#60: On the Frontline - How AI is Shaping the Future of High Volume Recruiting

Speaker A: Welcome to the Changing State of Talent Acquisition, where your hosts, Graham Thornton and M. Martin Kred, share their unfiltered takes on what's happening in the world of talent acquisition today. Each week brings new guests who share their stories on the tools, trends, and technologies currently impacting the changing state of talent acquisition. Have feedback or want to join the show, head on over to changestate IO. Um, and now onto this week's episode.

Speaker B: All right, and, uh, we're back with another episode of the Changing State of Talent Acquisition podcast. Super excited for our next guest, Sean Baer, CEO of Fountain. Sean, welcome to the show.

Speaker C: Hey, Graham, Marty. It's great to be with you guys. Thanks for having me.

Speaker B: Of course. Well, we like to start with a real softball. We hope it's an easy one, but love hearing about everyone's journey. We'd love to hear what led you to your current role as CEO of Fountain and, you know, maybe talk about some of the experiences all along the way that have impacted your perspective in your current role over there at Fountain.

Speaker C: Yeah, um, you know, obviously, by the way, this is the first time I've ever worked in sort of the world of talent acquisition and HR technology. So I'm fairly new, uh, to this world. My career has generally been focused on sort of enterprise B2B software. I've been fortunate to be part of four companies, Fountain being the fourth, but previously helped, uh, build a really big company in the E Commerce space, uh, again, doing B2B E commerce. Built a big company in the advertising technology space, built a big company in the automotive technology space, and now, uh, in the HR technology talent acquisition space. But I've always been focused on sort of how big companies and big industries adapt to new technology. And so that's kind of where I've focused my career, you know, with Fountain. I actually met the Fountain team when. When it was a very, very small team. It was a three, three or four people. And I said, you know what? I think they might be onto something. I actually wound up investing in the business, wound up joining and helping out the company along the way, and then a couple of years ago, became the CEO. And, uh, you know, it's been a. Just been an incredible experience. Great, um, team, great company in an industry, as, you know, and you guys talk about often an industry that's undergoing a lot of transformation, a lot of new technology and a lot of new opportunity for companies. So it's been a great couple of years working in this space and looking, uh, forward to what comes next.

Speaker D: We're thrilled to have you? And thanks for sharing the backstory. That's a pretty unconventional path to get into talent acquisition. And I'm curious, you know, what brought you to talent acquisition? Was it just connecting with these found folks, or did you have your eye on the space before that? And, um, maybe what has surprised you most as an outsider coming into this, uh, space?

Speaker C: Yeah. Um, you know, look, I've always been, you know, my. My third company, you know, dealt with a lot of frontline workers, and so I've always been interested in the frontline workforce. Right. You know, if you think about sort of. It's very easy when you, you know, you. You listen to podcasts and you. You're on Zoom Calls, or you sit behind a desk, or you kind of do hybrid work, or your company's fully remote. It's very easy to kind of get very deep into thinking this is how everybody in the world is. We all are on Zoom. We all work in Excel. We all deal with Google. And the reality is the vast majority of people in the world don't go on Zoom calls. They. They don't sit behind a computer or at a desk. You know, they're doing things in the front lines of our economy. They're delivering packages. They're working in a grocery store, they're working at a drugstore. They're working in, you know, a restaurant or a cafe. They work, uh, in a nursing home or a warehouse, or they drive a truck. And so I've been always focused on that population. I think the thing that really attracted me to Fountain was, you know, the mission of opening opportunities for that workforce. This is billions of people around the world who generally are on the front line of the economy and generally do not have great technology and great products to help them in their journey, in their work. Um, and so that's what really attracted me was this kind of, like, very large population of frontline workers. Now, I'll say part of it is altruistic. You know, our mission to open opportunities. As I tell the team, I think it's a. It's a mission worth doing. It's worthy of our effort here. As long as we are here on this earth, it's worthy of opening opportunities for this group of billions of people who do need more opportunity. Also, we happen to think it's a pretty good business. You know, we. We think, you know, the fact that there's billions of people who need to get jobs, who need to be supported in their career and people who are eventually going to look for another job and need to be Retained in the company opens up opportunities for Fountain itself. So that's what kind of drew me to it. Um, and I can say it's been way better than I even expected.

