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

Welcome, everyone, to our webinar today. My name is Ajda LaPrad, and I am with ServiceNow and will be your host today. So today, we're going to talk about putting people first and how humans plus AI help elevate the customer experience. And we will actually also be having a customer with us share his story on how he's been doing that with Konica Minolta. So let's go ahead and get started. So for today's agenda, we're going to dive into how humans together with AI elevate the customer experience. And we'll also be talking about generative AI, which we've been hearing a lot about in the news recently, and how you can use it to improve deflection, improve productivity and optimize your business processes. We'll also have our customer, Izzy Sanchez, from Konica Minolta talk about how he has worked at Konica Minolta to really unlock the value using our ServiceNow customer experience portfolio and AI solutions. And then we'll wrap up with some of the lessons that he's learned along the way and what the future holds for himself and at Konica Minolta. And of course, we will save some time at the end for questions and answers. [Operator Instructions] So I want to kick things off with a quote here, "Generative AI working alongside humans can have a significant positive impact on the productivity and retention of individual workers." Let's kind of let that sit in just a second here, right? I think we've been hearing a lot about generative AI and AI and how we can make the experience better as a whole. But really, it's about empowering our individual workers, our employees to really deliver those meaningful and seamless experiences for our customers. And generative AI can really help your people, your customers accomplish more in the same amount of time and allow them to focus on that meaningful work. So we're going to talk about generative AI as well as AI as a whole. So let's go ahead on to the next slide, where we can talk about how AI has really been able to help accelerate better outcomes and experiences. Really, as it relates to the customer experience, we've been able to help customers get those better outcomes, such as being able to streamline operations to resolve customers' issues quickly, being able to engage customers with easier and smarter service, empowering agents with real-time guidance and being able to extend those seamless experiences out in the field. So you'll see that there are AI capabilities that we have for each of these areas listed below, and we'll go through some of these, not all of them today as we won't have enough time, but we want to be able to help share how some of these really have come to life in Izzy's story. And that will definitely give us what's possible here with AI and generative AI. So brief introductions. As I mentioned before, my name is Ajda LaPrad. I am in product marketing for our customer workflows team at ServiceNow. I have about 15-plus years in the enterprise software space as it comes to customer experience, CRM and B2B integration. Now Izzy, please, welcome, and please introduce yourself.

Hey, good morning, everyone. So it's a pleasure to be here. My name is Izzy Sanchez. I'm the Director of Service and Support Systems. I've been -- I joined the IT world back in '95, and I transitioned to the imaging industry back in 2001. And when I started here at Konica Minolta, I basically started in the early days of our IoT deployment for our connected devices. And since then, I've kind of been on this trajectory to this point here. And so currently, I manage the contact support centers at Tier 3 level support, so advanced support from -- as it goes to Japan and the engineering teams. I head the IoT team, so all of our connected devices, pushing firmware, over 150 servers in our data center that I'm really responsible for, the automation [ out of this batch ], all of that good stuff. I'm also part of the analytics team. Also have the technical writing team, we create bulletins and knowledge and all of that good stuff. And then our QSS team, which is our development team and kind of -- the engine behind ServiceNow and our integration here. And so we -- I currently manage this top level support in the solution support division. However, we have around 1,200 direct technicians for our field service. And I believe at the last -- kind of somewhere around 2,500 technicians in our indirect channel. So it's a pretty big organization. Konica Minolta, if you don't know about us, we're 150 years young. We celebrated our 150th year in business this year. And I guess, it's hard to imagine, at a certain point, cameras were breaking and they were technology, but they were, and that's how kind of we broke into that back in the 1800s. And we're currently in 150-plus countries and we're a total of direct employees of 43,000 employees. So we have about 77% of the growth. We have some sort of presence pretty much all over.

