Name: The 54% Improvement Playbook: How Top Performers Integrate GenAI into ITSM
Uploaded: 2025-11-06T17:06:46.237Z
Duration: 50 min 12 s
Description: The 54% Improvement Playbook: How Top Performers Integrate GenAI into ITSM

Transcript for "The 54% Improvement Playbook: How Top Performers Integrate GenAI into ITSM": Hello, everyone, and welcome. Thank you so much for joining us today. My name is Lauren O'Crew, and I'm a senior manager here at SolarWinds specializing in ITSM. And I'm thrilled to be co presenting with Michael Clark, one of our expert ITSM solutions engineers. Michael, thank you so much for joining me. Do you wanna start by saying hello and giving us an introduction? Yeah. Absolutely. And thanks so much, Lauren, for inviting me, to this, informative webcast. My name is Michael Clark. I'm a solutions engineer for the SolarWinds service desk, and I came to SolarWinds almost four years ago as a previous client. In 2018, I implemented and administrated the service desk for a few years at a hospital, a large hospital here in Texas. 3,000 employees, almost 300 technicians working in the tool across many different departments and managing about 6,000 assets. So, really excited about our conversation today, and and thanks again for inviting me. No problem. Thanks so much for joining us. As everyone now knows, we're getting it straight from the source. So I'm so excited to talk to you today being someone who has worked, in service management and implementing processes that work for, their organization, their team. I think, you know, you offer that really unique perspective of, what's actually gonna work, you know, on the ground when when people need it, where they need it. So I'm really, really looking forward to, our chat today. So, we did this slightly backwards, so I'm gonna go back one. Over the next forty minutes, we're gonna talk about the 54% improvement playbook. And what that is, is a look at our state of ITSM report, where we analyzed over 2,000 ITSM systems, and we found a group of top 10 GenAI adopters who took their, you know, initial systems and improved them by 54%, reducing their average incident resolution time by that much. So we're gonna talk through maybe, what strategies they use, what, you know, actual capabilities they use to do that, and how it all ties into the report that we put together, just this month to see, you know, how different organizations are saying GenAI make massive changes. So, that being said, Michael, I'm sure you can back me up on this. Those organizations who saw that 54% reduction in their resolution time, they didn't just flip an AI switch, did they? You're absolutely correct. It does require, learning your data. So our generative AI is basically looking at your database of tickets, as well as your solutions for knowledge articles, that are in the service desk. So having that information in there, allowing the GenAI to build that that language model off of your data, is really helpful to kinda start the ball rolling with Gen AI. Very nice. And with that, let's get into the agenda for the day. So we're not just gonna read you the report. We're gonna deconstruct what we found in the report. We'll talk you through the key findings just to set the stage of what change we're talking about seeing. Then Michael's gonna take over and show you what capabilities those organizations were using to achieve the results that we saw in the report. He'll show us how to embed GenAI into, you know, our core ITSM tasks like instant resolution, that can really help reduce the manual work that agency day to day. And then after that, we'll tie it tie it all together with some actionable items. We want you to go away with this knowing, okay. Here's what I'm gonna start working on. And we're gonna put that in just a simple blueprint for you. So with that, let's let's have a look at, our first key finding. So to understand the playbook of the top performers, we first need to look at the baseline. So what impact does Gen AI have on the average organization? We analyzed customers' average incident resolution time, before and after they enabled the GenAI features in service desk. So these particular stats are based on those people who had enabled GenAI and what they were performing before they did that and after. So it's you know, organizations are so unique. They're so different. They have their own processes. But this is a nice baseline because it shows us what those exact organizations were doing before and after. So taking like for like processes and seeing in the reduction in resolution time. And to be frank, the results were clear. On average of this group, team saw a 17.8% reduction in in resolution time, which is also an average time savings of almost five hours per incident. So tell me, Michael, from your perspective, what does almost five hours really mean for our service desk team when talking about reducing the resolution time? Yeah. Absolutely. This is a great, result here because what we're doing is we're going to save that time to work on more complex issues, that may, require more resources. So, again, we're just starting to build those efficiencies over time with the use of the generative AI, for those constant issues that that we see come in often. And that's a really great point, Michael. And