Speaker B: Yeah, well, I think that's super interesting, Sean. And, you know, obviously we followed, you know, Fountain's journey for a while. So very excited about this conversation. You know, last week, me, it was two weeks ago, we were on with one of our workforce partners. We lightcast for an episode. And, you know, one of the things I love about, you know, Lightcast is I think they have a similar, um, thought process on these large populations that, you know, arguably get, you know, neglected. Right. For lack of a better word, in, you know, in the talent acquisition space. And, you know, I think Fountain does. I think what's arguably been needed in the talent acquisition space is, you know, some disruptors that want to think about, you know, we'll call it higher volume hiring, know, with a different mindset. And, you know, what that means is, you know, I'm not going to say I'm on TikTok much, but I'm on TikTok enough to see, like, all these new memes and videos coming up about, you know, hey, what's the apply process, you know, and the 9,000 questions that you need to go, you know, through just to submit your application and your resume, you know, when you want to apply for jobs through a traditional ets? Yeah, I'm just curious, like, have there been any sort of triggers, you know, or maybe just, you know, wax poetic for me on why do you think it's taken so long for, you know, HR systems or processes to understand that, uh, hey, there's not one blanket approach to, you know, recruiting all populations.

Speaker C: Yeah, I would even say I even brought in your question there, Graham, which is, you know, why has it taken so long, not only in the recruiting process, but in the retention process? You know, we've. We've generally taken a one size fits all approach to workers and to employees. Employees. And the reality is it is just there are just fundamental differences when you're talking about hiring, you know, three or four finance people versus hiring three or 4,000 warehouse workers. If you try to apply the technology or the product the same to those two different worlds, you will wind up with very, very different experiences. You know, to give you an example, right. In the world of hiring a finance person, you probably ought to collect a resume and you ought to have multiple rounds of interviews and you might want to check references if you're hiring 3,000 warehouse workers. I would not Recommend collecting resume, by the way, we can have a longer conversation in another podcast about how valuable resumes are in general, but maybe that's another. Another whole episode. Um, but certainly in the frontline workforce, it is demonstrably less valuable. Someone's ability to put together a Word document with a couple of bullet points about their experience, save it as a PDF on their cell phone, which is where they're typically applying for these jobs, is probably not a great indicator that this is going to be a reliable person who's going to help me and help my, my warehouse operation run. It, um, just isn't, you know. And so I think one of the reasons it's taken so long, though, is the labor and the job market has not driven us to the point of needing to think differently. You know, if you go back four or five years, you know, it was a good labor market, certainly, but you could generally hire these frontline workers with relative ease. So even if you were inefficient in your applicant tracking system or in your internal processes, you still got the people you needed. That I think, in 2020 and 2021, certainly post Covid has just fundamentally changed. You know, you have some less labor participation. Um, you have people working fewer hours, and you need more people to power your business. And those old processes just don't work anymore. You know, I think the old mantra of, well, they're going to frontline workers will quit and we'll just replace them. The problem is frontline workers are still going to leave you for better opportunities, but it's not so easy to replace them anymore. And I think when you run into that, what you see is all of a sudden companies that have never been interested in innovation on their hiring process are all of a sudden very open to innovation in the hiring process. Because if they don't, you know, they're understaffed. And unlike a knowledge worker. Sorry to wax. You said wax poetic, so I'm taking your direction. But unlike a knowledge worker, you know, if you're a finance person, if your finance team is down one or two people, things still work. If your warehouse is down a couple of, you know, 40 workers because you're failing to hire in this competitive labor market, all of a sudden everybody's got to work overtime or the packages go out late, or the morale of the warehouse goes down because everybody is shouldering a bigger burden due to the lack of. The lack of staffing. And so there's real business impacts. And I think that's what's driving the innovation. Long answer to A very good question.

