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

Hi, everyone, and welcome to our Field Service Webinar with ServiceNow. Thank you for joining us. Today, we'll go through how AI-powered applications, self-service scheduling and customer accessible databases can help improve efficiency, reduce costs and enhance customer satisfaction. We encourage you at any time throughout this presentation to submit your questions using the Q&A button at the bottom of your screen. And now I'll hand it over to Chris from WBR.

Thanks, Randy, and Hi, everyone. I'm Chris Rand the WBR Insights, the research arm of the Field Service Event series. This year was our first year producing our self-service industry research report, which was sponsored by ServiceNow. I've been invited to share some of the findings from the report. Before we begin today's session, the report explores how field service organizations are incorporating self-service into their strategies and how they can leverage self-service to drive results for customers and their business. But before I continue, I'd like to introduce our speakers for today, all of whom will be participating in a round table discussion once I'm done. I'm joined by Bulent Cinarkaya, he is the GM of Field Service Management at ServiceNow. He also has years of experience -- deep experience working with Salesforce and Oracle; Nikki Narang, who is Senior Director of Product, Field Service Management. Nikki has built and grown ServiceNow field service management for the last 6 years. He also has experience in enterprise software and customer experience; and Megan Magee, who is the Senior Product Marketing Manager for field service management at ServiceNow. Megan has launched and grown new B2B and B2C products for the last decade. So I just want to thank everyone for joining me today. As I mentioned, we'll start with a look at some of the findings in our research report about self-service and field service, and we'll follow that with a round table discussion between our 3 speakers, followed by a Q&A session before we wrap up the webinar. So just a little background on the research report. Our team surveyed 100 field service leaders from across the U.S. and Canada to generate the results for their report. You can see some of the figures here. As you can see, the respondents were senior leaders in both operations and service and support roles from a wide range of industries and different company sizes. And here's our premise for the report and a key principle in conducting our research. And that's a self-service as an increasingly important part of the customer experience, so much so that customers often expect some level of self-service capabilities now, whether they're trying to resolve a problem or make a purchase or some other action. So it's important that field service organizations learn more about their customers' preferences and identify ways they can deliver what they want in terms of self-service. In the report, we have a whole page of key insights along with in-depth analysis of key trends and a list of detailed key recommendations as well. I'm going to share just a few of the key trends with you today from the report. First of all, that we found that nearly 3/4 of field service organizations are already using self-service tools in terms of scheduling and over half are using customer accessible knowledge databases as well already in their field service operations. So it's clear there is a growing interest to sort of hand off some of these functions to customers where the results can actually be better for them and the administrative and support load can be looped from service teams. But needless to say you can't do that effectively without the right tools. So we have some findings here in terms of the effectiveness and success of field service teams, current self-service tools. We measured success in a few different self-service subjects with different ratings. One of the standout findings was that among nearly half of respondents self-service is very effective at improving efficiency. In this context, that figure is actually strong because respondents were given several aspects to choose from, and this was their top selection. But what stood out even more was how there are some improvement opportunities for self-service and other areas, namely improving retention, satisfaction and upselling. Of course, these are all key service metrics. So what we're seeing is that while self-service capabilities are streamlining some processes, they're not necessarily delivering on all these key service goals. It's clear from the results that optimizing self-service requires new technologies. The problem we're seeing is that managing complex self-service technology integrations is, a struggle for most organizations. But self-service technologies, they continue to evolve. So there will be more opportunities to improve those key metrics. The question is, how can service teams overcome these integration hurdles in order to deliver the best results. So before I hand things off, I want to share 4 of our key suggestions from the report. And of course, you'll see more findings and suggestions in the report itself. But first of all, implementing -- I'm sorry, implementing empowering technologies. So there are a lot of potential pitfalls to self-service because you won't have someone on your team in the driver seat. So you have to make sure the tools you're using eliminate any friction that might mean self-service hurts customer experiences rather than helps them. And that contributes to the second point, which is to drive down the risk of human error. So as you launch your solutions, test and test and test and make sure customers aren't going to run into frustrating roadblocks as they're using your solutions. And third, consider leveraging new AI capabilities. We're all familiar now with the capabilities of generative AI. But working that into self-service functions takes a lot of close consideration. And there are other ways AI can help to make self-service capabilities, better experiences for customers, such as information retrieval from a knowledge databases, which we mentioned. And finally, working with technology vendors with expertise in your industry. So there are industry agnostic self-service tools available, but you might find an industry veteran with experience and background is going to be more successful in delivering on your customers' unique expectations. So now I'd like to turn things over to Megan, who's going to lead our round table with her colleagues, and I believe they'll be discussing our recent field service event in Palm Springs to get started. So Megan, I'll turn things over to you to continue.