I think, you know, from your experience, working in ITSM and implementing these things yourself, you don't have one ticket per day. Right? So that five hours per ticket is multiplied over and over and over again. So, you know, think about this. If your team handles 5,000 incidents a year, which is actually, I would guess, on the lower side of the scale, That four point eight seven hours per incident adds up to almost twenty four thousand hours of work that can be reclaimed to do those strategic projects that you talk about. Like, it's mind blowing. Isn't it, Michael? Like, how can we even think about, like, the strategic projects we can work on in twenty four thousand hours? Right. Exactly. And not only that, but there are, you know, some issues that come up where it does require extra time, you know, maybe more collaboration and resources. So we're basically freeing up our technicians to work on those other items as well and, resolve more complex issues a little bit more quickly. Yeah. Great point. And we all know that, agent burnout is a real a real risk in ITSM. So I think, you know, first and foremost, reducing those hours might actually just bring the group into a place where they're feeling comfortable with their workload, with their feeling like they're able to take control of their day, and they're really able to, you know, put some focus in each ticket, not just constantly trying to keep up, with their day to day tasks. Absolutely. Great point. Okay. So let's go to our second key finding. We're just building now to that 54%. So the second group that we looked at within the report, are those customers who had enabled Gen AI and those customers who have never enabled Gen AI. Right? So, our first group was the same customers before and after to see their own changes, and this is those who have started implementing GinAI and those, who have never implemented GinAI. And what we're seeing is that the efficiency gap is growing. So between these customers, those who use it and those who don't, there's a 30% reduction in, incident resolution time, which is almost ten hours. So double the hours, almost double the percentage reduction, in those teams. And I think, you know, when when we see this number, we can say, okay. Maybe maybe the teams that enable Gen AI were closer to implementing these things. Maybe they were already operating more efficiently. What's your take on this when we look at, you know, our before and afters and our Gen AI, non Gen AI customers with this with this expanded efficiency gap? What what's what's your feeling on this, Michael? Well, I think it's apparent that for folks that are adopting the generative AI for, reducing keystrokes, reducing the number of clicks, it's just it's apparent in the data that GenAI is actually a wonderful tool to help our technicians, you know, just improve those, time to resolve as well as documentation and communication with the users. So, it's it's just, it's really apparent in the data that that there's a a real added value with GenAI. Yeah. A 100%. And I think I think there's, you know, there's really something to be said for an organization focusing on their maturity as well. Maybe, you know, the the modern end of maturity at the moment is implementing Gen AI or iGentik AI, but, there's a long journey to get to that point of implementing those things. And I think correct me if I'm wrong, Michael, but I think, you know, the people who feel like they're ready to implement GenAI have done a lot of work on their foundations, on their best practices, with their ITSM environment. And, you know, that's that's the efficiency gap we're seeing here is that they've they've said, okay. We're really gonna invest in, you know, our processes and getting set up for that next level of maturity, which is the generative AI or, you know, the agentic AI. Absolutely. Improving the the documentation is is one of the key features there, our resolution notes, overall notes within the tickets. Because, again, the generative AI is building that, language model from our database of tickets. So the better our notes are in tickets, the better our, solutions are, then it's just going to help us, achieve those efficiencies more quickly. Great. That's you you've just given me the perfect segue, into our most important finding, and I think the word, you know, that we can take to this is acceleration. So, Gen AI itself is an accelerator, and the data proves it. So when we look here at our top 10 organizations, who implemented GenAI. This is their before and after stats. So, you know, our first group was the average before and after. These are our top 10 organizations who implemented GenAI. And you can see here, you know, their starting hours were worse. They were not operating efficiently. They did not have, as many processes in place to ensure that they were getting through things in a streamlined manner. But what we can see is that GenAI for them became their accelerator. Once they implemented the GenAI, they were able to reduce their incident resolution time by 54%. So, you know, this this implementation process that they went through, obviously, was a catalyst for improving so much more than just being able to use the AI in their day to day, but really, you know, brought their whole organization