Syncing with ServiceNow: C-suite point of view: Top 5 challenges to AI adoption

Generative AI (GenAI) has disrupted how virtually every organization operates. In fact, 81% of organizations around the globe plan to increase their AI spend next year, according to the Enterprise AI Maturity Index by ServiceNow and Oxford Economics. But are they fully prepared to tap into the opportunities?

Host: Andy Whiteside
Co-host: Mike Sabia
Co-host: Eddie McDonald

Transcript

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Andy Whiteside: Hello, everyone! Welcome to Episode 40 of syncing with service. Now I'm your host, Andy Whiteside. I've got Eddie Mcdonald with me today, just the 2 of us gonna be good. We can have a little back and forth

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Andy Whiteside: without all those other guys trying to talk over top of us. I'm just kidding kind of sort of

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Andy Whiteside: so before we get started, let me do the the Zintegra commercials integra is a service. Now, partner, I am a super excited that we're having conversations with customers of all sizes, helping customers of all sizes with service. Now.

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Andy Whiteside: you know, I was listening to a podcast around Fred Luddy yesterday, Eddie, that talked about the history and where the company came from, and the very beginning they had a problem. They would go to customers with this, with this platform that didn't really do anything. But then customers would say, Well, what does it do? And it says, Well, you can do anything with it, and that I thought that was a really interesting statement. And then what they started to do they started to build out, you know, workflows within it, so they'd have something to sell. And then customers started coming to them with workflows that they wanted in it.

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Andy Whiteside: and they could either develop them to sell themselves or service now would develop it within the product over time. And I thought about you guys, and when I hear you talk about all the time. That's kind of y'all story in it.

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Eddie McDonald: It does. And I love that story. It reminds me of the Steve Jobs story when he created his 1st quote computer. That was nothing more than the than the Primary Board. It didn't have a screen, or a mouse or a keyboard, and the guy was like, what does this thing do. It's like it does whatever you want it to do. He needed to put it all together, and that's the same thing. Fred created the the structure.

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Eddie McDonald: but he didn't have anything that was customer facing. And once he did that with Itsm to be able to create the automation around ticket creation, the thing exploded. So yeah, I really love that story.

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Andy Whiteside: And then Cloud happened, and Itil happened. And it went from being, you know, just a bunch of computer hacks running the it to actual professionals running it. And next thing you know, everybody needed each other. And this thing was what brought them together in a business way. That's the service. Now story, I can't wait to have my kids listen to the podcast and make sure. They understand that because if you just understand that, then you know how to start every service. Now, conversation with every client out there, whether they're existing or whether they're new

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Andy Whiteside: and help them get on the right page. And I say all that, because that's the Zintegra commercial. That's what we're out here to do is to simplify what it means to adopt service. Now, whether it's in it, or in finance, or Hr. Or all across the the company, and then turn around and be a partner that can help you get that implemented, supported and help you grow it to the next phase

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Andy Whiteside: and doing podcasts like this is just just part of the reason, part of the ways. We do that is, to proactively get in front of these conversations and lead them with what I call, you know, content with context, where we have a discussion, and people get to hear our thoughts on something. Service now is put together in a blog.

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Eddie McDonald: Yeah. And you know, that's a really interesting point. Because service now, I mean.

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Eddie McDonald: it does so much, of course, but a lot of people don't understand what it can actually do. So I was just in Tampa this last week, and you know I do a little presentation, and each time I do one of these presentations. I give a real world example of something that I've built in my past. I had a background development. So

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Eddie McDonald: I was talking about as an engagement manager. Every time we got a new project I'd have to go in and create the project in service. Now I'd have to create all the associated tasks, all the workflows, the the, you know, resourcing all of that. And it was took a couple of hours, and what I did is, I spent 8 or 9 h and created 3 or 4 project templates depending on the type of project. I could click a button

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Eddie McDonald: and it would spin up the project, and it saved our entire Pm. Team something like 800 HA year off of 10 h of work, and it was so easy. So I use as an example of to your point. It can do so much, and our job is to identify what those challenges are, and creatively come up with solutions with our customers.

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Andy Whiteside: Appropriately where it meets the customer's needs. It's cost effective, and it tees them up for the future, no matter what that future is.

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Eddie McDonald: Yeah, hey, Mike? Sabia joined us. Look at that! What's up, Mike?

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Mike Sabia: I was busy, busy apologies. I thought another had another half hour good afternoon.

