The Changing State of Talent Acquisition
The Changing State of Talent Acquisition cuts through the noise in the crowded world of recruitment marketing, employer branding, workforce intelligence, and AI.
Hosted by Graham Thornton, President of Consulting & Growth at Talivity, this podcast brings you unfiltered conversations with industry founders, practitioners, and the occasional contrarian who's actually doing the work – not just selling you on it.
We're not here to hype the next big thing. We're here to help you separate signal from noise, understand what's actually working (and what's just well-marketed), and make smarter, data-backed decisions about your talent strategy.
You'll hear from TA leaders navigating real hiring challenges, founders building solutions worth paying attention to, and experts who see around corners before the rest of us catch up.
Whether you're navigating the AI arms race, trying to figure out your tech stack, or just trying to hire better people faster – this is the podcast for people who care more about ROI than buzzwords.
The Changing State of Talent Acquisition
#60: On the Frontline – How AI is Shaping the Future of High Volume Recruiting
#60: On the Frontline – How AI is Shaping the Future of High Volume Recruiting
This week we welcome Sean Behr to the podcast. Sean is a successful entrepreneur spanning multiple industries, including e-commerce, advertising and automotive. Before joining Fountain as an investor and CEO, Sean held a number of founding and senior leadership roles at STRATIM, Adap.tv, and Shopping.com. He is also an active investor and advisor for numerous early stage companies, including Nana, AntHill, and Kinectic Eye, among others.
Topics include: the unique challenges and opportunities of frontline recruiting, the limitations of applying recruiting tactics and technologies designed for corporate roles to frontline roles, how the labor market is forcing organizations to consider new approaches to frontline recruiting, technological innovation in recruiting as an agent for (and impediment to) change, the increasing demands for efficiency in HR/TA, strategy vs. technology, task-based automation vs. goal-based automation, and the iterative nature of advances in artificial intelligence
Sean Behr
CEO, Fountain
Welcome to the Changing State of Talent Acquisition, where your hosts, graham Thornton and Martin Credd, 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 changestateio. And now on to this week's episode.
Speaker 2:All right and we're back with another episode of the Changing State of Town Acquisition Podcast. Super excited for our next guest, sean Baer. Ceo of Fountain. Sean, welcome to the show.
Speaker 3:Hey, graham, marty, it's great to be with you guys.
Speaker 2:Thanks for having me, 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 along the way that have impacted your perspective in your current role over there at Fountain.
Speaker 3:Yeah, 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 to this world. My career is 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 build a really big company in the e-commerce space, again doing B2B e-commerce, built a big company in the advertising technology space, built a big company in the e-commerce space, 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 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.
Speaker 3:You know, with Fountain I actually met the Fountain team when it was a very, very small team it was three or four people and I said you know what I think they might be on to 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 you know, it's been a just been an incredible experience, great team, great company in an industry, as you know, when 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 forward to what comes next.
Speaker 4:We're thrilled to have you and thanks for sharing the backstory. I think that's probably the well. We've had a little pass, I guess. But 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 maybe what has surprised you most as an outsider coming into this space?
Speaker 3:Yeah, 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, 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 Slides, and the reality is the vast majority of people in the world don't go on Zoom calls, they don't sit behind a computer or at a desk. 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 a restaurant or a cafe, they work 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. And so that's what really attracted me was this kind of like very large population of frontline workers.
Speaker 3: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 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. We think 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 a company opens up opportunities for Fountain itself. So that's what kind of drew me to it and I can say it's been way better than I even expected.
Speaker 2: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, maybe it was two weeks ago, we were on with one of our workforce partners, lightcast, for an episode. And you know, one of the things I love about, you know, lightcast is, I think they have a similar thought process on these large populations that you know arguably get, you know, neglected right, for lack of a better word 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, you 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 you know memes and videos coming up about.
Speaker 2:You know, hey, what's the apply process, you know, and the 9000 questions that you need to go through just to submit your application and your resume when you want to apply for a job through a traditional ETS, through a traditional ETS. Yeah, I'm just curious, like, have there been any sort of triggers. You know, or 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, hey, there's not one blanket approach to, you know, recruiting all populations?
Speaker 3:Yeah, I would even say I'd even broaden 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 generally taken a one-size-fits-all approach to workers and to 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. To give you an example 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 a resume.
Speaker 3:By the way, we can have a longer conversation in another podcast about how valuable resumes are in general, but maybe that's another whole episode. 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 warehouse operation run? It 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.
Speaker 3:That, I think, in 2020 and 2021, certainly post COVID has just fundamentally changed. You know, you have some less labor participation, 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 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, they're understaffed and unlike a knowledge worker.