along to gain this twenty seven hours of efficiency per ticket. Like, that's that's an insane number. But Yeah. It Michael, what what like, what do you think about that, the Gen AI being an accelerator and this huge difference that we're seeing in these top 10 these top 10 organizations? Yeah. So for the top 10, what I think we're seeing here in the data is that, that adoption, by the organization to utilize the JENAI, tools in order to, you know, cut that time over over half, for resolution. Right? So, you know, that's gonna take everyone, being on board, all the technicians, you know, understanding the the processes, the expected results, grading those results. And just over time, we're gonna see those, those efficiencies, increase and improve. Amazing. And the the data's anonymized, obviously, but, like, I wanna commend our top 10 organizations for this, like, mammoth effort that they've given. You know, to to implement GenAI is quite simple, and you're gonna show us, you know, exactly how to do it on a day to day basis. But I think what I gather from this data is that these organizations really said, this is our moment to to make an impact with digital transformation, and, you know, we're gonna take it by the horns. We're gonna do everything that we can do to make this change really, really impactful to our business. So all of the things you just listed there about, you know, taking their taking their knowledge seriously, being diligent about their grading of the of the AI suggestions. Like, these these groups really decided that this was gonna be, a major milestone in their organization and the way that their organization operates. And you know what? This data doesn't necessarily show, but, that we can gather and you can probably gather from your own experience is that when you're saving these amount of hours, it's a snowball effect in a really, really good way. Right? Like, you start True. You start freeing up time to go, now okay. Maybe, now that we have all this time back, like, what are some what are some initiatives that the business has been asking us to do? What are some things that we can really dig in and improve that are gonna have, you know, widespread effects? Do we start implementing service management for our facilities team so that they can intake tickets more efficiently? Like, what, you know, what what are some things here that are coming to your mind, Michael, with that you can do with these twenty eight hours per ticket? Sure. Well, just the, you know, 54% reduction in resolution time. I think one of the largest impacts that, an organization will see is that end user customer experience with the support processes. So, that that is an incredible number, and I know we keep coming back to that. But cutting that resolution time in half with, generative AI features is really going to help that end user, and their experience with support. They're going to see the that improvement, not only in the time it takes to resolve issues, but that communication back and forth with our user as well. Tickets will become more detailed, and they will improve over time. And I think that's for me, personally, I'm very customer centric. So that customer experience is always, you know, top of mind for myself as well as just overall efficiencies, you know, with the with the support team. So That's that's a really great point. Like, I have been so focused on what it does for the team, but, actually, you know, ITSM is half the team, half the employee experience, and you're you're so right to bring that into the equation. And I think, you know, we all in ITSM know that when that trust grows between those two sides of ITSM, everyone has a much better, working day. Everyone has a much better experience. And, you know, the the employee is more open to coming to IT for a solution or coming to the service team for a solution, which then, you know, ensures that the operate the organization really operates, in an accurate and a well, well functioning in a compliance sense, way. But also, they just have a more enjoyable work experience, don't they, when they can come somewhere, get something fixed, and continue on their day? Absolutely. I mean, we're building that confidence in the support team. So many times and I've I've been in support roles for close to thirty years now in IT. And one of the things that's pretty consistent is the, you know, the sometimes the comments of, well, you know, support's not gonna do anything. They just tell me to, you know, turn it off and turn it back on. Right? So, so again, it's it's just going to you stated it perfectly. It's just gonna build more confidence in the support processes. People will reach out, you know, more quickly, as as we start to build that trend line of of resolving issues quickly, having that communication and that documentation, back and forth between the the technician and the user. Great. Yeah. I just I just love I can picture you going, I remember the days. I know them so well. I I I would have loved Jenny and I, back there twenty years ago. So but, I I I can pat myself a little bit on the back. I was very diligent with my communication and my notes. So I, you know, was brought up in the IT support world by, managers that, you know, if it's not in the ticket, it didn't happen. Right? So