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Eddie McDonald: That's alright. Well, we we were. We were talking smack about you. So you have to listen to what we said.

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Andy Whiteside: Well, I was saying, I'm sure myself has helping a customer. Just like we're saying here on the podcast you're out doing so no matter what the answer was. That's the answer, yeah.

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Mike Sabia: Indeed.

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Andy Whiteside: So Mike, Eddie and I identified this this blog. We're going to go over today. It's called C-suite point of view

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Andy Whiteside: top. AI top top. 5 challenges to AI adoption, and it's by Vijay Kotu is how I'm going to say the last name. It's from August 15, th 2024,

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Andy Whiteside: I listen to a ton of podcasts. As you guys know, we do a handful of podcasts. But I listen to a ton and this thing about what to do with AI and how to make it make sense is reoccurring no matter, whether it's a technology podcast, to podcast, around a specific platform, like service now in this case. But more often than not, it's the business guys trying to figure out where this thing's going, and all I all I can tell at this point is, they all don't want to miss out. So they're all investing. But they're not sure where it's going.

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Andy Whiteside: We are in an interesting space specifically around service now in this conversation. But it could be Citrix, it could be vmware. It could be Microsoft.

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Andy Whiteside: Every vendor we work with is adding AI into what they're doing. And so it's somewhat simple for us, because all our job is is to help that vendor's vision of AI get to its customers whether it's a future customer existing customer. And so that's why, you know, companies like service now want partners like us to be, you know, in thought, leadership, and helping explain what AI is to their clients, and why it matters.

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Eddie McDonald: Yeah. And and what does it do? I mean, that's a big, I mean, everybody knows they need it. But you know, is it productivity based, is it?

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Eddie McDonald: is it about? Experience is about building your business? I mean, what does it do? And by the way, it does all 3 of those things but it really depends on. As we said a second ago, what's the business case? And how do you step into it like anything else you're not gonna pull into. You're not gonna go to the run phase out of the gate. You're gonna crawl, walk, run into it because it's also data driven. So it's gonna get better over time.

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Andy Whiteside: So, Eddie, going back to the conversation a few minutes ago, you know the computer, Steve Jobs. What does it do? Well, it does what you tell it to do. This is where it gets interesting. It does what it needs to do, not necessarily what you have to tell it to do now all of a sudden, with that data, and with the learning that goes along with it, it gets proactive instead of reactive, like that old calculator which is reactive to what you plugged into it. The computers up to this point have been kind of reactive.

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Andy Whiteside: Now, all of a sudden it starts to think on its own, a little scary from time to time, but when it comes to doing good business things, it really can change the results of.

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Eddie McDonald: I want to use a quick little example before we jump into this, because I was noodling on this a few days ago about AI, and it's not just the AI, but it's the people who use it have to learn how to use it. And I use the example of

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Eddie McDonald: when

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Eddie McDonald: you 1st got your 1st keyboard, and you didn't know how to type. Writing was actually faster than typing, because you didn't know where anything is. Now, once you know how to use a keyboard. You can type exponentially faster than you can write, and AI is the same thing. You're going to have to get used to it and understand what it can do, and it's going to get super super fast and convenient. It might seem clunky out of the gate, but it's going to get better over time.

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Andy Whiteside: I'm I'm not sure if Mike's gonna get a word in here because I'm gonna jump.

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Mike Sabia: I want to get a couple words in there and.

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Andy Whiteside: Let me get one more. Let me get one more. I look at it as like a coach or a tutor. When I 1st started using a coach, or, better yet, in school, a tutor. It didn't really work until I learned how to use the tutor or the coach, and then all of a sudden it made it exponentially valuable to have that resource, but I had to. Really. I had to train myself on how to use it, and then it became super valuable. Mike, go ahead.

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Mike Sabia: Well, I I think Eddie's example is a great one, especially when you need to choose to use AI. If you want to say, hey, I have a case, and I wanted to summarize it before I send an email to customer. That is your decision to use AI and service now absolutely supports it. But there are other AI situations where, as leaders, we need to decide. Hey, this is a place we need to put it in place. But what is in once it is in place. An individual doesn't need to do to decide. And I'll give you an example. So

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Mike Sabia: today

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Mike Sabia: we might have a number of servers, and we might see that there should be an alert when disk drive hits 80%.