Hey, thanks, Chris, for taking us through this fascinating research on self-service. We were thrilled to share this report last month at Field Service Palm Springs, which was actually the 20th year of this event, bringing together field service professionals, and this year, it was focused on the theme of reimagining the future of field service, so very topical.

Bulent and Nikki were in attendance at Field Service Palm Springs. So this next question is for them. What were your key takeaways from Field Service Palm Springs, WBR's annual event regarding the power of self-service and the potential for organizations to transform using these tools?

Hi Megan, maybe I'll start first. First of all, kudos the WBR team for another successful event. I really enjoy field service U.S.A. Palm Springs event, because decision makers are there, and everybody is so knowledgeable. I learn new things every time I go there. So a couple of things stood out for me this year. One is -- remote assistance is part of the self-service strategy. Last year, I remember it was more of a conversation topic. How do we do this? How do we incorporate? Now this year, I saw many customers talking about, here is the ROI we're seeing. Here is how we're balancing the team load. So that was great to hear. And the other topic stood out for me is, we all know there is a global labor shortage. So there was an emphasis on leadership and workforce management, how to keep employees happy, how to lead them, motivate them, so they won't leave the organizations. And of course, generative AI was a hot topic. Those sessions were full house. But on the challenges side, a couple of things still remains as a challenge. The first one is change management and adoption. And of course, including the end users as part of this implementation and post the implementation journey to drive the adoption, which self-service plays a role. And last but not least, the connected operations. So if you think about the self-service, I usually think from end-to-end customer experience, vendor experience and ecosystem experience. And no matter how beautiful channels you provide, how beautiful interactions you provide. If there is a messy middle, if you're not really orchestrating through the enterprise, not connecting the dots, you have silo systems. You got a full shore, customer satisfaction or employee satisfaction, the end-user satisfaction is going to full shore. So that was one of the topic and our conversation with the customers now they want to be more proactive. During the pandemic and everything they have to move fast, reactive. Now they're talking about leveraging proven technologies and applications for other domains, how do we apply to field service and workforce optimization is one of them. So if you think about it, you start with the forecast, what is the future demand. So this is the proactive rather than reactive aspect comes into picture. Once you know what would be the demand, your forecast, then you need to do your capacity planning. When you look at your resources, you have your employees, you have your contractors, right? But also you have your customers. Now self-service is part of the picture. They can get things done on their own, if you provide them the right tools, augment their abilities, right? And the question is, what is the threshold, right? When you look at this resource pool, what percentage or what nature of queries you're going to direct your employees versus direct your contractors or try to deflect to digital channels or provide self-service from mode assistance, then it comes the question. If you do that, the questions your employees are going to get or the work they're going to do is going to be more complicated. Do they have the right skills? How do you upskill them or how do you augment their abilities with more self-service AI? And similarly, if you don't have enough people, you need to hire, how do you hire onboard and train them. So these are the things. I know it's a long answer, but that for me at the event.