I learned very quickly, so and I tend to rattle on a little bit. So I'm I'm very, you know, I guess, complete with the notes. So, again, I I wish Jen and I would have been available back when I was doing frontline support. We just call it detail oriented, Michael. That's all we call it. Not a not a rattling. Right. Well, speaking of, you wishing that GenAI would have existed. I think now is the time, for me to hand it over to you, to show us maybe exactly as we're talking about these organizations and all these changes that they've seen. I think it's important that we paint the picture of what actually they had changed on a day to day basis by enabling the GenAI. So, you know, this 17%, 30%, 54% reduction that we saw by our different groups, what are the tangible capabilities that they implemented to see these results? So I'm really looking forward to having you show us this, in service desk. So I'll stop sharing and let you take over now. Absolutely. Let me share my screen. Our current, features of generative AI or Genii is really going to be on the technician side of the house. We have some other tools. You know, AI is a huge buzzword, but the service desk has actually been in in the AI business for close to a decade with smart suggestions for both the end users and our technicians. But the generative AI for the technicians is really the game changer. Let me show you an example here. Got my dial pad not syncing, ticket. We see this a lot in our environment. So the first step that that, as we access this ticket for generative AI is gonna be our suggested solution steps. Now, again, where it's pulling these, this information is actually from our database of tickets as well as any possible, knowledge articles that we may have available. So you'll see the AI sources down here. We're gonna review this with you know, we don't wanna just, you know, display something and then click right through it. And we're also going to grade it on our one to five rating for stars. So, basically, if this is an appropriate, solution steps, we're gonna go ahead and give it that five stars. And there we go. So that's step one. The second thing that we're able to do is generate that first response. This is where I really think, the GenAI shines, in the service desk. So it's basically it's not just pasting over those solution steps to a comment to send over to the user. I really like the way that over time, we're gonna have this really informative paragraph that has, a, you know, a good tone to it, in my opinion. We're able to edit so I can, you know, put it a little bit more in my, you know, my tone. We'll go ahead and post that. So with just a couple of clicks, I've generated possible solution steps to resolve the issue. I had sent that first response back to the user that outlines those steps and just lets them know that, you know, we're here to help them resolve the issue. And I've done it with a couple of clicks. So I'm saving on the keystrokes. I'm saving, you know, time. And, and again, we're improving that communication back to our user. Now once we have enough back and forth so for example, I'm going to go ahead and send over a solution. I'll insert that I can go ahead and send that over. I'm gonna go ahead and say, you know, please reboot your workstation. Sometimes you do have to turn it off and turn it back on again. Exactly. Exactly. So we're gonna reboot the workstation and advise if, the issue still occurs. There we go. So once we have enough back and forth, set at least three comments, then, the next step or the third step is going to be our AI incident summary. So I can click generate summary, and here in a few moments, there'll be a summary of what's happened in the comment section. So, basically, it's gonna give us a small paragraph of just basically what's happened. We can use that in a couple of different ways. So as a first tier support or, you know, service desk support person, maybe I've done a lot of research. I've asked, work, you know, with the user to do some different troubleshooting steps, and I'm still not able to resolve the issue. I can send this over to the escalation team. And normally, the escalation team would go to the bottom of our comments and read everything going up to see what's happened up to this point. With the summary and let me refresh and see if I can get that summary here. There we go. With the summary, I can generate that, read my, you know, short paragraph, and just get an idea of what's happened up to this point as the escalation team. The other way that we're gonna use the summary is when we go to resolve the ticket. So let's say we've, got a response from our user. They say everything is working appropriately now. And I can basically take that incident summary, bring it over to the resolution description area. And, again, we're just improving that communication. We're reducing the keystrokes and the number of clicks, and I'm ready to move on and go to my next ticket. And, again, we're going to always grade it as we work with the generative AI. And what what's the, what's the importance? You keep saying, you know, we wanna grade it. What what does that do in terms of our overall GenAI strategy? Absolutely. So grading, each of those steps is going to help refine those results over time. So for