the preparation and preparing for AI agents. And I think, Allan, this might be a good question for you, which is in terms of the biggest challenges, and I think you touched on data and the importance of knowledge base and data being clean. What are the biggest challenges that organizations that work with ServiceNow face when implementing AI, AI agents in HR? And how do we help sort of overcome those challenges?

Yes. So I think a couple of things that I would put at the top of the list as we talk to customers and see how they're going through the implementation process. First, it is about data, right? At the end of the day, any AI is as good as the data that it has access to and making sure that you have access today. So a couple of things there. One, look at the data you have inside of ServiceNow and outside of ServiceNow to make sure you have what you need to be able to really answer employee questions. So for example, if you have a knowledge base, the first thing you need to do is spend a little bit of time thinking about how to make sure your knowledge base is really strong and up to date because you can have a generative AI capability, for example, or an AI agent that specifically is pulling from those articles to maybe provide approval recommendations, for example, but if you don't have solid policies or if you don't have the right knowledge articles in place, it's not going to be as effective as if you have quality data. So first is the quality of your data internally. And we have some interesting tools inside of Now Assist that actually help you with the quality of your knowledge base. That's something to explore as well as using generative AI to actually improve the quality of the knowledge so that you can then improve the quality of the AI agent experiences, right? It all kind of goes full circle. The second thing, as I mentioned, is the connection with other systems because, again, ServiceNow is a system of action or the system of experience for employees. But there's different systems of record. You may have an ATS, you may have a VMS, you may have a learning system and an HCM. You really are going to want to pull from each of those different systems. And so making sure you have the right integration strategy in place. And again, I encourage you to look at Workflow Data Fabric as the potential solution for that in 2025. But of course, having that access and that connection and making sure that you are able to let those agents get access to the data they need to actually deliver the experiences that need to be delivered. So that's the second key thing. But one of the most important ones is get your conversational experience in place. I mentioned this earlier, I'll just say it again, more directly, these AI agents aren't going to be able to interact with and do -- and provide value for your employees if they don't have the conversational experience connected through this omnichannel approach. That's why ServiceNow's Now Assist getting that inserted now and then adding those AI agents as time goes on will make sense. But foundationally, you're going to want to have that Gen AI conversational experience in place and ready to go to be able to support AI agents.

Abid, one thing that we didn't talk about, but I think is important is also the role that ServiceNow is playing in the orchestration of AI agents because many of you have a litany of HR systems in the back end when we talk about the power of integrations. We also -- when we move to agentic AI, the power of orchestration across the enterprise and the multitude of AI agents that will be working in the enterprise. And so that is a unique capability we have to orchestrate those AI agents and also to ensure their efficacy and also the data and the guardrail. So when Allan was talking about Workflow Data Fabric, the ability to pull data from anywhere in the enterprise but also ensure that that data is protected. And that's something that we, of course, need to really think about in HR.

It's a key point. And looking at the time here, I think one more question, which is probably going to dovetail right into what both of you just kind of touched on. Everyone wants to know there's a lot of questions here around what is the current out-of-the-box availability? And what can customers expect in terms of future out-of-the-box AI agents? Maybe Allan, you could speak a little bit to the preview on road map coming up into Knowledge coming up in the summer?

Yes, sure, sure. I mean, yes, 2025, like I said, is the year of AI agents. You're going to see more and more out-of-box AI agents coming online that you'll be able to just implement and use, but we also have our AI agent studio that allows you to build your own agents and of course, all the governance aspects that we've spoken about. So really, there's two different things to think about. Again, one being, let's get that core conversational experience using our AI -- agentic raising capabilities for conversational experiences. That's always step one. That's Now Assist as it's been over the last few years. This year, in 2025, we started to introduce all of our AI agents. So you can take a look and see the road map of what we've already delivered as well as what's coming in the rest of 2025. So reach out to whoever your account team is from ServiceNow and ask them to review the AI agent road map for 2025. And then there will be additional capabilities. Like Kelley was mentioning, we really are the control tower for the enterprise when it comes to AI agents. And that includes looking across all the different systems that are going to have these agents as well. So you'll see more and more investment in 2025 around expanding that and really making sure that we are able to govern and get the most productivity out of the entire enterprise of AI agents -- sorry, the entire ecosystem of AI agents across the enterprise.

We are just about at time here. And so I wanted to just take a moment and say thank you so much to Kelley and to Allan for a fantastic conversation and some wonderful insights. . Just as a reminder for the audience, there's probably so much more that we can talk about, but we can't do it in this amount of time. Please do scan these QR codes for some more information and resources to learn more about AI at ServiceNow along with a data sheet around our employee experience solutions. And definitely, you don't want to forget that Knowledge 2025 is coming up May 6 through 8 in Las Vegas. Yes, we're looking forward to having all of you there and meeting in person to shake hands as well as to talk shop about some of the things that we just talked about today amongst so many other things. Please do take a look and scan that QR code right there to get directly to the registration page and get yourself registered and for more information and for more of what we talked about today, please do visit servicenow.com. And thank you again for joining us today. You all have a great one now.

Thank you.