Generally, we see businesses look at their IT teams and ask them to complete initiatives that they don't have the bandwidth to do because their job- Yep. -Is in the day to day activities of those businesses. And a lot of those IT folks don't feel it's safe to ask for help. They view that as a, I'm saying I can't do this, versus- Yep. You know, or I'm unable to, versus, I don't have the time. And so that's where having a partnership can really accelerate that technology adoption. Welcome to the latest episode of Unraveling IT, Expert Tech Talks. I'm Garrett Wiesenberg, Director of Solutions Engineering here at Corsica Technologies, and I'm sitting down today with the CEO, Brian Harmison, and COO, Peter Rodenhauser, to dive back into AI strategy. We know AI is everywhere, but the question isn't really what is AI, it's how to use it. Today, we're breaking down how businesses can step into AI in effective and a meaningful way. Thanks, Garrett. Yeah. One of the things we hear all the time is my business, you know, we wanna do AI. How Yep. How do we get started? Or we know we need to get into AI. What everyone is asking about now is how do I practically use it within my business? It might be helpful for us to kinda define some of the terms that we're gonna use today. Yep. So, you know, one of the things that that we often hear is, we wanna implement some AI in our business. And, you know, the first question we ask is, well, what does that mean for you? What are you, what are you trying to solve? And I see a lot of confusion between AI and automation. And automation is just, you know, the things we've done in business for a long time, which is creating routine tasks that that are able to be completed automatically, where AI brings a level of decision making and reasoning into that. That typically replaces some portion of a person's role that that we've traditionally needed a thinking person in in order to complete that task. Yeah. I think that's an important point. And Garrett, thanks for having me. You're welcome. Today. Oh, yeah. Thank you. But, you know, and I think it's also important to note that the two coexist, you know, and they're gonna continue to coexist. So, you know, automation, Brian, as you said, is that, you know, these are these are predefined steps or tasks, that we can programmatically, or systematically automate, in a way that introduces efficiency. Whereas, you know, AI brings that level of, decision making, based on, you know, either known or unknown quantities or variables. Mhmm. So it's exciting and, yeah, definitely worth noting that, you know, we're gonna continue to see them coexist. Yeah. Yeah. I think one of the great things about businesses asking about AI is it gives a chance to talk about some of the areas of automation that maybe they haven't explored in the past. Why do you think AI is creating both excitement and anxiety for business leaders right now? Is it because of the the unknowns surrounding AI? Is it just hype? Are they hearing, you know, the buzzword of AI and just wanting to jump in head-first? I mean, where's all the hype coming from? I think, I think for business leaders, there's, you know, whether it's anxiety, there's fear of not wanting to be left behind. Mhmm. So not wanting to miss out on- FOMO. Yep. Maybe some FOMO. Not wanting to miss out on on a wave. You know, I think any business leader is being, you know, certainly challenged or inquired by, you know, their board or their executive team to say, hey. How can we better leverage AI in our business, to either introduce innovation or introduce, you know, cost savings. Those are those are, you know, gonna be typically, your two levers. But I think, you know, the other, you know, concern or fear is around just wanting to better understand it and the applicability of it. I know we're gonna talk about that today Mhmm. Because that's a huge unknown. You know, how can we apply AI to our business that's most meaningful and most impactful. Right. I don't know what you're seeing. Yeah. I agree with what you said, Peter. I think on the anxiety side is, is some of my data being put into a ChatGPT, or used in a way that maybe I don't know about? Are my employees using AI to fulfill their job functions, and, you know, I'm paying somebody to do something that maybe they're not doing anymore? Are we violating some kind of rule or, you know, potentially even ethics around the way a person, for example, in HR might be using AI to, you know, screen candidates. Mhmm. They're so I think some of the anxiety comes from less of the productivity side and more of as Peter mentioned, there's this unknown element of what could be happening in my business. And, you know, I do think the fear of being left behind, you know, I consistently hear it that, you know, we're afraid we'll be the last ones to adopt or we're gonna end up at a disadvantage because we haven't adopted AI. So when you hear leaders, you know, in organizations saying, you know, I want to get into AI, what do you think they're truly asking? I think they're looking for that advice of how do I not get left behind? How do I make sure that I'm not the last one at the table saying we're bringing AI? Mhmm. What what's often missing from that is, well, where in your business? Because we as business leaders have to think about our business in terms of, you know, what are the right areas to use AI? I mentioned HR as an example. HR is not a good area Mhmm. To use AI because AI has natural biases. We don't want to depend on, you know, the the machine reasoning and and learning to to make human capital decisions. But when it comes to my data and looking for insights on my data, that that could be a really good