example, if, you generate some solution steps And then you see in there, wait a minute, the you know, this fourth step, it really doesn't apply to this particular issue. So then you would give that a lower star grading. So, again, it's just gonna help the generative AI over time, just refine the results and and improve, each piece of the, GenAI that we're using. Very nice. I hope I said that where it makes sense. It does. It does. Yeah. Like, the GenAI has to you know, businesses are unique, and I think, you know, an important piece of SolarWinds has a has a framework called, AI by design. And one of those principles is keeping the human in the loop, and this is exactly what that is because to to make the AI work in the best way possible and the most accurate way possible, it needs to understand when it's doing well and when it can be improved. So, yeah, you've you've said that exactly, and that's, you know, an important part of, the way SolarWinds approaches AI. Absolutely. And, you know, we never wanna just, you know, turn on a generative AI, in any application or or situation and just let it, you know, do everything and and not review it. So, like, the human element, for ensuring that, you know, the GenAI is, giving us appropriate guidance or or, you know, has well worded responses and summaries and things like that is is really important as well. Amazing. So true. And I think, you know, in my conversations with, some customers who are implementing AI, and maybe you can shed light on this. You talk to way more customers than me is sometimes I think people you think you do just turn it on, and it works. But, actually, you have to get to know each other a little bit. Right? Like, the GenAI, the more tickets that it receives, the more gradings that you give it, like, it it really does come to know your organization a bit better. It's not it's not an instant setup. It takes a bit of understanding from both parties, to work in this really, optimum way. Absolutely. We're going to as the technicians and as a, you know, person in the organization, we're gonna help train, the GenAI to give us the appropriate information. Because, again, we don't wanna just click, you know, through something and send it off and never review it. You know, we want to make sure that the information is is, appropriate, for the issue and, does it create additional, issues for us with, incorrect guidance or information. Absolutely. Yep. This new member of our team, we have to get to know him. We gotta we gotta have lunch with him sometimes. You know? Exactly. It's it's our it's our sidekick. You know, we're we're actually the superheroes. And the the Jenny Eye, you know, I've I've likened it to, that's our Robin, you know, to our lab. Right? So Love it. Love it. So so there's another, a GenAI feature I wanna just cover really quick, and it has to do with Runbooks. So let's talk about what Runbooks do first off. Runbooks is a great way to standardize some of your support processes or troubleshooting processes. So each organization is different, of course. You know, one organization may troubleshoot, you know, a software issue this way. Another, you know, organization does something different. You know, there's two of us right now, and if we were given an issue to resolve and we did the research, we could probably come up with a couple of different ways at minimum to resolve the issue. Right? So with one way that we can use runbooks is to just take those processes that we're gonna follow, and the runbooks will actually and, like this case for, VPN troubleshooting, we're going to assign tasks to the assignee of the ticket to basically follow like a map. So we're gonna complete, you know, the first task and verify, you know, that resolved the issue, and we'll just keep moving down. One of the things that GenAI, can do for us with runbooks, because we have to create those runbooks, and we can either do that manually or we can import a documentation like a a word file or PDF or even a text file. We can bring that in, and then GenAI will create the runbook for us. And we can go in and edit and and clean it up a little bit. This example I have here, just a VPN troubleshooting documentation, document that we had, brought that in. I had to make two edits and within just about two or three minutes, I had a full run book for how to troubleshoot VPN with each of those tasks assigned to the incident assignee. So this is a great way to standardize processes. We're gonna do the same thing every time. We're going to be able to onboard newer technicians more quickly in organization. If you have some runbooks built, then that newer technician can, you know, get the runbook, follow the task assigned, and come up to speed a little bit quicker on the organization's processes. So that is creating the runbook. I'm sorry. Go ahead, Lauren. No. That's really nice. I'm just I'm just thinking of, like, how how what's a good analogy for, like, what the Gen AI does here? Like, you know, we we all love to go to our dresser drawer and find our clothes that are folded and, you know, we can find easily the things that we're looking for. But, actually, I don't really like folding my clothes that much and putting them away. So that's that's kinda like a run book. Right? Like, it's a lot of work