Oh my gosh, 150 years young. That's for sure. I love that -- and growing, which is fantastic. So we're going to run a quick little poll before we really dive in here, and we would love to know from our audience as well -- we'll definitely be speaking to Izzy about this. But we'd love to know from our audience what -- is your organization currently using AI? What are your plans for it here? So how are you using AI today to elevate the customer experience. Some examples might be virtual agents using predictive intelligence. Go ahead and click through some of these if you're using AI as well, and then make sure that you click on the submit button to make sure that we can see your answers. But obviously, everyone is on a different path right now when it comes to AI and generative AI. And I think when it comes to the customer experience, we're all still navigating as well what kind of use cases, right? So we're curious to see what our audience is seeing over here. And make sure that you do remember to hit that submit button. All right. So let's see here. For the majority, we have not yet -- okay, not yet, still exploring use cases, some AI, but not sure yet about generative AI. So I think this is really helpful, and we're going to make sure that we touch on some of these areas so that hopefully, we'll help you as you're exploring and navigating your journey as well. So let's go ahead and click on to the next slide. So we are definitely learning more and more about AI and customer service management. And Izzy, we'd love to learn from you, how are you using ServiceNow's Customer Service Management today? Tell us what led to your deployment of CSM and how you're making use of it.

So when I got promoted, my first task was -- I was told, hey, you're on an older version of Remedy. It's played good security, and you have to fix it. And they gave me a very aggressive time line and -- something like 6 months. And there were a lot of bets occurring internally, like, no way. And I'm happy to report, yes way, we basically kicked off our project back in February with our technology partner, [ Insource ]. And by July, we basically onboarded our biggest customers that represent $100 million worth of business for us or their tickets. And then by basically September, we brought everybody else on board. Initially, what we did was we targeted our open cases, right? So we launched and said, hey, we're going to use -- basically port over all of our open cases. And it was almost 6,500 cases, meaning -- working, right, so these are cases that somewhat had just opened, moved over. And then what ended up happening was that pretty quickly, we started to see the benefit because of the Agent assist and some of what you guys call classic AI. And then we decided, at the time, when we ported the 6,500 cases, we were going to live in Remedy, which was paired to our existing AI platform. However, because of all the AI built in and how we started surfacing data and marrying information and our advisers, they became proponents. And they said, hey, can you -- can this -- can we bring those tickets over here because we want access to that? And so pretty quickly, we were able to move those tickets over. And again, like I said earlier, they had made some bets in here that it would not happen. [indiscernible], thank you for reminding me, that they said it will take you 3 years, and we were able to do like I said, in 6 months. So in addition to moving those tickets over, we basically went with Now Mobile, which made a big difference. So our technicians can scan barcodes and again, it's about reducing errors. And quickly -- again, we're in the minutes business. I've said that a couple of different times, right? So more minutes we can get back. We integrated our CMDB data, so we know the equipment that's out there. We integrated all of our IoT devices, which are over 0.5 million devices, and we're collecting all of that telemetry data from there. And then we implemented our AIRe Link, which is our assisted reality platform. So we put all of that in, and we've created this beautiful gumball that works very well for us right now. We're very much a fanatical.

That's amazing. That's a lot of new capabilities and a lot of integrations in a short time. Well, congratulations on that and really excited to hear more on how it's been since that deployment. I want to highlight a few more here on some of the capabilities that you touched on, right, Agent assist and so forth. What you'll see here on the left-hand side is a lot of the technologies or AI, if you will, that we've been investing in for over, gosh, 6-plus years at this point. So we've been in AI for quite some time. And we've interwoven these technologies throughout our platform. So we want to make sure that customers like Izzy are being able to use AI ethically today, and we know that we'll continue to use our AI capabilities and generative AI technologies to provide some of those impactful outcomes for customers. So if we head on to the next slide here. We are now interested to learn a little bit more about -- from our audience, what are some of the AI capabilities that you're most interested in learning about today? So on the left-hand side of that screen earlier, you saw conversational intelligence, search intelligence, predictive task intelligence, document intelligence, analytics, intelligence and operations intelligence. So go ahead and select which ones you're interested in learning about because we're curious, we want to make sure that we cover some of them. And make sure you hit that submit button. [Operator Instructions] All right. Let's keep on going here as they come in. And you'll also see we have resources available, so make sure you can access and download resources from the resources panel at the bottom of the screen. And once -- you'll see -- you'll have another opportunity to submit a survey at the end of the webinar to let us know how we've done. So we'll just make sure we'll cap on that towards the end. So let's go ahead and show the results here of our poll. All right. So we're looking at, let's see, predictive and task intelligence as well as conversational intelligence as being the top capabilities that the folks here are wanting to learn more about. So that's perfect. So we'll make sure we touch on those. So if we go on to the next slide here, what we've highlighted here actually are -- is perfect based off of our whole scenario. So we're going to be talking a little bit more about conversational intelligence, predictive and task intelligence as well as document intelligence and how Izzy has actually been able to work at Konica Minolta and bring those to life. So he'll share some great use cases there. So let's go ahead and get into it. So Izzy, can you share with us how you're putting AI to work at Konica Minolta?