area. So what I usually hear is, you know, when somebody asks that question, they're really saying, you know, where do I get started? Yeah. Yeah. And I think with that, you know, our guidance and advice to clients is gonna, you know, be to really obviously better understand their business. And as Brian said, you know, what areas do we wanna focus on? But I think it starts a very natural place to start is working with the vendors and software applications that you are currently partnering with today and understanding how they are incorporating AI into their products and platforms. Mhmm. If you gain some insight, you know, into that, you know, of course, it's gonna give you a road map of what features functionality you may be able to leverage in in the future. But it also gives you some insight to how a technology vendor or provider is thinking about AI or looking at AI within the products that they're providing you today. Mhmm. I think that's such a great point. I think people think of, you know, we wanna do AI in our businesses. You know, they need to go implement Yeah. Something. And the reality is they likely have partners who are already making those investments that that they can leverage. Mhmm. And where they need to focus is maybe a little bit more the way their business operates and what areas they can leverage the tools that they might already be paying for within that environment. I think that's a really great point. We have this conception or misconception of AI because of things like ChatGPT and even Copilot to some extent, that it's really easy. You know, I just type in stuff and it gives me things back. Yep. And that's true if you need, you know, to write a poem or you want to put something in maybe a little different format, word it differently. Mhmm. Gather a lot of data for research that that doesn't have to be super precise or maybe a hundred percent accurate, but you're looking for directionally accurate. When it comes to integrating those concepts within our own business, the AI has to be trained on our business. And the best way to do that is through the applications and the vendors that we already partner with to run our business, and EMR, or even, you know, SharePoint OneDrive, the data verse Copilot. Yep. And I think that, you know, along those lines and examples you shared, Brian, you know, this this is where we really draw the distinction of leveraging AI as a productivity gainer, not necessarily an automation job elimination tool. And, you know, a couple of good examples, when you look at Copilot, when you look at ChatGPT, you know, how can we leverage that? Well, you know, maybe we're leveraging them just to get an idea or a concept, you know, whether it's summarizing a document. That's a time saver. Doesn't replace the fact that I still need to absorb and understand, digest, marinate on the on the information itself and come up with my own conclusions, but it can get me there faster. Or if I plug in the ChatGPT, hey, give me an idea of a structured report on, you know, something that, you know, whether it's a topic or even, you know, a business report. It can give you an example of an outline. So you're not starting from a blank piece of canvas. Yeah. You know, so it just gives you a little bit of an accelerator, to start that project or initiative. It's not, you know, replacing a function in its entirety Mhmm. Today. Oh. Yeah. Today. I think that's a great point. Where we see AI at right now is not replacing humans doing tasks. It is a productivity multiplier, as Peter said. And, you know, transcribing meeting minutes and giving action items are great another great example. These are things that do have an impact. They're maybe not quite as exciting as saying, you know, we can reduce our direct labor by thirty percent because we're implementing AI, but they allow your good employees to be that much more productive, have a better balance, and spend their time on the most important tasks. Mhmm. You both meet with quite a few clients, you know, often and have these conversations with them frequently. Do you find that there's this misconception surrounding, AI versus automation and they're using them interchangeably to to some extent? Oh, absolutely. Yeah. They think that, you know, AI will solve everything. But really, you know, the automation tools, like you've stated earlier, have existed for quite a long time. It's just a matter of implementing them. Yeah. And I think AI can introduce automation. Yep. Right? So AI is identifying in some cases what can be automated or even how to automate Right. It's becoming that that think engine to to do that. Right? The means to to ultimately that automation end. Yeah. And and a great example is, you know, ChatGPT. Write me some code that does x, y, and z. Mhmm. That code provides a level of automation that was produced by AI. Yep. Which traditionally, maybe I would have had to call a developer and have them do that where now I can just go plug it in. So I I think that distinction is often lost when someone says, you know, the classic Mhmm. We need AI in our business. Yeah. A lot of times what they're thinking of is really automation, and AI can help accelerate that automation for sure. Yep. So what do you think is the the biggest barrier for entry for these organizations trying to adopt AI and trying to, you know, maybe automate some of their tasks, but, you know, also add that layer of AI on top to really intelligently analyze the data and and make decisions. I think it's it's the challenge that businesses have anytime they go to adopt something new, whether it's an ERP system or some automation or AI in this case. It's what is their willingness to adapt the