Speaker D: Yeah, well, I want to double click on this word innovation because, well, we hear that word a lot in our industry and um, from my perspective, I would hate. There's some basic things that the industry wasn't doing that are not new ideas. Like you pointed out, this idea of, hey, maybe we should treat warehouse workers and the apply path a little bit differently than hiring a SVP of finance or whatever the case may be. That seems obvious to me having grown up in my career in consumer marketing. It would be like purchasing a high value durable good like a refrigerator and applying the exact same marketing strategy to uh, a phone case sale. You know, like you wouldn't expect those two to have similar marketing strategies and you would by default take a different approach. I think the point is well taken that the industry or the labor market has forced this. But my bigger question, I suppose is any sense of why do you think the industry had to be forced into this? It just seems like a best practice. Don't we want to be efficient? Don't we want to treat people well? And I know it's a hard question, so if you don't know, that's totally fine. But I'm trying to make sense of it.

Speaker C: Yeah, yeah, it's a great question. Um, you know, what I would say is that two things, I think they're interesting. One, I definitely think there's some sort of necessity is the mother of invention. And so you see more of this happening as a result of sort of the, the uh, the need for innovation. But to your broader point about like, why now? Right. Is it only because the labor market has, has shifted? My sense is that you also have, you know, today's senior, senior HR leaders, you know, have spent basically their entire career in a world where there has been rapid innovation in software writ large. You know, like the people that started their career in say 1990, remember a time when most things were done with pen and paper. Right. The people that have started their career in 2000 or you know, 2010 and have spent the last 15 years moving up the ranks of the, the HR team at a large organization. They don't know, they don't even know the world, uh, before sort of real collaboration and real technical innovation. I mean that's been their whole career. I think some of today's chros basically got their role based on their ability to adapt to innovative technology along their career path. And so I think some of it is this sort of necessary because of the labor market, but I think some of it is today's Leaders are just schooled in how do I deploy technology across the HR tech stack. And the people that sort of started 10 or 15 years ago as sort of, you know, your HR analyst or your benefits administration or your, you know, your director, uh, of talent acquisition, all of a sudden those people are in the C suite now. And the way they got there was deploying innovative technology. So that's, that's my sense of why you're seeing more of it. But I, but I would take your point that some of this stuff feels pretty self evident. Asking, you know, a fast food worker to put a resume together feels, feels crazy. But I can right now. Lots and lots of employers are still stuck in that mindset.

Speaker B: Yeah, I think, um, you know, on some level, maybe we kind of forget or, you know, undervalued just how quickly things have moved over the last couple decades, I suppose. And you know, I think, you know, 20 years ago I went to, you know, IU and the first degree that my parents made me sign up for was an informatics degree. It was the first ever informatics program. No one knew what it was, so obviously I didn't graduate with an informatics degree, you know, and then 10 years later, you know, hanging out with one of my insurance clients, they're like, we need informat people that studied informatics. I'm like, well, I guess my parents are right. Yeah. You know, and there's that whole adage that, you know, hey, the top 10 jobs that'll be in demand, that are in demand today, you know, arguably didn't exist 10 years ago and the same is going to be true, you know, ten years from now.

Speaker C: From now.

Speaker B: Yeah. Yeah. So, you know, I had already, like, you know, hey, maybe that's just par for the course. And like, we're just, you know, our expectation is we should always be moving faster, but maybe we actually, maybe we are. Um, you know, when you zoom out a little bit, you know, thinking of that story of, you know, where people were 15 years ago in their careers. So that's fair. Well, you know, uh, I want to double click a little bit into, you know, this idea of, you know, where HR technology, you know, is going. You know, I think, you know, you touched on two things, Sean, that are super important. Right. We've got a lot of instant uncertainty or change in the broader labor market, the wider economy. I think a lot of TA leaders are being tasked to, uh, hear this phrase a million times, do more with less. But I also think we've got an industry where we've had a Lot of change in tools. We have a lot of new technologies that are being adopted. People are more open to changing their processes, looking at bolt on tools, trying to figure out where there's less bloat in HR tech stacks. So I'm curious, from your conversations with leaders, how are modern Chros, for example, approaching some of these calls for increased efficiencies? Or where are you seeing leaders think about how do we identify smart investments, adopting emerging technology, generative AI, uh, and so on? What are you hearing in your conversations with leaders?