So based on that conversational intelligence, for example, so the Agent assist is a perfect example. So when we have issues, right, someone calls in, my machine isn't turning on. My machine isn't booting up. It's getting to 25%, black screen. All of those things are the same issue. And so through the Agent assist panel, when our advisers, which is your classic AI, when our advisers go in and type any of those features basically or any of those -- sorry, symptoms, it basically returns and groups these cases back. And that conversational intelligence has been pretty impressive because, again, from a traditional standpoint, you wouldn't think of black screen and basically not booting up or getting to 25% for -- would be the same thing, but they're the same exact issue. The other thing that we're actually exploring right now is Document Intelligence. Document Intelligence is pretty important for us because otherwise, devices come equipped with some car machine management list. And that machine management list is pretty much like the machine's DNA, the digital DNA. And now picture what our advisers are looking for, it's almost assisted. To make it into -- turn it into layman's terms, it's if our machine is experiencing some sort of configuration problem, let's say, right? This thing is in a 6 [indiscernible], about 40 pages. We want to be able to surface that quickly. And it's like the blood panel, right? Hey, this is my cholesterol, right? This is all we're interested in. So that's very impressive that, that capability -- we're going be moving that to production pretty shortly. And last but not least is the Predictive Intelligence. Again, so we handle all sorts of different type of cases. And the goal is that the Predictive Intelligence can automatically start, like, auditing cases and try to basically say, hey, there's something way out here that you should be looking at. Like we have something called CAR, critical accident report. So the Predictive Intelligence, the conversational, all of this AI is kind of coming together and intersecting and basically helping us surface if we happen to miss any of those types of cases. So it's very interesting of what we've been able to do with the AI.

That is truly impressive, I think, especially around the conversational intelligence front and the predictive intelligence here. I can only imagine, as you're going through these CARs, right, how can you help prevent future issues that might happen, especially if you have like legal, right, ramification? So how can you audit those cases and provide coaching to your technicians and to customers in the future to be able to mitigate all of that. So that's really exciting. We'd love to also talk about how your agents are using the CSM Configurable Workspace, right, to display the telemetry data in all of your IoT devices. Can you tell us a little bit more about that?

Yes. So IoT, for those that are not familiar with the term, is Internet of Things. And basically, what it means is our devices are connected to our cloud. And by being connected to our cloud, we can basically perform a multitude of tasks, right? So we've been -- we've kind of been in the space with automation for a very long time. Back in 2008, we were intelligently dispatching technicians, no interaction, collecting data for billing, collecting -- knowing when the device needs something and sending it out. So these IoT devices, they basically -- they are a wealth of knowledge, and they basically feed the system a bunch of data. What we've done with -- in the agent -- in the Configurable Space, right, is that we created the telemetry panel, and what that's allowed us to do is to target very specific, high-value datasets. So for example, firmware, error codes, consumables, right? Customer calls in and says, hey, I need something. We want to be able to serve them in real time and make sure that from our perspective, right, I'm not talking about from the customer, that we're shipping them what they need, right, not what they ask for because again, you got to have tight inventory controls. When we started, for example -- so you see that consumable tab there. When we first started this, we used to have about $10 million worth of inventory at any given point at customer locations so that they would have what they need. By leveraging this IoT data, we basically have almost just-in-time inventory out there so that when the customer calls in -- we usually tend to ship it before they know they need it by having this IoT connected device. But again, it gives us the ability to see, oh, yes, I see you calling about this. We're going to go ahead and get that out or usually more than likely, that's on its way. So it's close to 600,000 devices. So as you can imagine, that's a lot of data that's helped us. And by having the telemetry panel there, again, being in the business of minutes, I've reclaimed something between 5 and 15 minutes. Some of that information will take us 5 minutes to [indiscernible] for, go here, go there. So by having it all here at their disposal, it makes executing quickly. From a experience level, our advisers now tend -- they don't have to be as skilled, right? I have guys out there that have been here 30 years. They know everything, right? What this does is makes my guy who's been here 6 months sound like an expert and have that harmonized voice when we support a customer.