Speaker 3:You said wax poetic, so I'm taking your direction, but unlike a knowledge worker, if 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's shouldering a bigger burden due to 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 4:Yeah, well, I want to double click on this word innovation because well, we hear that word a lot in our industry and you know, from my perspective I would hate there's some basic things that the industry wasn't doing that I would. That are not new ideas, you know, like, you pointed out this idea of hey, maybe we should treat warehouse workers and the apply path a little bit differently than hiring an SVP of finance or whatever the case may be. That seems obvious to me, having, you know, kind of grown up in my career in consumer marketing. It would be like saying, you know, purchasing a high value, durable good like a refrigerator, and applying the exact same marketing strategy to a phone, 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.
Speaker 4: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, I'm trying to make sense of it.
Speaker 3:Yeah, yeah, it's a great question. You know, what I would say is that two things I think that are 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 need for innovation. But to your broader point about like why now? Right, basically their entire career in a world where there's 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 2010 and have spent the last 15 years moving up the ranks of the HR team at a large organization, they don't know, they don't even know the world before sort of real collaboration and real technical innovation. I mean, that's been their whole career.
Speaker 3:I think some of today's CROs 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 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 my sense of why you're seeing more of it. But I would take your point that some of this stuff feels pretty self-evident. Asking a fast food worker to put a resume together feels crazy. But I can tell you right now lots and lots of employers are still stuck in that mindset.
Speaker 2:Yeah, I think you know, on some level maybe we kind of forget or, you know, undervalue 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. And then, 10 years later, you know, hanging out with one of my insurance clients were like we need informatics. People that studied informatics. I'm like, well, I guess my parents are right. Yeah, you know, there's that whole idea, is that you know, hey?
Speaker 2:the top 10 jobs that'll be in demand, that are in demand today.
Speaker 2:You know, arguably didn't exist 10 years ago and the same is going to be true, you know, 10 years from now, yeah so you know I've 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, when you zoom out a little bit, thinking of that story of where people were 15 years ago in their careers. That's fair. Well, I want to double click a little bit into this idea of where HR technology is going. I think you touched on a few things, sean, that are super important.
Speaker 2:Right, we've got a lot of uncertainty or change in the broader labor market, you know in the wider economy, you know I think a lot of TA leaders are being tasked to you know for this phrase a million times do more with us, right. But I also think we've got an industry where you know we've had a lot of change in tools. You know we have a lot of new technologies that you know are being adopted. People are more open to you know changing their processes. You know looking at bolt-on tools. You know trying to figure out where there's less bloat. And you know HR tech stacks from your conversations with leaders, you know how are modern. You know modern CHROs, for example. You know approaching some of these calls for you know increased efficiencies, or where are you seeing leaders thinking about? How do we identify smart investments? You know, adopting emerging technology, generative AI and so on. What are you hearing in your conversations with?
Speaker 3:leaders. Yeah, it's a broad question, but a great one, graham. A couple of 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.
Speaker 3:Majority of CHROs and VP of HRs and VP of talent acquisition are being asked, to use your phrase, do more with less, or do the same with less, 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 incentives 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 appreciated by more investors, both retail and institutional. So it's always been a call center. They are definitely feeling the pressure to do more with less.
Speaker 3:Two things that I'd say in addition to that one is they are all being asked to look at how AI is going to impact the world of talent acquisition and HR writ large. 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.
Speaker 3: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 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 4:Yeah, well, there's a lot of interesting follow-ups that I suppose. But maybe, 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, 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 you know, maybe you started with a pen and paper and a rotary phone on their desk at some point, and now we're talking about AI. So it has been a lot of change, I think.
Speaker 4: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. 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.
Speaker 1:Which is.
Speaker 4:I guess a long way of asking, yeah, a long way of asking. Is AI 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 3:Yeah, Marty, great, brilliant question. Look, I'll answer your question and give you some thoughts on it. But I think one thing that's very clear and and, by the way, Silicon Valley is probably deserve 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, less products, less innovative shiny technologies, and I think this is a sea change.
Speaker 3: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 realized that 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. Like those days are over.
Speaker 3: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 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, you know, the three of us will maybe hop back on in December and we'll see how this take translates, but or lasts from now until then. By the way, the reason why I'm saying six months is who knows, things could dramatically change with AI in six months.
Speaker 3: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 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 hiring a warehouse worker in Topeka or in you know, Spokane, Washington. Okay, we can put that into an AI tool at Fountain, Topeka. Or in Spokane, Washington. Okay, we can put that into an AI tool at Fountain, and the AI will actually come up with a five, six, seven different ideas for how to attract different people to work at that job. Okay, 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.
Speaker 4:Yeah.