Yes. If I can just add a little bit to that. And first off, I want to echo what Bulent said, the event in Palm Springs is fantastic. WBR does a great job and it's a great opportunity for us as software and solution vendors to listen to these amazing leaders, service leaders across all these different industries. I'm just going to delve down a little bit on one of the themes that Bulent was mentioning around employee engagement and employee growth. And one of the areas, again, Bulent mentioned, workforce optimization. We see that being really relevant for service organizations in terms of one of the key themes that we always see when we're talking to service organization is the need to drive employee engagement. And with workforce optimization, the ability to have managers have deeper interactions with their service teams, being able to have feedback loops, closed-loop sessions, being able to identify when someone might need coaching, might need training or even allowing someone to take more control of their career by self-service, training, upskilling themselves, tracking all on the platform. So the manager can reward someone who is taking the time and investing in themselves, taking additional training, going on additional service calls and rewarding those positive behaviors. And one of the things I'm excited about from a ServiceNow perspective, we just announced a new product called employee growth and development. About a year ago, we acquired a company called Hitch Works, which is AI-based skills management. We're using that AI-powered tool to do talent -- to have a talent transformation product within ServiceNow, to drive skill-based workforce management. The new solution is going to help organizations better understand the strength of the workforce and build a skill strategy that's going to help close talent gaps and again, improve employee experience all across a single platform.

Thanks both. Very interesting. So it sounds like lots of promise here, but still a bit of a hill to climb on execution for self-service tools in some cases. But like how Bulent mentioned, there's a great potential to move from reactive to proactive and then Nikki's addition of the flavor around workforce and employee growth optimization to keep the workforce healthy, which is more important now than ever. So since you're both talking to our customers at ServiceNow daily, what are you hearing from them about self-service? How are we seeing our customer base uptake self-service? And what have been some of the results and ROI of that if companies want to undertake this journey?

Yes. We've seen quite a bit from our customers with self-service. It starts with some of the basics of making sure you're a single point of connection for your customers. You're providing consistent experiences for your customers. You could start with a portal with different ways of engagement. We see a lot of value from omnichannel engagement, engaging with your customers on the channel that they're operating in. It could be through social media, through the portal, e-mail, whatever it is making sure you're engaging with them in the right channel. And again, our approach at ServiceNow is, we want to be that one platform for self-service. And we've seen some simple use cases, we're just having knowledge-based articles available to your customers can help deflect the service call. As you go into more advanced use cases for self-service, any one of the great success stories we see is with Xerox, our customer and using a tool called CareAR. All facilitated through the ServiceNow platform, where CareAR allows Xerox call center agent, contact center agent to have a video conversation with the customer and potentially triage the issue in that manner. It could allow potentially a customer in the future to go through their own self-service video instructions augment reality guide instructions for how to self-service and resolve an issue. It allows a technician before going on-site to, again, have a video call and figure out while working with the customer, hey, what parts do I need to bring or having a sense of what work needs to be done to make them more efficient when they arrive on-site. We've definitely seen improvements in repair time per technician per day, reducing the need for some truck rolls, increasing remote solve rates. And once the technician, again is on-site, because they're so prepared for what they're going to see. We're seeing significantly better outcomes when the technicians do go on-site.

I love the example of the Xerox story and how they're utilizing self-service and just wanted to underscore that extra repair time that technicians are getting back from this process per day is amounting to nearly a full hour back of their time that they're able to allocate to strategic activities and additional repairs. So we are really seeing super deep ROI in a lot of industries and a lot of use cases here. And another flavor of that is reducing those truck rolls leading to fewer carbon emissions. So definitely something that can help organizations meet their ESG goals as well, which is something that we're also seeing. Changing gears slightly for a minute to a hot topic that's on everybody's mind. You probably -- if you're on this call, haven't been able to get away from Gen AI. So we want to tackle it head on in this conversation. And we've been having a lot of really interesting conversations around it lately, both as a team and with our customers. We actually had our big customer event Knowledge 2023 last week in Vegas, and had a lot of discussion around the use of Gen AI in field service. So we think there's a lot of potential there, but wanted to provide some additional guidance. So I wanted to post the question to Nikki and Bulent. How do you see self-service capabilities, particularly Gen AI making a difference for customers, service technicians in the field as well as operations teams?