That's amazing, and you get rid of that swivel chairing issue that I think a lot of folks encounter these days. Can you give us some of the examples here that we have on the screen that you can talk to a little bit?

So this is a good example. So this is our devices firmware. So anybody else in manufacturing or even in IT, if you're in break/fix or you handle switches or servers, firmware is a big thing, right? That's the operating system of our devices, usually our IoT components. And so here's a good example. So firmware, we've always had that capability to find that information. But the issue is that where is the return on investment, right? I have a call queue. I have 100 people waiting to get support. Am I going to have my adviser go find this information, which is accessible, but it will take them about 15 minutes. Find it, what's the release notes, when was it released, what version is this machine on. There was no return there. So it was just basically incredible information, not right now. And by leveraging ServiceNow and this integration capability with IoT, we're actually serving now. So when the customer calls in or a technician calls in that's really our customer, we can see what firmware version the machine is on. We were able to leverage the CMDB capabilities in ServiceNow to build these tables out so it gives us synopsis. So my guy who's been here 1 month, who probably doesn't even understand what firmware is, he sounds like an expert when he's communicating with our customer, right, with the technician, oh, well 2 versions ago, we released a [indiscernible] certificate, SSL certificate for that machine. So again, these are things that it's not just the time reclaimed, right? It also impacts morale, job satisfaction. Well, usually, people that are in service, we tend to chase that fix hit, right? It's like, I fixed it, yes, it feels so good. And usually, it takes 3 to 5 years to experience that. And what we're doing now is bringing that all the way down to our Tier 1, less experienced folks. They sound like experts, and they're happy, they're fulfilled because we're giving them all these tools and resources.

Well, I think that's fantastic because we -- not just in your industry, but a lot of industries right now are facing like talent shortages, right, and skilled workers, and the onboarding time to ramp up someone new can be quite the investment and take a long time. So to be able to get your newer folks up to speed quickly and take some of that 10-year knowledge of your more skilled workers and be able to bring that to the forefront for the new workers, I think that's incredible. And that really helps address some of the talent shortage issues that a lot of industries are facing today.

Yes, definitely.

So I know you've been using some of our classic AI or traditional AI as some folks call it as well, such as Agent assist. Can you talk a little bit more about the value that you're getting so far?

So it's basically the more you feed it, the better it becomes, right? So we've basically gone from -- we've had 100% increase in productivity. So remember, we're a top level support. So the traditional service -- my guys can be on the phone for an hour with someone trying to get that machine back up and running. And basically, every adviser right now at minimum is getting 3 calls per hour. So we went from an hour-long call at times down to sub-20 and actually even less than that since we initially kicked off these conversations. Some of the other things that we wouldn't have been able to do is, for example, we have our assisted reality platform. So that's -- again, our adviser comes on, we're able to create this virtual visit. And because -- the way that the CMDB and the way that ServiceNow basically allows us to integrate all of these pieces together, we can now kick off a session, see what they're seeing on site, get that feedback, take that data, feed it to the ticket -- because I know there's FaceTime, there's Zoom, there's Google Meet, there's 1 billion ways, launch a visual support ticket. The question is, when you do it through FaceTime, when you do it through Zoom, who's going to find that data in the future? How are you going to mine that data? How are you going to present that data? Because your customer wants to know what you did for them this year, right? And if that data is somewhere else, it's useless. By integrating our AR platform in, we're actually able to have it in the ticket, reference it, click it, look at a video. And it's creating a system for us, a closed loop like iTunes-like system where in the future, that ticket will have more value to our customers. Oh, yes, that's right, Konica Minolta helped me this time. Let me see how I did that. So again, it just creates this incredible closed loop, for us at least, service loop, where we can service. There's post call postmortem value, which is unheard of, right? We're done. You helped me. I don't want to hear from you again. But again, our equipment goes from these little, small desktop appliances to machines you actually walk in, imaging, MOBOTIX, which is our security, AI surveillance. You name it, we're in it. And again, service people tend to be very resourceful. You teach them once, teach them how to fish and then you keep a record of it, I guarantee you, they're going to go back and be self-sufficient. So it's been incredible basically.