Speaker 3:Like that is that process that I just described would normally have five, six, 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. You know, by the way, marty, you know this cause you, you know you come from this, this world of of, uh, marketing 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. So that's where I see AI as maybe a little bit different, but we'll see how that takes last in six months.
Speaker 4: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 and make sure that I'm understanding how you think AI is different. So one of the challenges I think we have in this space is that we've been AI has been long promised and disappointing, and it does seem like with these chat, gpt and various models, we're now seeing the real power of this.
Speaker 4:It's not just automation, there's some kind of thinking going on, and is that really the key difference here?
Speaker 4:Because I think the drumbeat over the last, say, five to 10 years, which is about as long as I've been in the space, is machine learning, yes, ai, but automation, and you go to HR tech.
Speaker 4: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, you know in, automation, of course, is about tasks ultimately at least that's how I see it and you're telling a machine to do some 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 worry about the strategy in theory, because the AI will actually come up with the strategy. That was missing all along Is that accurate.
Speaker 4:I think you're right.
Speaker 3:I think it's exactly right. I mean, look, one of the reasons why I'm again. I am not yet sure about the product, so 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.
Speaker 3:If you sort of step back and just think about a think about a company that has 10,000 workers, right, and let 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, but that's 10,000 people.
Speaker 3: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 you know, and different advertising copy for their booth, who knows, across the whole board, across the board, everywhere. My instinct is that a lot of that work is going to get replaced by 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 we'll be better. Hopefully we are. The three of us are working on it, but with no work. In five minutes, if I can get 80% as good, that's pretty incredible.
Speaker 2:Anyway, we'll see how that goes yeah, I think that's great. And like yeah, well, you know what I what, what I think, more anything sean's, like you know, I think what ai is, you know what people are realizing, is the 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 100 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 does not let perfect be the enemy of good here. Right, and like if we're 85% of the way there, is that better than having to?
Speaker 2: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, utilizing AI for your different components.
Speaker 3:Does that make sense, sean? Well, it totally makes sense. Look, I think the other thing that would 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, one of the biggest shifts of the last 20 years has been, you know, the birth and growth of search Search. You know just 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, I think what you're seeing today.
Speaker 3:I think one of the things that's really interesting about the chat GPTs of the world, right, is, I think people are treating the interaction of is it's a one and done game, meaning like and to take it to kind of a casino analogy, right, they're treating chat GPT 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-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.
Speaker 3: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 really fancy college? 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 really fancy college? Can you make it sound like it'll appeal to people of all walks of life? Right.
Speaker 3: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 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 can 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 welcoming to people. Okay, great, I'll make it less professional. So that's where I think it's headed.
Speaker 4: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 you know, earlier we were talking about strategy or the lack thereof. That 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.
Speaker 4:So a client comes to us and says, hey, we need to hire a bunch of wind turbine technicians. Where should we hire them? It can be anywhere in the country. Currently, people hire us to do that work. We put a lot of effort into it, look at a lot of data and make a recommendation us to do that work. We've put a lot of effort into it, look at a lot of data and make a recommendation.
Speaker 4:You're describing an AI future where we can just ask AI or not even ask it, just hey, we need a thousand 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? Are we going to stop caring about the why Because, ultimately, what does it matter as long as we have our 1,000 wind turbine technicians, who cares why? It happens to be that Boise is the best place for it? Or do you think, as organizations and as business leaders, we're still going to think about the why?
Speaker 3:I think we'll still think about the why.
Speaker 4:And AI will be able to tell us those answers.
Speaker 3:Maybe Check back in.
Speaker 3:December To bring it back to the fountain side. Right, we use AI throughout our hiring process, right. So we have AI that writes text messages 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 and continue to be valid and aren't fraudulent. So we're using AI throughout the process.
Speaker 3:I can tell you one place we're 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 being to make that most critical decision should this person join the team or not. We think that's going to remain a human activity for a very long time.
Speaker 2:That's great. I think that is the right place for us to pause this episode, Sean, and reinforce some of that Like, yeah, is anybody going to take all of our jobs? No, the human element is still going to exist.
Speaker 3:It's still going to be there for sure, that's great.
Speaker 2:Well, let's end with probably the easiest question of all, and that's you know, where can people find you online?
Speaker 3:Sure, Really easy. Obviously, you can learn a lot more about Fountain at fountaincom, but you can find me on LinkedIn and I guess it's called Twitter now or X now, whatever it is, but LinkedIn and fountaincom.
Speaker 2:We'll add all of the links in the show notes, sean. This has been fantastic and, yeah, super, super interesting discussion, so really appreciate you joining us today.
Speaker 3:Thanks so much, graham. Thanks, marty, really appreciate it and fun to do it. Thanks, Sean.
Speaker 2:All right, thanks for tuning in. As always, head on over to changestateio 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.