Sure. It's a very fast-moving topic. So in fact, it reached 100 million users ChatGPT just in 2 months, it's unprecedented. And AI was always part of everybody's strategy, but now it seems like everything is on bullet train and moving fast. At field service U.S.A. event, I attended all the Gen AI-related sessions. To be honest, I was looking for more concrete use cases for field service, but the content and the talk track was around what it is, what are the basics, what are the pitfalls, and I was not able to find concrete use cases, because everybody is learning, everybody is trying to figure out and every day, you're seeing new thing. Unfortunately, we didn't talk there, because we were under the media embargo because we announced our Gen AI initiatives last week at our conference, Knowledge 2023. When we think about the Gen AI, we see the potential in 3 categories. One, first of all, it provides the scale that normally you cannot, right. So you give your data, you train, you prompt, and at the end, you generate content or you analyze things and you iterate it, but the biggest promise is on the automation side. So ServiceNow at the heart, at the core is a workflow platform. So integrating Gen AI at the workflow level, really opens up a lot of doors for product teams like us and also for customers to do this innovative things in a self-service fashion, low-code fashion. So the other one is providing digital assistance to every employee. So there are a lot of main tasks that we do every day. If we can have a digital assistant and offload those tasks or get help, that will improve the productivity. At the end, if you look at what field service leaders are trying to achieve, contribute to constant profit margins, keeping employees and customers happy. This helps on all aspects. And the last but not least, one-on-one coaching. So at the conference, our employee workflow teams also announced that coaching aspect. But I suggest really good TikTok to our audience, CEO of [indiscernible]. He was talking about incorporating Gen AI to [ conconomy ]. So if there are studies -- we all know the [ Balcar Sigma ] shows the -- how the 30 people classroom is performing. But if you can provide the same class one-on-one coaching, your below average student performs at the 98 percentile compared to previous report. So you can really, with the Gen AI and one-on-one coaching, you can scale this. You can provide this coaching to your managers, to your employees. So automation, augmenting people with digital assistant tools and one-on-one coaching. So that's why at the conference, we announced this, the short-term. We provide an access to third-party LLMs, specifically Azure OpenAI and OpenAI. So you can call content generation, summarization, Q&A, generic prompts all the way from workflow level. We also announced Now Assist, it's going to be part of our search. It's going to be part of our bots technology, so that no employee has to go figure out which workflow they need to select or where the answer is. This is going to help one-on-one coaching. And also, we announced cogeneration as well. So with the partnership with StarCoder by BigCode, and we showed the live demo at the keynotes. Our customers can generate code, but just telling what kind of code they want. So in terms of Field service. Nikki, do you want to talk about how our teams are leveraging these platform-level capabilities and bring in the field service?

Yes.

Yes, let's get into some specific use cases as well.

Yes, absolutely. So we see AI making a huge difference in field service and service organizations. We've used traditional AI in a number of ways here at ServiceNow field service management. We use AI to recommend knowledge articles to both to customers and to technicians in the field, having those -- when you're offline, you may want to know here the 5 most recommended knowledge articles for the work that I'm trying to accomplish right now on this customer site, we can use AI to recommend those knowledge articles and expose them to a technician. Similarly with similar work orders, hey, I'm working on this work order. Here is 3, 5, 10 work orders that were very similar, that's all generated via AI. We even do things like clustering of work orders using AI and trend analysis techniques to figure out -- this is a cluster of work orders that are similar to each other and you're able to do that analysis and understand what is the trend, what's happening? Why is it happening? Where we see Gen AI really taking this to the next level is, let's say, now you have that trend or that cluster of work orders. And it's a specific type of problem that you're seeing in the field, you can have Gen AI generate a summary and create a knowledge article for that cluster. So not just having that cluster, but using Gen AI to tell you here is how we resolve this issue the next time we see it. And then again, being able to now use AI to associate that knowledge article when that same similar type of work order happens in the future. You talked about Gen AI again for generating closed-loop work notes, resolution codes, symptom codes. We have all the information that a technician is doing on a work order that they're docking in the old device. So parts they use, notes between the technician, the customer, the call center agent interactions the customer had via chat, via the portal, being able to actually generate a summary of that work order once it's completed on behalf of the technician, the technician can of course go edit, make changes. I mean now that we've got these Gen AI generated summaries, you're saving time for the technician. You're making sure all the work that was done, the most relevant work is in that summary. And that summary now, the next time someone has a similar work order, when we attach that similar work order to let that take know, hey, this is what was similarly done. They've got a great summary that's going to be consistently done, easy to read, easy to consume. And again, reducing the burn on a technician to, hey, here is a similar work order. I have to go through a week long history of events. I can read that summary that was -- that came from Gen AI. And we see other opportunities as well to grow the AI footprint in field service in terms of -- we mentioned using AI again to generate skills needs and shift schedules predicting gaps in service. There is -- the use cases are endless. I would say, like what Bulent said, it's growing quickly. And every day, we're hearing from our customers, new potential use cases. It's really an exciting time.