That's amazing. And I think being able to collect that data like you were talking about also helps those agents in the future be able to service similar cases in the future as well. And I think with Agent assist being able to surface all those similar, like, cases or knowledge articles with that information also empowers them to work faster and easily when you have future incidents happen like the ones that you've described.

Yes. Well, it's -- again, with the Agent assist, just to not harp on it any longer, it's just the way that we're able to avoid red herrings, right? An adviser -- someone may call in initially on a noise, right, but the issue is much rounder and there's buried information that has high value to resolve this issue. The way Agent assist goes in, and it's almost magical the way it goes and it brings it up. And again, we look for hallucinations, right? We want to -- especially my advisers, they always want to prove the system wrong. So up to this point, they haven't been able to. Oh, we've got a weird one, right, and will go and look at it like, keep reading, keep reading. Oh, no, it was right. Yes, look, right here, here's the resolution. So again, the Agent assist is pretty incredible. It's really helping us.

Yes. It's like Jimmy Cricket to help you. I love it. So we talked a lot about AI and how you're using traditional AI. What are your thoughts around generative AI?

Yes. So we have big plans. So we're currently not using your Virtual Agent. So we wanted to lay the groundwork, wanted to have all this integration built in. And so now what we're working on and we're basically -- it's actually in development, and we're actually actively working on this, is to have the virtual assistant be able to -- so when someone calls in, currently, we're taking all of these steps. Here's your firmware, here's this, here's that. In the future, we don't see a need for that anymore. What we see is the ability to kind of call avoidance and basically have the virtual agent say, hey, you're calling on this machine. We see it has this problem. By the way, your firmware is out of date. Do you want us to update the firmware? And oh, by the way, you're not trained. Do you want us to give you that link? So these are all these pretty incredible capabilities that are coming. The other thing is -- so every adviser gets a 3.5-minute post case wrap-up, right? And so meaning they collect all the data and then they have to debrief the ticket and kind of wrap it up. So that 3.5 minutes, I can regain with the gen AI summarization. And if I can get that 3 minutes back, right, those 3.5 minutes, every 5 cases, I'm basically adding an additional ticket, that additional bandwidth per agent, right? So multiply that against 1,300 advisers in the field and all of our support desk, right, across all of Konica Minolta, it's really going to ramp up productivity. The other intangible here is that we have a harmonized voice, right? So as we start to debrief, as the virtual agents starts to serve up this data, we have this unified voice because I have all of these advisers out here, right? And they're writing a case, again, went up to 25%, this, they're all speaking in their own language and their own interpretation of the situation. Post-case summarization creates almost like harmony or music-like, and every article starts to become more refined and reusable so -- in a very professional space.

I like the analogy to music and harmony. But yes, I think if I'm to paraphrase, really, it helps to reduce and minimize errors and provide consistency, right, I think, in how these cases are being reported. And honestly, I think with generative AI as well, you're improving productivity. Again, you're also helping ramp up new agents a lot faster and get to speed faster on the incident itself so they can start helping the customers directly. So yes, that's huge. So if we go into just kind of like the return on investment that you've seen so far with CSM and with AI, I would love to have you talk a little bit sort of like kind of wrap up everything that you shared with us so far.