way they think about their process and their use of technology towards the toolset versus towards the way they think it should be done. Mhmm. And, you know, some of the classic ERP implementation horror stories are all about, we tried to bend this ERP system to match the way we operate versus saying, the ERP system's made for our industry. We can adapt what we do to fit these best practices. And Mhmm. And and AI can can be the same way. If if you look at AI as the tool that could build you anything, well, it's gonna be very expensive. It's gonna take a long time, and it probably won't produce the best results. If you look at AI as the tool to help in the evolution of your business towards your business goals, then it can become a very powerful tool that helps you also adapt the way you operate to match what's happening. And and a practical example is, you you know, the the the adoption of Copilot and saying, you know, I I wanna use Copilot in my business to help me find files and do client summaries faster. Mhmm. If if we don't say, well, we're gonna move out of file shares on servers into OneDrive and SharePoint, that becomes very hard Yeah. To do. Where if we adopt now a cloud based file system, it naturally lends itself very easily to say, I wanna apply some AI to that cloud based file system that's made to operate on that cloud based file system. Mhmm. Yeah. I think that's well said. I mean, I I think, you know, when when we talk about the adoption of AI, we're talking about a change management, you know, item and challenge inside people and the processes to support it and Mhmm. Set up to support it are are gonna be key and and critical. I think if if those are set up, then you're set up to be successful. So it's really a a top down mentality. Like, you gotta get the leaders bought into the the changes that you're going to be pushing through the organization, and it's really more of a cultural thing. Yeah. I mean, I think most things are. Yeah. Cybersecurity, same way. K. If Yep. If the the leadership doesn't believe it and it's not culturally valued Mhmm. Neither will automation. Yep. I'm I'm gonna say automation instead of AI first. Yep. Neither will automation, which ultimately then can can drive you towards the use of AI. Mhmm. Because it because AI is just intelligent automation of of these things that that brings in that reasoning and decision making capability Mhmm. To do an automation process. Yeah. And I think it's critical that, you know, with that top down approach, if the the top is casting the vision of, you know, we want to explore and identify ways that AI can help grow, innovate our business. That's a great message to hear. You still need to create the culture of allowing the ideas to grow from the ground up to the organization. Because it's not going to be, you know, the executive team that's gonna think of all of the, you know, applications of AI. It's going to be the teams that need them and creating a culture where, you know, there's not fear of job replacement. Right? I mean, you're truly creating, that vision of, you know, how do we leverage this technology to introduce new products, new services, to our customers or in a more efficient way. Mhmm. And if you can be successful at that, then you can have your team supporting the business, operating the business, ultimately seed where those opportunities are and funnel them back up for the organization for approval and sponsorship and ultimately funding. Yep. Yeah. Yeah. I think that's such a great point, Peter, because in unless the people who the automation's going to impact are on board, it, you know, it's not gonna be adopted, and it's not gonna happen. And that's where, as business leaders, we can talk more directly and accurately about AI in terms of, you know, what we expected to do for you as an employee around it's going to make your life easier. We wanna remove these repetitive tasks. We want you doing the real work that you are hired to do and to really make it that that bandwidth multiplier for you. Yeah, absolutely. And to draw a similar analogy, it's when we talk with customers as a managed service provider, we're often talking with, a director of IT, a VP of IT. And, you know, we're positioning ourselves to partner with their organization to provide a lot of the, you know, the back office, IT, and cybersecurity services to free them up Mhmm. To focus on the business. Because they're in a position where they know so much about the business that, you know, let's not waste that time on keeping the lights on, so to speak. Leverage a partner that can do that, you know, more effectively, you know, or, maybe efficiently so that you can focus on adding value and strategy to the business. Same as applicable in, you know, with with AI. How do we leverage this technology so that we can better end? I wanna go back to, something you said previously, Brian, which is, you know, where your workloads are located. You know, having file shares on-prem versus file shares in the cloud, are you are you saying that you can't leverage AI if you have file shares on prem? Or, you know, what are the- Yeah. - you can. There are ways to do that. I you know, our recommendation and, you know, maybe a way to answer this question is to step back a little bit to what I said before, which is, are you adopting the way AI was designed Mhmm. In your particular use case was designed to operate, or are you trying to fit it into the mold of the way you want Yeah. To operate or the way you've always done things? In the software development world, you know, we tell people when they ask you, well, is this possible? Well, anything's possible given enough time and money. Like, this