Yes. One thing I want to add. So for the functionalities that we want to iterate fast, we do store releases. Normally, we have 2 family releases a year, but we can do 4 store releases a year. So our plan is after Vancouver release start putting generative AI templates for field service management on our store. And again, these are templates customers can take it, make it their own. In fact, we're going to be building these templates the way customers will build themselves. So they don't really need these templates from us. It's just a starting point. But the things you can do with the platform level capabilities we just announced is limitless.

Yes. Thanks for that good overview. So we're hearing a lot about that ability to enhance human interactions and take some strain out of the day-to-day for the customer, for the technician, for the agent and speed that time to productivity, but also it can be a retention play if you're making the job of your field service organization a lot easier. So I like the call from Nikki to focus on the most relevant work. And it really is an exciting time to be operating in this space, growing that AI footprint, but I know there's a lot of focus on doing it the right way as well. So just moving us along. Any parting thoughts, Bulent and Nikki, that you want to leave the audience with today, knowing your fresh off of dozens of interactions, maybe hundreds of interactions with your field service customer base last week. What is top of mind for you? Similarly, what should be top of mind for other field service leaders as we enter the second half of the year?

Not specific ordinarily about self-service, but I want to talk about the change management concern that I mentioned at the beginning of this conversation, because the entire success of this digital transformation is a boils down to successful project management, successful change management. What I see -- and again, this is one way of 2 things, successful go-lives and implementation starts with bringing the stakeholders together and really writing down what is your goal? What you're trying to achieve with this project, with this digital transformation, because people always overestimate what they can do in their first release and then underestimate what they can do iteratively. What happens, if you don't write down, then feature creep starts coming, the end goal keeps moving and everything holds apart. So once you write down what you need to do, you need to assign accountable owners across the enterprise, right? These are the people, leaders you pick, could be cross-departmental, but they're going to drive the success. And of course, always, you have to have the KPIs that you know when you say you deliver, you deliver, you can measure it. If it is not measurable, it's not a good target. So after that, it comes how do you make it operationalize, right? So they're really picking the right partner, implementation partner and make sure when you pick the partner, they are certified for your vendor. And those certified people are on the ground working on your implementation, not the people certified working somewhere else. And also bringing your vendor as well. So we usually work with our customers. We have monthly check-ins, so that we can share best practices with them. We can share a road map with them, correct course or learn from them because we work with multiple customers, right? So when you do that, the go-live line become successful. And then post go-live, similarly, you're measuring, right? So make sure, first of all, you have access to your data. If you know where you are, you can set KPIs, measure and get better. If you have silo systems, it's really hard to put a KPI and move forward. And keep managing that, incorporate the end user as part of this journey as well. So they feel ownership and that helps the adoption as well.

Awesome. I feel like that was a quick get started, everything you need to know for a successful implementation and beyond in 2 minutes. So thanks for that to wrap up Bulent. With that, I wanted to open up the Q&A and just see what's been on your mind throughout this discussion. And if you've been holding a question, feel free to drop it below for us in the chat. But I wanted to take the first question that came in and just keep rolling with this Gen AI train. So Bulent, you were just talking a little bit about getting sort of implementations and measuring success for field service in general. But if an organization wants to get started specifically with Gen AI, you did mention a little bit about how we're going to templatize that and make that more of an iterative process with our store leases on the ServiceNow side? But from an organizational standpoint, what are the top recommendations that you would have for field service leaders looking to get started here?