Yes. So the big thing, again, it's 100% improvement in productivity. Our benchmark has changed, right? So before, we were kind of all over the place and was always hearing, hey, this is really hard. This is why it's taking me so long. We've actually increased our productivity by 100%. Very minimum, we're hitting 3 very advanced, Tier 3, machine is probably smoking or in pieces and getting 3 calls per hour. The other thing is, again, we've empowered the agents. So the agents have all of these tools. They feel more confident when they're engaging the advisers -- I mean, our customers, our technicians because the technicians are our customers. But in addition to that, you're providing this level of support, you're increasing confidence in our products. And you're basically positioning Konica Minolta more as a technology partner, not afraid to embrace the future of AI and gen AI, for example. I'm not sure if I mentioned this yet, but again, it's very important to explain here that it's not that AI is going to take over my agent's job. It's not. It's going to allow them to be more efficient, more effective, deliver more consistency, reduce their level of stress by 100%, right, because they have all these tools at their disposal. And another area is we've improved accuracy, right? Because with the Now app, with the ability to scan our 13-digit alphanumeric serial numbers, you don't know how long that takes. The fact that once you scan that 13-digit number, we find it, we're calling about this. It's here, it's in the system. We see your problems. We see you're trained. We see you're not trained. Training is a very critical part we need to spend a lot of time on. But if you know if someone is trained or not trained, you basically meet them where they're at. If they're not trained, basically, you're going to do some hand-holding. You're going to take some additional steps. You're going to be little slower about it all. If you get an expert, that guy doesn't want to sit there and talk and doesn't want the banter. They tend to be, hey, I'm looking for this information. Here you go. Thank you. Have a nice day. Moving on to the next one. So again, the productivity between now -- and again, for us, for Konica Minolta built around ServiceNow, we're kind of creating our own iTunes service experience, kind of to put it in layman's terms.

No, that's perfect. And I think with leveraging AI not only to help guide and coach your agents to be able to meet customers where they're at, right? Because you're right, your customers will have different skill levels themselves. But I think it's also freeing up your agents' bandwidth to focus on those more meaningful tasks and complex issues. So if you can leverage the Virtual Agent and collectively, with generative AI, for example, to handle a lot of that upfront troubleshooting, for lack of a better term, then I think that will end up allowing your agents to really focus on more meaningful work, how it gives them a better experience. It gives our customers a better experience. Overall, it's a win-win and you're able to push the boundaries a lot further of what your company can achieve. So I think that's really huge, especially with the talent shortage issues that we have this day.

Yes, definitely.

So as other customers start to explore, right, or continue along their journey with AI and generative AI and as we saw today in our poll earlier that a lot of them are still navigating, still uncovering and discovering what's possible, what are some helpful lessons that you've learned along the way that you would love to share here?

The most important one is you want to feed the system enough information, especially if you're definitely pursuing -- even if you're just going to stick to the classic AI, which is built in, right? You don't pay anything additional. It's like gen AI is just built into the platform. What I would have done sooner was I would have fed it all the data, right? So I fed it and then I'm like, oh, good results. Fed it again, fed it again, right? So now we're just feeding this thing everything we can throw at it, so feeding the data. The second thing is like we work with great technology partners, an integration partner. [ Insource ], for example, they made all the difference, right? They helped us get to that 6-month very aggressively. They understood what we needed. And ServiceNow, right? So I am always almost shocked and flattered at times in how often ServiceNow engages me, hey, do you have what you need? Yes, I'm good. Hey, anything that we can do, anything we can move forward? Hey, have you opened any tickets? Are you getting the information you need from our folks? And it's not one person, right? So you think one person cares, right? It's actually the whole organization. I hear from different people at different times. So again, being with a great partner made all the difference. And last but not least is make sure you interact with your data. Make sure you take advantage of the reporting capabilities. Make sure you're looking at what's effective, what's not, making sure you talk to your advisers, hey, we're moving into this platform. Because by interacting with data constantly, right, when I engage with them, I kind of know what's going on. So I don't -- sometimes it's just reservations or fear of change or people that are not change agents, right? So we come to them with data and they go, it's not working. Okay, why? I see here you're doing really good. You actually improved 20%. Why don't you like it? And when you see what they're bringing to the table and they see that you know, it tends to really change the conversation and you get more adoption a lot quicker.