technology, we can do whatever you want. Yep. But none of us have unlimited time or unlimited money. So the question comes down to, you know, what's the best use of that that time and money? And while it could be done, the best way to do it, the most efficient way that also sets you up for long term success and other opportunities is to adopt the methods and systems and data locations that naturally support AI and were built to support AI rather than those that are, you know, being, you know, patched in Yeah. As legacy support. Yeah. And I think to summarize and be, you know, provide even a specific example is, you know, a lot of our clients, even ourselves, we, you know, we're in the Microsoft ecosystem, Microsoft, you know, 365. Storing files in OneDrive versus, you know, a file system will automatically unlock native AI capabilities that aren't going to exist otherwise. Mhmm. So why would you not take advantage of that? Yeah. And that's really, you know, we're getting at is those native capabilities. So going back to talking with your current software, you know, vendors and providers, understanding, you know, what their roadmap is for AI, how they support AI so that you can take advantage of those capabilities, you know, in the most native way possible is gonna get the most bang for your buck. So what are some practical AI use cases you've seen, organizations adopt, you know, as sort of like a use case example? You know, is it document summarization? Is it data analytics? Maybe a mixture of both or even something else? Yeah. It's, it's both. I think some of the most practical examples maybe aren't the most exciting, because they're not the things that- the silver bullet kind of AI implementations that I think a lot of business folks have in their mind. Mhmm. But they're things like recording meetings, summarizing meetings, creating follow up action items. Those are the super practical everyday force multipliers within business that we see happening, a lot. The other is around, you know, writing automation code through things like Copilot Studio Mhmm. To build efficient workflows in the online Microsoft ecosystem to to be able to operate their business better. So whether that's, you know, an HR approval process, you know, document approval, change management, those kinds of things, all are very easily supported as well as, you know, the movement and reporting on data automatically. Yeah. I would, I would agree. I mean, I think, you know, an accelerator in in low code environments, to automate tasks. So again, using AI to support automation is an area. You know, we're not, I'm not seeing or hearing of AI being used to build, you know, enterprise class, you know, software applications by any means that could be, you know Maybe at the individual level, it is. Right? But it's not Correct. Not replacing those developers who might be using some AI to help them. Exactly. So that's one. You know, Brian mentioned, you know, productivity within businesses. You know, another area, just because, you know, scenario that that we touch on that I see some very practical implementations on is around service desk, help desk ticket management software applications Mhmm. In really helping agents, identify and correlate various incidents as they're working with customers. Again, accelerating knowledge base articles, to them based on some of the keywords that might be, you know, within a request or an incident. That's one. I think we're seeing some things in in even, you know, call center, technology where there's an actual voice over, you know, component. It can pick up based on dialogue. So, you know, if you are in the southern part of the country versus, you know, someone calling in from the UK, the dialects that get translated can even, you know, have a localized Mhmm. Dialogue and accent. Wow. So there's some cool technologies like that that's happening. That's awesome. Yep. So how should a business go about identifying, you know, how they plan to adopt AI? What sort of questions should they be asking themselves or, you know, their coworkers to, you know, really find the right fit? Yeah. There's really kinda two key parts of AI adoption. One is how do we adopt technology in general and bring it into our ecosystem and provide security for it and make sure that that we're using it in a safe and ethical way that that also protects our business. So that's, that's one piece. And that's not really the topic for today, but it's worth mentioning that, you know, as a business, when we talk about adopting any new technologies, bringing in a new system, we need to have a process that manages us through that. So that's one. The other is then what are we why? What's, what's our reason adopting this new technology, and where do we expect it to take us? And that's, that's a piece that that I frankly see most businesses missing. I kinda mentioned this idea of it's like the silver bullet Mhmm. Of technology now. We're gonna implement AI, and all of our wildest dreams are gonna come true. But we don't even know what those dreams are, and we're Yep. We're starting to to use something. And so we see a lot of experimenting with AI because of that, you know, things like Copilot. But it's sitting down and really developing what's our technology plan. Mhmm. And then how does AI help support that plan? And how does it support our growth and our business strategies? And without those strategies in place, it's very difficult to have a successful adoption of any new technology, let alone AI. Yeah. I think, you know, we're still in such an infancy, you know Mhmm. Mode of AI technology and even the implementation of it. So, you know, in my view, you know, what's most important