Yes. Organizations and in fact users have rightfully a lot of concerns such as like cost, the data sources, reputation, trusting the machine, poor response quality kind of concerns. When it comes to using from the enterprise, there are 2 aspects. There is the public generative AI solutions out there. Keep in mind, anything you use that tool can be public. So there are some stories, some large organizations put their code base and generate the documentation and now their code base is publicly available. So you need to take a look at this from what is available, what is private point of view. For that reason, working with the vendors like us is important, because day in day out, we look at what is the scalable, secure, easy way to integrate with these solutions. Our first version, we provide access to third-party language models, large language models via API. And then mid-term, we're going to make this license LLMs available. In the long-term, we also announced partnership with NVIDIA. So we're going to use their infrastructure, their technologies to build service now LLMs for our customers, so that their data, their LLM is going to be specific to them.

Okay. Great. And speaking of the secure way to do this, a question came in from a participant. They're feeling like this is exciting and all, but what are the pitfalls of AI implementation and rolling out to a larger user base that we need to stay on top of, and like a short guide for how to protect your users and protect your customer base in that way.

Yes. Definitely, I mean, at the platform level, we're thinking about that as well. So we're putting corrective APIs, make sure if there is any bias admins and users can step in and retrain adjust the responses as well. So this is, again, a fast moving area. Everybody is looking, what at lot of the guardrails, what are the securities and tools that we can provide. And we're taking this seriously and working closely with customers. I don't know, Nikki, do you want to add anything?

I think it's also just starting small, get those incremental use cases. I feel like your proof of concepts and involve your technician or service organization in this journey, making sure they're seeing the results that they are expecting to see and going from there. But closely monitoring what you're doing, how it's being used, how it's being adopted with your organization will make sure that you see the results you want to see.

Yes. The proof of concept before scaling is a super important and worthy watch out before scaling and going big. So one last question that came in a little bit more on the grounding us in measurement side. So somebody asked both Nikki and Bulent mentioned KPIs in this conversation several times, which ones are most critical to track for our organization and how do you go about deciding that?

This is a fun question, Megan. We just -- we had our Knowledge -- ServiceNow Knowledge Conference last week. We had a product advisor counsel for field service, where we had a handful of our Customer Advisory Board more or less on-site going through a KPI conversation and the diversity in what KPIs are important, 2 different service leaders in different industries or maybe the same industry is staggering. And I think one of the things that's humbling for me is to [Technical Difficulty] service leaders constantly as to what KPIs are most important to you and why it can go from equipment uptime to technician efficiency to travel time, mean time to resolve customer satisfaction. There is so many that could be critical to truck. I really do feel like it's going to vary on what you're driving towards what your business goals are, what you're -- how you're trying to transform your service organization and finding the right KPIs to measure and increment on based on your particular goals as a service organization.

I want to make a couple of things that I mentioned while trying to answer this. I talked about the business drivers for field service management, right? So reduce costs, contribute to profits, keep employees happy, keep your customers happy. This is easier said and done. And actually, you can never be done. You can always get better and better. But it requires a delicate balance across the enterprise different initiatives. So you need to balance, right? So which one are you going to balance that goes back to my answer related to change management. First thing, I said write down your goals, what are you trying to achieve in this business transformation. Once you write down dispose, you're pretty much balancing different initiatives across the enterprise-related to these business drivers, right? And of course, based on these, you can set your KPIs. Of course, in order to see the KPI results, you need to connect the dots in terms of no silo systems. And the other thing is KPIs are going to tell you what happened. CSAT is x, truck rolls is y. But they're not going to tell you why this is happening. It's just going to tell you what it is happening, right? So for that reason, in fact, one of the -- our latest release, we added process optimization to our product portfolio. So the field service organizations can take a look at these KPIs and drill down and answer the why questions as well and figure out where the opportunities are, where the bottlenecks are so that it can go fixed those to improve the KPI results.