Absolutely. Data is king, I think, to help make informed decisions and so forth. So I absolutely agree with that. That's impressive. So I'm going to talk a little bit about -- we talked about generative AI. And for the benefit of the audience as well, we've been investing, as I mentioned before, in AI for over 6-plus years. But generative AI is kind of that game changer, especially on the Now Platform because generative AI can do things like summarize cases and chats and interactions, very similar to how you're looking at what it will be able to do for Konica Minolta. And that will -- I think, combined with the Now Platform, is really taking those outputs of generative AI and being able to take action on it, right? And I think that's the powerful combination of bringing generative AI together with powerful workflows and automation. And ultimately, that can lead to improved deflection, improved productivity and optimize processes, and this is really what Now Assist on our Now Platform is able to garner. And if we go to the next slide here. I think we've heard a lot about what's been happening with generative AI. Izzy, can you tell us what's next for your AI generative AI path?

Yes. So we're probably going to -- we're starting -- we had our toe in. Now we have one foot in, and I think we're right on the cusp of jumping in with both feet. We're going to be definitely pursuing the case summarization like we said earlier. Document Intelligence is really big. Again, it's about being able to interact with these existing datasets that were out there, right? The level of effort was so high to, again, find the document, find -- get that machine management, this was so high that we just didn't interact with it. It turns out, that's always the answer, right? Our engineering team, who has the luxury of time, they can go ahead and interact with it for as long as they need to on that phone, 5 minutes feels like an eternity if you don't have the answer. So again, we're going to jump in with both feet. And another thing is for anyone on this webinar, we're in service. It's more deterministic. This is not creative. This is not about, hey, help me write a book. This is deterministic. Machine failed, here's a code. Help me surface that answer. So gen AI, actually a much better fit for those in service. In my opinion, in my 29 years of experience, it's a much better fit than it is for someone out there trying to deploy this to write books and marketing because there's a lot of unknowns. For us, it's all there. It's a matter of surfacing it and then creating content around it, so it's a lot easier to audit.

Yes. No, that's powerful. And I can see that being relevant across different industries, right, whether it's med device or retail. Anywhere where there's like a bunch of products and SKUs and technology involved, could be applicable across multiple industries. So I'm really glad that you shared your story with us because I'm sure there will be a lot of folks here that find it relevant. Now let's -- I'm going to talk a little bit about our road map here. A lot of folks have wondered about where ServiceNow is going with AI, generative AI. And honestly, a lot of companies have been jumping on this bandwagon, right? So we've been delivering AI, generative AI recently. Especially with generative AI, we came out with Now Assist on our Vancouver release, which included generative AI-powered search, summarization capabilities. And as we look to what's coming next, we have Washington, D.C. in March. And that's where we're really going to be looking to help transform that self-service experience. And so with reimagined generative AI, turn-by-turn virtual agent productivity and also with automated knowledge creation, I think that's going to be huge -- and case insights and root cause analysis. So I think there's a lot more to come with generative AI as companies learn what use cases they can apply to, and this is really a time for innovation and inspiration for companies to share with each other how they are leveraging generative AI in their workplaces.