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Mike Sabia: Now, if we want to wait until it hits 80% or 95%. You can do that. But with AI we can see, hey, this draft drive is at at 78%, just below our 88% threshold. But it's stable

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Mike Sabia: that should be less concerned than a disk drive that is, at 70% still below, but is ramping up quickly

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Mike Sabia: if we can have the AI. Look at those things intelligently, say, Hey, this is an up and coming issue. What is likely to impact you within next week.

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Mike Sabia: Then we can operationalize and improve, and that's something can be set up without an individual deciding to to choose AI

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Mike Sabia: and.

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Andy Whiteside: And, Mike, I love that you gave that example on something very tactical within it. And then the future that you know very you know, expanded out around other lines of business like Hr. For example, like it might be able to predict when an employee is, gonna you know, retire or resign.

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Andy Whiteside: you know, weeks or months before the manager can.

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Mike Sabia: Potentially.

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Mike Sabia: And you know, you have to have some false positives. You don't wanna like start, you know, putting

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Mike Sabia: people on notice or or the link based on some suppositions. But you want to highlight the possibility and then act upon it.

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Andy Whiteside: Well, maybe if that.

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Eddie McDonald: Can it predict when I'm gonna ask for a raise cause? That would be nice to know.

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Andy Whiteside: Every everybody can predict that one.

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Andy Whiteside: But I guess maybe a different example is somebody's onboarding. Experience isn't going the way it should. It can proactively tell you that. So you, as a manager, can jump in and and start to fix it versus, you know, having to hear a brand new employee complain about being unhappy.

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Eddie McDonald: Absolutely. And I mean as a perfect example of that is, how long does it take to complete their onboarding task? You can evaluate? You know all of those tasks. It's like this person took twice as long as it should have. What is wrong there, let's get ahead of that. So we didn't get a mishire.

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Andy Whiteside: Yeah.

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Andy Whiteside: all right. So let me kind of read the the starting, the opening paragraph generative, AI Gen. AI has disrupted how virtually every organization operates, in fact, 81% of organizations around the Globe plan to increase their AI spend next year according to enterprise, AI maturity index by service now, and Oxford economics. But are they fully prepared

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Andy Whiteside: for this opportunity, and how to take advantage of it? And then it goes on to talk about some research that was done recently, and the takeaway from the Idc. World worldwide CEO survey from 2024, and from that they deduced 4 or 5 of the following takeaways, I'm gonna start with the 1st one here. Measure. Return on AI investments, Mike, what is that? And why does it matter for the CEO.

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Mike Sabia: Well, let me use an analogy right off. So

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Mike Sabia: service now has a cost impact. And for Tom something like software asset management, Sam.

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Mike Sabia: there is a not insignificant cost to set that up, but once you set it up.

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Mike Sabia: the savings outweigh the costs considerably, and with AI investments you need to choose

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Mike Sabia: where you can invest it and have a business case or proof that you're gonna have the return you're expecting. So if you want to say, hey? We wanna have case summarization so that the next person looking at a ticket or the end user, looking at the the ticket afterwards gets a quick summary without having to read all through all that that sounds fantastic. But you kind of need to prove

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Mike Sabia: where that the the savings match your investment to it.

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Eddie McDonald: And you need to do it beforehand. You just can't be all enamored with AI implement it. So we need to have what are the impacts that we're looking for. How can we measure those impacts to justify the cost? Because we have to look at the investment of AI, and then look at what the results are going to be, to make sure there's a business case there, just like anything else in it.

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Andy Whiteside: But but, Eddie, I think for years and years and years people have been enabled with, let's say, Cloud, and they couldn't justify financially going there, but they were going there anyway. I'm not so sure AI is not like that, too.

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Eddie McDonald: If it's going to well, it it depends on the type of organization. You know the cloud, the the whole cloud conversation, is one we can definitely have. But as far as the AI comes in.

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Eddie McDonald: I look at it as another tool in the service now, suite, and like anytime I'm looking at

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Eddie McDonald: asset management or Hr. Security operations. I need to understand your cost. Where? The where the stumbling blocks what do you want to get better? And then I have to analyze that financially. So as far as our role as integra, we need to make sure that every single thing that we're implementing for a customer means it makes sense from a business standpoint, and that's what we have to do. We have to find out what that cost looks like.

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Andy Whiteside: Mike anything else. To add to this, this 1st topic around measuring return.

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Mike Sabia: no, I think we've covered it fairly well.

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Andy Whiteside: All right. Topic number 2 is AI governance.

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Andy Whiteside: I didn't really.