actually to fold my clothes and put them away. So for me, like, this is how my brain works. What the Gen AI is doing is it's taken that step out, or at least reducing it by by quite a bit of saying, like, you go straight from clean laundry to in the drawer rather than Sure. All that extra work in the middle. Even though I know it's better for me that everything is organized and it's there, it still is work. It's still work to get done. So that's another way, that time is, you know, given back. Absolutely. It's an effort. Right? So it's an effort to sit down and, you know, stand up a a workflow, you know, assign task out, type that information out of what each task what you want to happen. So, again, great success, with the, you know, creating runbooks through GenAI. And just as a reminder, we're always going to grade that process, or our experience with the generative AI and make sure that we're sharing, you know, yes, this is wonderful or, this could use some work. So, so we talked about the runbook. Let's see it in action on how we could use that in our day to day operations. So I'll go back to my incident list and there there's my issue connecting to a VPN. So from here, there's a process tab that I could go to. And this is where I can add a runbook. And remember, we have to have those runbooks created in advance, but I'm going to just add a runbook. There's my VPN troubleshooting. I'm gonna start it after it's added. And then here, just a moment, it's going to assign out all of those tasks that need to be completed, to troubleshoot an issue. So, you know, this is all for the on the user side. So, yep, they've got good Internet. They've, rebooted. They turned it off and turned it back on again. They've restarted their app. They've rebooted their router. So now we move on to, you know, the VPN specific steps. So maybe, you know, we try a different VPN server or update the VPN app if needed or change protocols. Now maybe we get to, like, check credentials and we realize that our user is not even in the correct o u in active directory to have VPN access. So then I'm able to, you know, check this off as completed and then add my comments that this is where, you know, the issue, was found, is in the OU. And so added to o u, validated, verified. And, again, we're just gonna improve that time to resolve, you know, by having those same steps that we're gonna follow each time. So cool. I mean, like, it's you can just see how I I think one thing we haven't really talked about here yet is it just takes away that time to decision. We keep talking time to resolution, time to resolution, but a huge part of that is deciding what you're gonna do in the ticket and a runbook that that's your decision. Absolutely. And and, again, it goes back to, it goes back to everyone has a different way to troubleshoot issues. You know, there's some people that, you know, are are self taught, you know, IT folks. Right? There's some folks that are, you know, highly certified in different areas. So, with those differences, we can use the runbooks to standardize the troubleshooting and take some of that this, you know, decision making on how we're gonna research the issue out of the hands of the technician and just help them, you know, again, get some of that time back, that they would normally spend researching or troubleshooting. We can also use the Runbooks for an ad hoc approval. Maybe I get that ticket from a user that I feel a lot more comfortable with that user's, manager approved the the, you know, working on the issue. Again, we we can use many of our almost well, all of our workflow action steps that we have for our service catalog, we can use those in the run book. So it's really kind of endless possibilities. Very nice. Very nice. Well, thanks, Mike, so much for, walking us through the generative AI steps. Like, I don't I think it's fair to say that we weren't even too far from solving a ticket in real time watching you go through that. I mean, obviously, you have to wait for people to get back to you on stuff, but, like, all the actions you took are as fast as we saw you do them, which is, you know, just mind blowing to me. It it it is to me as well. Again, it's a a wonderful tool. You know, and, again, we want that confirmation or that validation, you know, from the user, that their issue was resolved. And then, but, again, I think it's huge from a customer experience standpoint. You brought up the the quality of my work life as a technician. You know, maybe not feel as buried under, you know, the volume of tickets, you know, with the the Jenny and I helping us out. And the and the simple boredom of doing the same thing over and over again. That's like that's maybe an under underrated, like, pain point is, like, I'm just bored repeating the same the same task over and over again, and it's valid. It is. But we do need those users, though. So, you know, saying saying that that same thing over and over, is also part of why we all, you know, have, have roles and and jobs in in the support industry is because you're gonna have, you know, new people come on and they're gonna have those same questions. And, again, with those, those issues that we see repeated, often, you know, the the GenAI is really gonna help out a lot there. Yep. Yep. Our our agents