Okay. I love it. And building on that, we just got one more question across the line. As you were talking about that. It was just around -- we have a lot of data that's growing daily, and it's a little bit of a mass. How do we get the organizational visibility as well as range that data to get visibility to these KPIs.

So in terms of -- Yes.

I know there's a little lot there to unpack maybe Part A and B, both the organizational cross-work buying as well as the visibility and the growing data standpoint, but...

I think part of it is the first off aligning on those KPIs, and you have different people across the organization where we don't want to see different things. So making sure ServiceNow platform is great for this where you can have different dashboards, you can personalize your own dashboards, but then there's also this need for how do I want to receive that data. It's one thing to have a dashboard set up, but you could have a CEO who you don't expect to go visit a dashboard on a daily basis, on a weekly basis, even and it's -- do you have the right tools in place or the right processes in place to e-mail that report out or it's a quarterly meeting where this is presented. But again, I think to me the different levels of data based on roll, the person looking at dashboard on a daily basis is going to want to see more granular thing, something at a higher level, less great and making sure you account for those situations and then how you receive that data? Who is going to be logging in, if you're a ServiceNow customer to the ServiceNow platform on a daily basis, on a weekly basis or not lugging and it needs to see that data in a different tool in a different way and being able to export that data, again, very easy service now to generate a PDF and have scheduled e-mail going out to your CEO once a quarter, once a year, but again aligning on of the KPIs, aligning on what different people in the organization need to see and then how frequently and where do they need to see that data.

Yes, definitely. I mean, as Nikki said, you might have a lot of data as long as these data is not on silo systems, you're in a better shape. It is a silo system, it's really hard, than your KPIs are not going to reflect or you might not even able to show the KPI. If they're connected, then KPI will drive which data you need to get access. And again, going back to my process optimization answer, that's just the starting point. Once you start showing what information, people are going to start asking why this is happening. So be ready to be able to drill down and explain the why side of KPIs as well.

Okay. Great. Good insights there. We had another one come across in the chat. How concerned should we be about [ hallucinate ] trends with AI. How do we ensure that output is real and accurate and thereby living up to our brand promise?

Yes. I know it means I'm an AI expert or anything like that, but based on I'm learning as based on what I hear is that if you think about the public Gen AI, right, it's trained based on every possible information available on the Internet. So you can have many different kind of conversations. And when it reaches a certain point, it starts giving you answers making things up and they called it hallucination. In the business context, you're not really having the conversation that you have that type of conversation, you're having a business context conversation. And if you leverage summarization Q&A kind of parts, but have an LLM trained with your enterprise data, the chances of having these kind of hallucinations on this limited set of data compared to all the data on the Internet is low. But again, providing the right APIs and guardrails to enterprise customers is a top priority, so they can fine-tune these things.

Great. We've just got another one in -- John mentioned, I think one of the advantages of ServiceNow is that not only can you produce and display KPIs, but alerts and notifications and be set to note 5 parties of an exceptional condition. We do not have to count on a human to review a dashboard or scoreboard, but the application itself drives the action with generative AI this has the potential to be richer. So some nice commentary there.

Yes. John helps us a lot. So he is part of our product advisory council, Xerox, he is a design partner. And he is really right on this. The traditional ways you put a dashboard, somebody looks at it takes an action. That is there. You have the ability to automate this, definitely, Gen AI can take the actions and interpret this data and connect the dots.

Yes. And I know testing and having guardrails and those proof of concepts that Nikki was going back to, I know we did some tests internally as well where we were trying to see how much of a support function could be managed through Gen AI and not until we've had 100% accuracy, 100% of the time with our vendors, where we -- are we willing to transition support to that model. And so that's something that you can think about and keep an eye on with your organizations as well. So we'd love to wrap this up for today. I think that was the last of our questions. Thank you so much to both Chris at WBR, as well as Bulent and Nikki for this awesome informative conversation reaching across all areas of field service and the hot topics they're in today, and thank you to all of the participants on the line for tuning in with us.