Speaker C: Um, yeah, it's a broad question, but a great one. Graham. Um, a couple things I'd say. First of all, I think every HR leader today is being tasked with becoming more efficient. In fact, if you're not being tasked with becoming more efficient, you are the exception to the rule because the vast majority of CHROs and VP of HRs and VP of Talent Acquisition are being asked to use your phrase, do more with less, um, or do the same with less, um, or do the same, but do it better. You know, look, HR has always been a call center from the beginning of time. Today I think it's even being pressed further to find out can we recruit the right people and still spend 10% less. Right. The way that their incentives and the incentive specifically in the public company realm. Right. Being able to do more with less is a ticket to a higher stock price, which is what you're seeing I think across C Suites now is a focus on being even more efficient so we can become even more profitable so that our stock can get bid up and you know, appreciated by more investors, both retail and institutional. Um, so it's always been a call center. They are definitely feeling the pressure to, to do more with less. Two things that, that is, is that it? Addition to that one is they are all being asked to look at how AI is going to impact the world. Uh, of, of talent Acquisition and, and, and HR writ large. Um, every single company is absolutely looking at how it is now. Maybe they're not deploying it, you know, in, in large scale, maybe they're just experimenting. But there is absolutely a mantra of we need to be thinking about how is AI going to make us more efficient and better going forward. We see it across our entire customer base. So AI. I think there was some feeling that maybe smaller companies would be faster to adopt AI and the larger companies would be more conservative and take their time. I actually think it might be reversed. The larger companies are actually setting aside budgets, even saying I'm going to set aside 50,000 or $100,000 this year I want to do two or three experiments with AI, right. And we're seeing that everywhere. I think the second thing you're seeing is just a real focus on automation. Right. In order to do more with less, you've got to remove tasks that are, you, uh, know, low value tasks. So how do you automate tasks? And sometimes you use AI and sometimes you don't need AI to automate a task, but sometimes you do. And so I think those are the things you're seeing. I think you're being asked to be more efficient. You're being asked to invest in AI or at least experiment in AI and then you're being asked to deliver automation in a way that enables you to get the same kind of work done with far more efficiently.

Speaker D: Yeah, well, there's a lot of interesting follow ups there, I suppose. And I do want to talk about AI, but before we do that, I kind of want to just zoom out a bit, um, and pick your brain on something. So you shared an interesting insight earlier, which is that many of the people who are sitting in the C suite or the Chro, uh, have undergone an enormous amount of technological change in their careers. These are people who, as you pointed out, maybe started with a pen and a paper and a rotary phone on their desk at some point and now we're talking about AI. So it has been, um, a lot of change, I think, but one trend, and maybe you'll disagree, I don't know, in this industry, seems to be that we haven't necessarily always been good about the basic strategy components of this space. For our conversation earlier, why are we treating frontline workers the same as we're treating people we're trying to recruit for senior leadership? Probably doesn't make a lot of sense. And the solution, quote, unquote, I think historically in the last 20 years since the Internet came around, has been technology will be our savior. There's always some new bright, shiny object that people get excited about. You can understand why people get promoted for discovering new technology and saying this is going to be the salvation for whatever our woes are in the organization. And yet after successive waves of technology, there is a sense that organizations are bloated with technology. And one of the reasons may be that we didn't actually start with the strategy. We just thought that the technology was somehow going to fix everything. Which is, I guess, a long way of asking. Yeah, a long way of asking, is AI, uh, going to be any different? And maybe the bigger, broader question is, is there a way that technology can encourage, if not demand, that people take a strategic view so we can kind of grow as an industry while we're also implementing the latest technology.