So we are now on to our Q&A portion of today. [Operator Instructions] I do realize we are limited on time. So we'll make sure that we can address at least a couple here. So let's go ahead and look at what we've got. Okay. So first question I see here, what is the difference between classic AI and generative AI? Okay. So that's been the main topic of today. So I'm definitely happy to take that one. So with classic or traditional AI that we've been using for quite some time now in our industries, really, with that type of AI, it's really been about capturing data and insights to kind of see how the trends make some predictive assessments, especially based on pattern recognition, right? And I think that's been helping a lot of companies today make those most informed decisions. I think what we're seeing with generative AI is really taking that to the next level with generating content. So a lot about being able to summarize cases and generate work notes, create knowledge articles, right? Being able to do those with the tap of a button, I think, is really going to significantly improve productivity. And I think that's where that -- generative AI really takes things to the next level. Some things you might see in different industries could be around enhanced credit scoring or natural language processing to analyze public sentiments and improve communication with citizens in the public sector, being able to kind of coach better in real time. There's just so much that can be done with generative AI. So I think that ultimately, it will come down to making sure that all employees are coached well on how to best leverage generative AI. I think that's where companies will succeed is if everyone is well equipped to use generative AI in a way that makes them productive and allows them to do more meaningful work. All right. Let me look at the next question here. How are you staffing and training your team to be equipped -- it's like they read my mind. How are you staffing and training our team to be equipped in handling AI and gen AI capability? So I think this question is for you, Izzy.

So for us, it's actually not so much training and equipping as it is building trust, right, building trust in the platform, building trust in the answers that are being returned. So I have a technical writing team, for example. They're seeing this knowledge that's coming through and they're like, oh, well, here's a shortcut, right? Let me grab this. And so again, the fact that the data that's being returned is -- we have yet to detect hallucinations. I don't know if there's anyone who knows what hallucination is on here or not. It's when the AI is just trying to please you, right? It's just like, hey, and then just change the water pump, right? And there's no water pump in our machine, right? So it's actually giving us hard data. So in turn, with every support call in every return result, it's building trust, and then our advisers are now turning to it more and more and more. So yes, I mean, again, I'm really excited about the possibilities here in the future.

All right. And I think we have time for one more, Izzy, if that's all right. One more question that will, I think, help the audience, too. I think you touched a little bit about this before. But when you're -- when launching new AI technologies and so forth, how do you overcome certain concerns or fears that AI is replacing jobs and things like that?

Well, actually, it's -- we basically bring them together, right? You need subject matter experts, right? So just because we haven't detected a hallucination doesn't mean we won't, right? So you have -- we take these folks that are being trained up, right? So good example, I have someone who used to be my top-level adviser who have migrated to this project. And I'm creating these new opportunities because I no longer need her to be the heavy hitter and have every answer on the phone. Now I need her subject matter expertise to sit here and then say, oh, here's an opportunity. There's an opportunity. So again, it's a matter of having my subject matter experts work with the AI, the gen AI to be more productive. That's where -- what we're focused on, right? Instead of giving me 1 or 2 articles per hour, can you give me 4? Can you give me 5? Because at the end of the day, me, as a corporation, for the additional -- every time I add productivity, I'm saving big dollars. It's not just like -- so the goal is if we can, basically through AI and gen AI, basically add a body of support without adding a body, right, just make them more efficient, look at all the savings, 401(k), dental, health, everything that comes with that, better retention, training. And now guess what? So for example, the woman I'm talking about, her name is [ Noelle ], she is 10x more valuable to me. I'm going to be more eager to please her and keep her as part of my staff because she's doing a brand-new -- [ attending ] a brand-new skill set that a year ago, we couldn't even imagine. So...

Yes. No, that makes sense. You get in -- what you put in is what you get out, right? And I think that investment is clear. Well, thank you. I think we have definitely some more questions that came in, but we are running out of time. So we'll make sure that we get back to you all individually with answers to your question. So thank you for submitting them. And so just to kind of wrap up here. Izzy, this has been a real treat to have you today share your insights, your stories, your suggestions and recommendations for those in the audience that are navigating their AI journey as well. So thank you so much. And thank you to our attendees as well. For those of you who want to share out today's webinars with your colleagues, this will be available on-demand on our website, and there's a link to it there. And also, be sure to sign up for the latest. Knowledge 2024 has been announced. It will be back in Las Vegas, May 7 through 9. So make sure that you sign up. You can scan the QR code there to learn more. And also, please, please, please don't forget to complete the survey that will pop up. Feedback is a gift, and it's the holidays, and we would love to receive your gift of feedback so that we can continue to give and produce educational webinars that will help you along your journeys as well. So -- and with that, thank you all for attending today's webinar. And I hope you have a great rest of your day, and happy holidays.