right now for organizations, especially as they're, you know, dipping the toe in the water and getting some initial exposure is really, you know, incubate, you know, incubate, experiment with some ideas. You know, don't go into, you know, some huge initiative. Figure out, you know, you know, what may work. No idea is a bad idea. Right? I mean, if you come across an idea and you're able to cross it off the list, then, you know, it's something that you shouldn't be focusing on. That's okay too. But really going through that, you know, in terms of an experimental phase, once you get to the point where you can actually identify some, you know, some specific areas where you can leverage AI for that innovation or for efficiency, whatever it might be, you know, those two pillars. You know, the most important one of the most important things that Brian hit on this is really having some governance around the data. Mhmm. You know, that data and where that data lives and, you know, because that that data is what's going to be used, ultimately for, you know, AI engine, whatever it is to make its decisions and to, you know, to create its output. So ensuring that that data is safe, protected, based on your governance within your organization's experience. Okay. Let's say a business has identified a use case. What are the next steps for them to actually, you know, pushing that adoption forward or pushing that initiative forward? I hate to say it depends. But it, you know, it really does depend on where in the organization. Mhmm. But, you know, going back to something that I mentioned earlier, in ensuring that you have people in process in place to support whatever the technology in in some cases is almost secondary to these implementations, because it is a change event. But ensuring that the people and process are aligned, with what the ultimate objective is of your implementation is really that first step. And I mean, you can even go back to that beginning where, where I said, you know, if you're gonna go with that top down approach and, you know, making sure that the top is communicating to all levels, and really encouraging that, you know, that some of that thought leadership and innovation with your organization. So, that would be my recommendation. And I think, Peter, you said it well, a few minutes ago. Start small. Don't go for the whole the whole thing all at once. Choose a portion of that. Use the people and the process Mhmm. To guide you through that implementation. And the other is find folks that have done it before. Find a partner. Yeah. And leverage their expertise. So it can be really easy to look at it and say, we can go this alone, but, you know, partner with a good consultant that can provide you with some guidance in where they've seen a use case like theirs be successful. What are some of those roadblocks? You know, it's always good to get that outside view Mhmm. Of, you know, what are the things that could go wrong? What are the things that could go well? What haven't we even thought of yet? Yep. That's a great point, Brian. Because, you know, most implementations for most companies, you know, when we say, when you say, hey. We've identified, you know, a project or a use case for AI. Mhmm. They're likely not developing something new. They're they're likely deploying or implementing a technology or capability that exists within a software application. Yep. So, you know, having, you know, a consultant or a third party that can help you with that change management aspect of the people and the process is important if you don't feel that you can support yourself, but also the technology implementation itself And making sure that it's configured appropriately and that you have in place, you know, the right monitoring to track the, ultimately, the outcomes that that you're after. Yeah. And that's actually gonna be my next question. I'm hearing a lot of what you guys are saying, which is, you know, a lot of these are more business driven decisions based on, you know, the outcomes they're You're right. Looking to achieve. But, you know, how can they leverage a third party? You know, what do you need to leverage a third party? But it sounds like, you know, know, there is still value in leveraging a third party, that has experience in the different AI platforms. Yeah. I mean, I think of it like any other discipline within our business. You know, why do we do financial audits? Why do we Mhmm. Engage third party security, you know, providers to do assess we do these things because, you know, anytime we're embedded deep into something, it's easy to get that myopic view and miss the bigger picture. And so, you know, having technology partners that that you can leverage within your business who are gonna broaden that view. You know, I think IT people, especially technologists in in general, whether they're, you know, a straight IT person, a developer, You know, we all would like to kinda build it ourselves and Mhmm. You know, figure this out on our own. But what we recognize is that we also have limited views of what's out there and how to do that. And so finding the right partner who doesn't take over, but is able to step alongside Mhmm. Help your internal team really own that long term, but get past that getting started part of the project and knowing what finished looks like. Because those are the yeah. The in between isn't isn't generally so, so difficult. It's how do we know when we're done Yep. And how do we get started? Those are where a third party can really help and certainly accelerate the in between as well and provide some knowledge. But the last piece of this that I'd say is generally, we see businesses look at their IT teams