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Andy Whiteside: I mean, I hear on my political podcast and I'm talking about what to do around AI at the government level. And then somebody has a product that I was talking to the other day. And not only they talk about the, you know, governing it.

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Andy Whiteside: you know, within our government, but also at the corporate level, and and making sure it aligns with the corporate strategy and policies.

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Andy Whiteside: Eddie, I'll come to you 1st on this AI governance governance. Why is that so important.

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Eddie McDonald: Well, because people are scared, they're scared of it, you know. What's it gonna do? What is it? What data is it gonna have access to who's gonna have access to the data? You know, there's there's private personal data that can't be. You know, it's what does the AI have access to. And how do we govern that so service now? They actually built a governance app

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Eddie McDonald: to manage the inventory of their AI models, including data, security, privacy and performance, but that is something that service now got ahead of. They wanted to make sure that they could measure or control, you know. Put the guardrails around the AI that are implemented, based upon what the customer needs.

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Eddie McDonald: My thoughts.

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Mike Sabia: For sure. So I have a I have a friend, a buddy, and he's an account, and his company has standards about using AI. They're allowed to use it. But they have to only use abstract questions. Hey, find me the policy on this, this, this great but you can't feed it any data that would represent the customer. And when we talk about service now, and it's language models, Llm. Service now has its own Ll.

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Mike Sabia: Excuse its own Llm. In order to send that information within the service. Now ecosystem, but not outward. Now it is possible to extend service now to actually directly you know, query, chat, gpt, or open AI or the like, and that's possible.

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Mike Sabia: But if you're looking to leverage, what service now has provided already? Has some of that governance around it. But, as Eddie says, you need to have some governance about what you're doing.

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Mike Sabia: why, you're doing it

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Mike Sabia: to have cleared clarity, not only for your end users, but your C-suite and the like.

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Eddie McDonald: If anybody's unaware if they're not, you know, used to using virtual agents. Llm. Stands for large language models. So Mike was. There was just make sure everybody listening understands what that means.

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Andy Whiteside: So I'm seeing products like the one I was kind of alluding to a minute ago. Pop up where there's companies that have software that sits in front of your AI usage or your AI development to make sure it aligns with company strategy, or maybe government regulations. It's regulating AI within a company, or the government is going to be a big business all in itself.

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Andy Whiteside: so let's see Mike back to you, because you're probably a great person to talk to this one about as a master architect, AI skills and talent strategy.

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Andy Whiteside: I people have to be curious and interested on how they're going to get there, and how they're going to keep up.

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Mike Sabia: Well, any customer who's looking to leverage AI absolutely wants to work with a partner who is familiar with AI in general, and what service now provides. And you know Eddie and I were talking about this this just this morning about how we can ensure that we use integra are up to the challenge, and

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Mike Sabia: any customer who comes to us today we'll have some of those same talking points. We'll talk about the value. We'll talk about governance. We'll talk about the skills we have, what talents we have to accomplish that. And you know, as with any company, we're going to be growing, that we're going to be making sure the appropriate people, not just Eddie and myself are fully familiar.

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Mike Sabia: So you know, abstractly.

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Mike Sabia: you want to make sure that you have the correct people not say, Hey, we're implementing AI. You want to have the the business process. People aware of what you're accomplishing. You want technical people like myself or my colleagues to say.

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Mike Sabia: What does this mean to actually implement it? What does it mean to structure it in an appropriate way? What does it mean to to do it in an appropriate way?

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Andy Whiteside: This, this article or this paragraph or section of the article it starts off with. According to Idc research, 60% of Ceos report, the organizations don't have the skills

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Andy Whiteside: to implement AI initiatives. That's probably higher than that. To be honest with you. And then it goes on to talk about what service now is doing. So I love that Mike brought up what we're doing, because at the end of the day every customer, no matter how big or small. How successful or not successful they should have a partner. They can lean on for service now, and AI pieces, or both, vice versa even. But there's there's this next part talks about service now, believing in low code and no code AI development. And while that's true

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Andy Whiteside: that didn't say low code, no code or unskilled, there's still gonna have to be skills that go along with that to be able to coach the solutions and train the solutions. Or, you know, tee up the solutions, and then how to know how to get the most out of the solutions. Eddie, do you agree with that?

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Eddie McDonald: I do, and and to your point. Yes, low code and no code is, are very buzzworthy. But you're absolutely need a technical expert and service. Now to do this, but more importantly, it always begins with process

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Eddie McDonald: and to try to implement something like AI strategy into a broken process is only gonna make that broken process dance. We have to make sure you're following good or best practice around AI and around whatever process we're putting they on top of to make sure that you're gonna get the value. And that's what we do. Or I mean, our entire team is, I told V 4 certified. So we are gonna have those best practice conversations before we even get into the technical.