Speaker C: Yeah, uh, Marty, great, brilliant question. Um, you know, look, if I'll answer your question and give you some, some thoughts on it, but I think one thing that's very clear and, and by the way, Silicon Valley is probably deserves some, some shade for this. Um, but we have this, this shiny object, you know, this, this next thing, this next tool, this next product, um, this next company. If we just buy this one piece of technology, then all our problems will be solved. I can tell you that. That narrative, I think, has run its course. And I think most companies are looking for less tools, less products, less innovative shiny technologies. Uh, and I think this is a sea change, to be honest. I think there was a time where I wanted the best, absolute best piece of software to do this one minute thing for me and I would buy it because it was shiny and it was cool. I think those days are over. I think companies have, have realized that if, if I have, in order to run my HR operation, if I have 50 different software shiny tools that my team is using, that's a lot of different tools. I got to get those tools to talk to each other. I've got to make sure they're all compliant. I've got to make sure that they're all being used. I got to make sure that they work together in some way. I got to make sure they're being used at all. Those days are over. I think your point of having a strategy and then seeing how pieces of technology fit into that strategy versus the reverse, which is just sort of, well, we probably ought to buy a performance review system. This is the best performance review system in the world. Let's get it. And by the way, I love all the performance review systems, uh, in the world. So I'm not trying to say anything bad about any of them, but just using them as an example of let's get the shiniest thing. That might not be the best idea going forward. The reason why I think AI is different and again, we'll have to see, the three of us will maybe hop back on in December and we'll see how this take translates, um, or lasts, uh, from now till then. By the way, the reason why I'm saying six months is, who knows? Things could dramatically change with AI in six months. But one thing that I do believe that's different about AI is we've even seen it be fundamental in terms of making you More efficient, not as a product, because if it's, uh, a. If it's a product, that's just another thing I have to manage. I'm talking about the underlying technology. Does it make me more efficient? I'll give you a perfect example. At Fountain today, you know, we can take a job description for a frontline worker. Okay, let's say you're looking, you're hiring a warehouse worker in, uh, Topeka or in, you know, Spokane, Washington. Okay. We can put that into an AI tool at Fountain, and we can. The. The AI will actually come up with a five, six, seven different ideas for how to attract different people to work at that job. Not only that, it will write the advertising copy that would appeal to each of those different Personas, and then it will actually post those ads to the right places with zero human beings. Yeah, like that is that process that I just described would normally have a team of five or six, you know, kind of thinking about who would work here. Okay, what should the ads say? What kind of images should the ads have? Let's test five different variations of the copy. By the way, Marty, you know this because, you know, you come from this world of marketing, uh, stuff, but, you know, that would be a team of five or six people that was done in 10 minutes with no human beings today at Fountain. Um, so that's why I is maybe a little bit different. But. But we'll see how that take lasts in six months.

Speaker D: Yeah. Yeah. Well, this is an interesting thread here though, Ron, so I'd like to spend a little more time on it. I just want to maybe restate what you said in my own words to make sure that I'm understanding how you think AI is different. So one of the challenges I think we had in the space is that we've been. The AI has been long promised, um, and disappointing. Uh, and it does seem like with these, um, chatgpt in various models, we're now seeing the real power of this. It's not just automation. There's some kind of thinking going on. And is that really the key difference here? Because I think the drumbeat over the last, say, five to ten years, um, which is about as long as I've been in the space, is machine learning. Uh, yes, AI, but automation. And you go to HR tech, everyone is saying these terms. And the reality is up until recently, up until some of these big shifts, we're seeing in big advances with AI, it was really just automation for the most part. And I think the trouble with that is if you don't have a strategy or you have a bad strategy, then you're just getting better at automating nothing or a bad strategy. And with AI in automation, of course, is about tasks ultimately, at least that's how I see it. And you're telling a machine to do, uh, a specific task over and over and over. And maybe the difference here, one way of talking about the difference with AI is that AI has the promise at least, or maybe it's already here, of not optimizing based on tasks, but optimizing based on goals. And so the goal is to achieve this outcome, hire these people, the best people we can, that will be this happy. And then you don't actually have to, then the CEO doesn't have to worry about the strategy in theory, because they will actually come up with a strategy that was missing all. Is that