and ask them to complete initiatives that they don't have the bandwidth to do because their job- Yep. Is in the day to day activities of those businesses. And a lot of those IT folks don't feel it's safe to ask for help. They view that as a, I'm saying I can't do this, versus- Yep. You know, or I'm unable to, versus I don't have the time. And so that's where having a partnership can really accelerate that technology adoption. You know, and it it's because it's not solely a technology project or implementation. Nothing is. Yeah. Nothing is. I mean, it's you know, so it's not just a technologies expertise. It's understanding the hows and the who components, to actually implementing the solution and ultimately the outcomes. What do you think will separate businesses that succeed with AI from those that don't? Yeah. It- it's a great question. We see it some now. I mean, I would say every business has some element of where AI could help them improve the way some part of their business operates. I think that's true. Not every industry is going to be as applicable as others. Right now, I just see everyone wanting AI and maybe not knowing why, like we've talked about. Some industries customer service, the example Peter gave was excellent because those are areas where, you know, AI can truly change the way customer service is done in a really meaningful way. And those are going to be the businesses that find the right use case and leverage it well that will have the biggest impact. Mhmm. Again, so much of what we talk about is AI just helping with some automation. We should be doing that anyway. We should be looking at how do we make our businesses more efficient all the time. That's what Yep. That's part of what our job is to do is to say, you know, how do we produce more revenue for whatever the unit cost business model can I change the way I operate that either accelerates my differentiation and provides new ways for me to engage with my customers or dramatically changes my cost structure? Mhmm. Yeah. I think those that are not experimenting or exploring will be left behind. Yep. Yep. That doesn't mean that they have to jump off or jump in completely in the next month, six months, or a year from now. They could you know, it's about knowing what capabilities- Mhmm. Exist. Mhmm. And rewiring, frankly, our minds on how to think about how we operate, whether, you know, it's growing the business, operating the business, all of those things. This is a rewiring exercise that that we're going through. Yep. So constantly challenging, you know, these leadership teams and the broader organizations to evaluate and experiment. There will be an opportunity that presents itself where, you know, the organization will know we have to do that. We have to do that because it's gonna be a step function change for our business. That's who will survive. And I think any business today who's trying to make decisions on what vendor and partnerships they make, needs to be asking a new set of questions around AI road map for those. You know, we we've talked about, don't try and roll your own if you don't have to. Yep. And I'd say in general, none of us really have to. Mhmm. So then it becomes who are we pitching our wagon to in terms of what we expect out of out of AI long term. Yep. And those are different questions than we would have asked five years ago of those same vendor partnerships. And so whether it's your IT partnership, whether it's your ERP system, you know, whatever those key strategic partnerships are for your business, having those AI roadmap conversations with them of how am I going to be able to leverage AI in my business because I partner with you Mhmm. Those are some of the right questions to be asking now and will also help further separate you from those who fall behind. Yeah. That's great, guys. I really appreciate, you know, you joining me today and talking through some of these items. I do have one final question though for each of you. What excites you most about the future of AI in business? And do you think that we're just now scratching the surface of what's possible? So I'll answer the last the second part. I guess there was two questions. I apologize. No. It's two questions. It's a sign of a good interviewer. Yeah. You know? Yeah. Yeah. I think we're just scratching the surface. Abs- absolutely. There's no doubt about it. What excites me the most is the unknown. You know, I think we you know, discovering all of these various implementations and the process of rewiring our brains and how we think. And I mean, this is, you know, this is me. This is Brian. This is you. This these are this is everyone really having to rethink how we operate. And, that's exciting. You know? I mean, because that means that we are evolving. And, yeah, that's really what excites me the most. So we are scratching the surface. Yep. Hundred percent agree. What excites me the most is, you know, what's far beyond what we already think AI is possible. I think most Americans at least think of AI as ChatGPT or the conversational, you know, GPT style. It's generally what people are talking about. There's so much more that that AI can do when it comes to how we manage data. And if there's the one thing that's growing in our world, it's the amount of data that we have. Yep. And seeing ways that we can leverage, you know, this data ultimately into knowledge and into difference makers in our own lives, in in our businesses, that's the part of it that that's really exciting for me. Yeah. Great. No wrong answer there. So appreciate you guys' time today. And, you know, thank you so much. And have a great day. Alright. Thanks, Garrett. Thanks, Garrett. Yep. Appreciate it.