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Andy Whiteside: So because I'm gonna I'm gonna skip number 4,

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Andy Whiteside: because Number 5 always comes out to me. 1st ahead of Number 4, number 4 is probably the one that trumps them all, I guess, but Number 5 is prioritizing the right use cases.

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Andy Whiteside: How do you do that when there's so many use cases that you see evolving in front of you

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Andy Whiteside: by the minute.

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Eddie McDonald: Well, it it. I think it goes back to what we talked about a minute ago about finding the business case, so you know, you might need it in your help desk. You might need it in your project management team. You might need it in your security team.

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Eddie McDonald: But if you've got 80 people on your help desk, and you have 5 project managers, you know, looking at the business case. If we can save your help desk people 30 min a day each, and we can save your project managers an hour a day each. It makes way more sense to implement the use case around the biggest return on investment for your help desk. So I think it would start there.

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Mike Sabia: And I. I would also tie in them business imperatives. Hey, what are you trying to improve? You know, when we do a service. Now implementation, we want to say, we ask the question, Hey, what are you trying to improve? Are you simply need us a a product that replaces something that's no longer supported that that's pretty straightforward. But if you're looking to increase customer satisfaction either, hey? These

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Mike Sabia: that the the interface is old and clunky, or hey? I want to improve customer interface customer experience because I want to be proactively aware of issues before they happen. Or I want to increase kpis around time to resolve tickets. It all depends on the the Kpi. What imperative you want to approve. And if this customer satisfaction we're gonna focus on

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Mike Sabia: case summarization, or some of that proactive assessment. If you're looking up at, you know, time to speed up the process. Those are different. AI challenges. And that's where we would focus.

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Andy Whiteside: I heard process improvement. I heard customer satisfaction, I heard cost reduction or avoidance.

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Andy Whiteside: I mean, then they could just keep coming like like I don't. I don't know how we do it. I don't know how you guys do it on your team.

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Andy Whiteside: I don't know how you guys help a customer figure that out, or do they just typically come with their priorities

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Andy Whiteside: and we help them with their priorities? Or do we push back, trying to point them to better places, to prioritize first.st

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Eddie McDonald: We ask really good questions, we ask questions that make them unfold their dirty laundry.

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Mike Sabia: There's a lot of partners who will listen. Say, Hey, this is what you want, and they'll do it. But we try to be a little more proactive. Say, hey! What are you really trying to accomplish?

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Eddie McDonald: Sometimes that means we have to go a little bit up the food chain, because what's important to the help desk manager might not be as important to the director of it. So we need to understand what the overarching we're gonna we're gonna address the tactical while keeping the strategic back of mind.

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Andy Whiteside: Yeah, I I don't know what you just said. That made me think about it. But in the podcast. Again, listen to the story of service now, and they they talked about it just being a help desk tool. And it's just like what I say to people all the time. If if you're looking at a help desk tool you, you don't need it because you're you're gonna woefully under leverage it.

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Andy Whiteside: Alright number 4 and this is what I assume most Ceos care about the most. Maybe not. Maybe if they're thinking about driving their business forward. But the the cost concerns

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Andy Whiteside: AI is going to be expensive, and there's no guarantee that you're going to get your money back out of it.

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Andy Whiteside: But I don't think companies can afford not to let me read the quote here. They have call it out in the picture here Idc. Predicts that by 2026 organizations infusing AI into their business models could see double the revenue growth compared to their peers

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Andy Whiteside: guys. Is that rhetoric? Or is that real.

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Mike Sabia: Potentially it could be when we were at not the Knowledge Conference back in May. One of the big presentations they had was a little

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Mike Sabia: bakery, and they were using AI to determine when

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Mike Sabia: customers would come through the door. Oh, there's a conference next door. Oh, this is the student season. Oh, this is how many we're selling now, and all of those things informed how many

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Mike Sabia: buffins, or bread or donuts they they created, and so it can directly

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Mike Sabia: affect sales absolutely. But that

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Mike Sabia: means that you have a a way to measure all of those items. So you know, we talked a little bit, you know about the customer satisfaction. And and you know,

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Mike Sabia: proactive identification of possible alerts. But if you want to really go even a further state, you need to go back to the business process. What are you trying to accomplish?