Speaker C: right? I mean, look, one of the reasons why I'm, um, um, again, I am not yet sure about the product. So I don't, I wouldn't, you know, do I know which AI product and which delivery mechanism is going to work best? I don't yet. What I do know is that the underlying power of the technology, somebody will have the right delivery mechanism and that company will be very successful. But the underlying technology is incredibly powerful. If you sort of step back and just think about a company that has 10,000 workers, right? And let's say they're half of them work in the office and half of them are frontline workers, I'm making up a company I don't even know. Um, but that's 10,000 people. Just think about in a given year how much energy and time those 5,000 office workers spend writing documents, whether it be presentations or emails or word documents or summaries of meetings and different versions of one pagers and different advertising copy for their booth, uh, who knows, you know, across the whole board, across the, across the board everywhere. My instinct is that a lot of that work is going to get replaced by, by an AI, an AI technology. I won't say a product because I don't know what the delivery mechanism would be. But I think we're pretty close to a place where an AI, an off the shelf AI product can deliver almost as good of a one pager summary paragraph for an email as me and the three of us sitting around for a day wordsmithing every word. Now maybe, maybe we'll be better. Uh, hopefully we are. The three of us are working on it. But you know, with no work in five minutes, if I can get 80% as good that's pretty incredible. Anyway, we'll see how that goes.

Speaker B: Yeah, I think that's great. And like. Yeah, well, you know what I, what I think more than anything Sean, is like, you know, I think what AI is what people are realizing is the opportunity to what you just described, right. And I think what, maybe there was a little frustration is not the word, but I'll use it a little, um, hope that. I think what people Forget is like AI is going to get maybe 85% of the way they are using your document examples or creating videos or scripts or social media posts. We're still gonna have to check it. And like, I think maybe there are some unrealistic expectations that you know, we want it to be a hundred percent perfect and also be better than what we would have written out the gate. And like, okay, well that's, you know, let's, you know, let's not let perfect be the enemy, uh, of good here. Right? And like if we're 85% of the way there, is that better than having to your example, you know, a hundred people that are working on social media posts from scratch, is it better to have 10 working with, you know, 85 half baked ideas out the gate? And I think the answer is yes. And like, so I think there's going to be some interesting expectation setting and you know, I think there's going to be, it's going to be an exercise of really thinking through, you know, what are the new skills that are required, what are the new job categories that you know, are going to exist, you know, what does the workforce look like, knowing that there will be some rails that need to be put around, you know, utilizing AI for your different components. Does that, does that make sense, Sean?

Speaker C: Totally makes sense. Look, I think the other thing that it'd be interesting to see is I think we're in the early days of interacting with this technology. So generally today, if you think about like one of the biggest shifts of the last 20 years has been, you know, the birth and growth of search, search at you know, just uh, search engines and by proxy search advertising. But you know, there was a day, you know, two decades ago when people didn't type something into the Google box. You know, like that's not how you got information. And I can imagine the first time people interacted with it, they may not have loved the result. You know, they may have been like, well I searched, I was trying to get information on this and I didn't get what I wanted. You know, in fact, if you go before Google, many of Them were terrible. Right. Um, I think what you're seeing today, I think one of the things that's really interesting about the ChatGpts of the world, right, is I think people are treating the interaction of as it's a one and done game, meaning like, and to take it to kind of a casino analogy, right. They're treating chatgpt like it's roulette. Like each role has no relation to the role before it or the role to come after it. It's a one shot deal. I roll the ball and it comes on a number and then I start over with another one. One of the things that's really powerful about AI technology in general is that it has a memory. It's closer to blackjack than it is to roulette, meaning that I might ask it to write a first version of a one, uh, pager, opening paragraph. The first result I get is not the final. It's not like the game starts anew. I can then interact with it and say, actually I want to make it more professional or less professional. Can you make it shorter? Can you make it longer? Can you use bigger words? Can you make it sound like I went to a, uh, really fancy college? Can you make it sound like it'll appeal to people of all walks of life? Right. So you have this like, notion of a history where you can continue to improve on the product. And again, we see that with, with job descriptions. Right. Help me write a job description. Great. The first time it comes out, you know, hey, help me write a job description for barista. It's not, might not be perfect. It's missing a few things for me, particularly for my company. But I could say, hey, I need you to add a couple more things about, you know, how important it is to, uh, to love working here in our culture. Okay, great. Here's V2. Okay. You needed to sound less professional because we want to be more, uh, welcoming to people. Okay, great. I'll make it less professional. So that's where I think it's headed.