can manage them, but they no longer have to type out the whole reply themselves. That's that's the Exactly. Very cool. Okay. So, like, thanks so much, Michael, for showing us, you know, how we got that seventeen, thirty, and 54% reduction in our in our different groups. I think that is, you know, so clear how the Gen AI is coming into the exact place the agents are working, and really making those differences that we saw in the report. So from there, let's talk about a blueprint for success. So what can everyone who joined us today, start doing to start their to start their GenAI blueprint, their GenAI process. So, the first step I wanna talk about is adopt practical GenAI. I think we we saw it in action today. You want tools that assist like a sidekick. You want your Robin to your Batman. These things, you know, allow you to maintain that control that, we were talking about, but really do that folding of the laundry. They really do that work, that we kind of don't exactly have to do anymore. The second step is integrate with ITSM foundations. You you touched on this, Michael, quite a bit. You know, you really want to implement your AI after you've cleaned up your core processes. So you're not get your knowledge base, in order. Get your get your service catalog in order. Ensure that your, existing tickets are in a good in a good place. What any other foundations that you mentioned, Michael, that you wanna bring up here? Well, you know, I one of the concerns that that, you know, I I hear sometimes from users that are, new to adopting the Gen AI and turning that on is the, you know, the voice concern of, well, we haven't done really well with documenting our our tickets or resolutions. But what we're seeing is that since we're building that language model, not on just comments or notes, but, like, the entirety of the ticket. So all of those data points, including the description of the issue, the category, subcategory, all of that goes into to building out that language model. And again, at first, you may, you know, have to really focus on that grading. And and as you grade it with our one to five star method, it will improve over time. So, you know, one of the biggest things is just, you know, let it build that, language model and then just like that third bullet point, just bring it into your daily workflow because that is really what's going to refine and improve and will realize those efficiencies much more quickly. Exactly. You said it. I no. No. The the only way to get to that 54% is to ensure that your team sees the value in it. Everyone on your team sees the value in it. Everyone is, you know, understanding of how it can help them, and then they start to use it on a day to day basis. As Michael said, it will not only approve how it works, but also that's where those efficiencies really start to add up. Absolutely. Okay. So, just as we've, you know, talked about all of these things, everyone's come with us to understand the report. Michael showed us, you know, what capabilities contributed to the numbers in the report. If anyone on this call, you know, is interested in implementing GenAI into their own workflows, we have people like Michael Michael himself available to, help show them how to do that. So we we just sent a poll around now. Just let us know if you're interested and someone, will be able to help talk you through even if it's just questions about, your current setup and if there's any efficiencies that can be improved. We we love we're ITSM nerds. We love talking about, you know, ways helping helping our people understand, you know, where where they can start to optimize. So let us know, and someone from the team, could be Michael himself, might talk to you about getting GenAI implemented into your own ITSM workflows. Okay. And with that, I just wanna say a huge thank you to Michael. Your expertise is, like, of another world. I'm so excited to talk to you. Every time I do, I always learn something really valuable to take away. So thank you so much for your time and your wisdom. Thank you very much for inviting me, and I I love doing this. This is the perfect role for me. I love talking about, you know, processes, service management, improvements. And, yeah, I'm just really excited to see, see how this goes from here. So You're you're the best man for the job. So really appreciate it. I'm good. And I'll be anytime. I'm here to help. So What are you doing next week? Okay. So, for everyone else who joined us, we hope you enjoyed the state of ITSM report. If you, haven't downloaded it yet, it's available to everyone. So give it a download. Give it a read. It's mostly what we covered here today with just a bit more context. And we also hope that, you know, you found the playbook that Michael showed us and the blueprint for what to do now, if it's time to implement GenAI helpful to you. We've we've really only scratched the surface today of all the ways that we can start to optimize our own ITSM systems, but, this is an important one for driving transformation in the organization. So, to everyone who joined us, everyone who's rewatching, at a later date, thank you so much. Send us send us a message. Let us know on THWACK what you thought of the session, and, we hope to see everyone soon. Thank you so much. Thanks all.