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Mike Sabia: And and how is that gonna improve? Maybe your your revenue.

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Eddie McDonald: And it goes back to use it. You have to use it. And Mike and I had a conversation, and Fred Reynolds and I had the same conversation

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Eddie McDonald: way way. More often than not. We talk to a customer, and they aren't using a fraction of what they're currently licensed for. And their service now, environment. So if they got itsm, that includes incident, problem, change, knowledge, request, asset seem to be virtual agent. And they're using 3 of those applications. So there's they wonder why they're not getting the value.

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Eddie McDonald: This is the same thing. If you're gonna license, the AI, we need to understand your immediate business case and all the other associated cases where we can apply this tool to get that value. So the cost concern is valid.

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Eddie McDonald: But they have to be, they have to put their resistance to change in their pocket and look at what's possible. If they're going to make the investment.

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Andy Whiteside: Well, and you know we talked about our commercial at the beginning of this. There, there are a ton of customers out there that have implemented service now, and now they're talking about doing AI with it, and they really haven't gotten the value out of it that they started to get out of it, and that's just that's the easiest opportunity for us to come in and help a customer right the ship around service now and prepare them for the AI investment that's gonna help them. You know, with this what this quote.

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Eddie McDonald: 100%. I would all I would actually push back on somebody trying to implement AI into a really

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Eddie McDonald: terribly implemented existing platform. We need to clean it up, put it on stable ground, nice foundation and scale from there.

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Andy Whiteside: Yeah, which goes back to the you know the origin of this whole platform around getting a common database for all things it so that you, you have a platform. You have a foundation, and you can make smart decisions going from going from that that that position of knowledge.

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Andy Whiteside: I think we covered what we did cover. We covered the 5. Says the bottom line is AI adoption presents a transformative opportunity for business leaders must navigate these 5 challenges to realize the full potential of AI staying, proactive and adaptable, adaptable, extremely important to what's coming next. Mike, as a recap, or as a summary of this, anything we didn't cover. You think matters.

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Mike Sabia: I think we covered a lot. You need your use cases, but and you need a foundation as just Eddie just mentioned. If you're not fully utilizing the product, it might be better to consider those before we jump into AI. But knowing that AI is possible, knowing that you have a platform that can grow to it is super helpful.

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Mike Sabia: But as you start considering AI, look at what your imperatives are, look at what you're trying to improve. Maybe it's something customer satisfaction. Maybe it's being proactive. Maybe it's, you know, speeding up your ticketing. But if you want to go even further into hey? How do we change your business model? That's even further discussion, possibly beyond just service now.

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Mike Sabia: But service now provides a great framework for starting a governance to keep it secure to enable to, you know. Get your your foot in the door, and then grow from there.

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Andy Whiteside: Yeah, I love that you brought that up, because, like, you know what we see it. Service now brings all of our tech and other things together, and then does like allows us to do things with that data, you know, back out service. Now in that model the AI associated with it could be AI, enabling for all the other stuff it touches.

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Eddie McDonald: Yeah. And and at the end of the day, you know anybody listening to this? If you're still a novice in AI, and most people are.

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Eddie McDonald: You just have to put that resistance to change in your pocket like I said, you've got to embrace it because it's inevitable. It's coming, either gonna get on board or get left behind. So do your research, you know, reach out, ask us some questions. We're happy to meet with you, whether you're an internal folk a service. Now, you know seller or a customer, we're welcome to share our our knowledge and expertise.

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Eddie McDonald: But at the end of the day it's gonna have to be a switch that goes off internally with each person that says, yes, let's do it. Let's get a plan together and execute.

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Andy Whiteside: Yeah, yeah, we're we're building this for that moment

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Andy Whiteside: with the idea that we're gonna help customers once. And it's gonna create this. You know flywheel effect where we're helping them

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Andy Whiteside: achieve. You know what the what the article says, which is by 2026, you know double revenues well, that

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Andy Whiteside: in theory with AI is just going to continue to evolve and happen and happen and happen. And the companies take advantage of it

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Andy Whiteside: are going to get the benefit. The companies that don't will be left behind.

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Eddie McDonald: Yeah. 100%.

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Eddie McDonald: Yep.

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Andy Whiteside: Well, guys, I appreciate the time today and look forward to doing this again in 2 weeks.

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Eddie McDonald: Alright. Very good. Thanks. Guys.

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Andy Whiteside: Enjoy the rest of your week.