Speaker D: Yeah. Wow, this is such a fascinating topic. I mean, I'm trying to think how I want to ask this question. It's a big question. But earlier we were talking about strategy or the lack thereof that, uh, has been typical in HR and I think a strategy as well. When we're being strategic, we're asking lots of why questions. So we have a problem that we're trying to solve. We don't want to just solve the problem. We want to also understand why that is the solution. So we can Take that insight and hopefully apply it again in the future. So a client comes to us and says, hey, we need to hire a bunch of, uh, wind turbine technicians. Where should we, uh, hire them? It could be anywhere in the country currently, people hire us to do that work. We've put a lot of effort into it, look at a lot of data and make a recommendation. You're describing an AI future where we can just ask AI or not even ask it. Just, hey, we need 1,000 wind turbine type machines. Go find them. And it may actually do that. And this is an example to illustrate that. The point, I guess, is, do you think that AI is going to cause organizations to be more or less strategic going forward? You know, are we going to stop caring about the why? Because ultimately, what does it matter as long as we have our thousand wind turbine technicians, you know, who cares why? It happens to be that Boise is the best place for it, you know? Or do you think as organizations and as, uh, business leaders, we're still going to think about the why?

Speaker C: I think we're still thinking about somewhere,

Speaker D: even perhaps more so.

Speaker C: Yeah, I think we'll still think about

Speaker D: the why and AI will be able to tell us those answers.

Speaker C: Maybe back to the Fountain side, right? We use A.I. uh, throughout our hiring process. Right? So our, you know, we have AI that writes text messages to, to applicants and to workers. We use AI to ensure that people's driver's license and food safety handling certificates are valid and unexpired, um, and continue to be valid and aren't fraudulent. So we using AI throughout the process. I can tell you one place where not using AI in the actual decision to whether to hire a human being or not, that remains a human being, a unique human being experience. No AI is going to be able to do that. And I think, you know, I think we spend a lot of time worried about will AI, you know, lead to hiring mistakes at Fountain. We're very clear on that. We believe AI will help the process overall. But at the end of the day, no one is going to be able to determine whether another human being is going to be a good fit for the company and the team other than another human being. And so as much as we deploy AI, we still rely on that human, that human being to make that most critical decision. Should this person join the team or not. We think that's going to remain a, uh, human activity for a very long time.

Speaker B: That's great. I think that is the right place for us to pause this episode. Sean Reinforcement that like, yeah, is that going to take all of our jobs. No, the human element is still going to exist, still going to be there for sure. That's great. Well, let's end with probably the easiest question of all. And that's, you know, where can people find you online?

Speaker D: Sure.

Speaker C: Uh, really easy. Um, obviously you can learn a lot more about fountainfountain.com, uh, but you can find me on LinkedIn and I, uh, guess it's called Twitter now or X now, whatever it is. But, uh, LinkedIn and, uh, fountain.com.

Speaker B: awesome. We'll add all of, uh, the links in the show notes. Sean, this has been fantastic and, um, yeah, super, super interesting, uh, discussion. So really appreciate you joining us today.

Speaker C: Thanks so much, Graham. Thanks, Marty. Really appreciate it and fun to do it.

Speaker D: Thanks, Sean.

Speaker B: All right, thanks for tuning in as always. Head on over to Changestate I.O. or shoot us a note on all the social media. We'd love to hear from you and we'll check you guys next week.

Speaker A: It.