Karl Foster - Why Most AI Projects Fail: Sport Alliance's Head of AI on Change Management vs Technology

Hey friends, welcome to the future of fitness, a top-rated fitness and wellness industry podcast for over five years in running. I'm your host Eric Malzone and I have the honor of talking to entrepreneurs, innovators, and cutting-edge technology experts within the extremely fast-paced industries of fitness, wellness, and health sciences. If you like the show, we love it if you took three minutes of your day to leave us a nice supporter review wherever you consume your podcast. If you're interested in staying up to date with the future of fitness, go to futureofitness.co to subscribe and get weekly summaries dropped into your inbox. Now onto the show. Hey friends, I've had hundreds, if not thousands of conversations with gym owners and industry entrepreneurs. Some theme keeps coming up, the right technology can make or break your business. That's why I'm thrilled to introduce our new presenting sponsor, Perfect Gym. Perfect Gym isn't just another gym management system. They are part of the sport alliance group, Europe's leading fitness software company that has officially entered the US market. Now, I've seen this movie before, but here's the difference. They've opened up a US headquarters in Boston because they understand that the American market deserves dedicated, localized support. After digging into the platform, one benefit especially stood out. They are simplifying the nightmare that keeps business owners up at night migrations. These guys were able to migrate one mega client with more than 250 locations in six different countries in just 20 days between two payment runs. No disrupting operations, no member loss, one seamless operation that simply works. Now, if you have ever switched platforms, you know how terrifying that process can be and how truly impressive that fee is. At a high level, here's their secret sauce. They gave the power back to the operator. Instead of forcing you into their closed ecosystem, their perfect gym marketplace connects with over 120 integration partners. So, one of you's your own app, your preferred payment processor, class pass for booking, no problem. Whether you're running a single studio or managing a multi-location enterprise, perfect gym was built from the ground up for multi-club operations. They've invested a ton into this platform, and now they're bringing that European engineering excellence to America. The migration experts have arrived. Check out perfectjm.com where enterprise level sophistication meets operator freedom. All right, here we go. Carl Foster, welcome to the future of fitness, man. How are you? Good, thank you. Pleasure to meet you. Yeah, the pleasure. And you got the black t-shirt memo. So, check for both looking sharp. That's the real number one. Especially when you're talking about technology. I feel like when you're talking about technology, like black t-shirts are the way to go nowadays. It's just mysterious. But all right, man, so you oversee artificial intelligence efforts for support alliance. And we're going to get into a whole host of things, but I'm just going to start right now with kind of the big question straight up. I think a lot of operators are dealing with at this point. So, across the country here, operators are spending millions of dollars on technology, right? And there's big promises of artificial intelligence, automation with fancy labels on it. So what is the difference between AI that actually changes the members' experience and AI that's just basically a chap-bot with like some fancy skin and some clever marketing? Like, what do they need to be aware of? Yeah, it's a good question. I mean, there's quite a lot to unpack. But I think the main thing is, this has to be done with intent, right? So, I think it all starts with, you know, how you're approaching it as an organization. Are you serious about this? Is it senior leadership team serious about doing this? I often get asked, where should you be applying AI? I think the easy answers is kind of, you know, in the fitness sector and more on my experience should be on the members' lifecycle. And that's the easiest thing. How do you do it right? Do it with intent. Start small. Build the culture. Do all the things around the technology first and then look at how you can use the technology. I think that's the best starting point. Yeah. Yeah, great. Great. And we're going to give into all this stuff. And I should back up a little bit. Like, how did you get to be the head of AI for sport alliance? Like, how did that whole journey take place? It sounds like a pretty cool role. Yeah, it's awesome. I love it. Well, I've always been in the fitness industry my entire life. And I guess my kind of trajectory is a bit unique as a tech person. So started out as a PT when I was 18. Been in the gym space a long time. I'm just a natural nerd. And my brother's a software engineer. I've always kind of been involved in that space. I managed to kind of move up from a PT. I think my body started to break down in my early 20s and I couldn't train people anymore. So kind of went into the commercial space, operations, sales. And then managed to get some more involved in kind of the data side of things. We came to CTO in a big chain in the Middle East gym nation. We kind of at the time pioneered a lot of AI technology. We did a lot of stuff in the FinTech space. And then I had the opportunity to join sport alliance to kind of push AI in a much bigger scale and absolutely love it. Yeah. Maybe give us an idea. I think, you know, sport alliance is still fairly new to North America, right? Maybe remind listeners like how big this company is. Like how many operators you guys work with across Europe and UAE and on a global scale. Yeah. I think first just, you know, kind of what we do and what we have. So we've got a portfolio and we specialize in software for the fitness industry. So we've got 12,000 over 12,000 gyms now using our software around the globe. So Europe's quite a lot. We have Magic Line, which is more focused on kind of an SMB market, which is, you know, your CRM ERP. We have perfect gym, which is, you know, globally known as more of a larger enterprise mid-market and software. And we also have Finian Capital, which is FinTech vertical and payment vertical. And we have the app to go with it with my sports apps. So those are our companies, like I say, over 12,000 gyms. We're very excited about this new vision of ours for pushing the frontier of AI. I'm sure we're going to talk about that a lot today. And yeah, this is a great company to work for. Yeah. Yeah, it is, man. Every interaction I have with you guys is really, it's pleasurable. You know, everyone's, everyone's serious, like all business, but I don't know. It kind of has like this also laid back European vibe to it. Versus you know, the US, everyone's a little, can be a little aggro. So let's set the stage of the industry. Where do you think we are? The gap between AI hype and AI reality for gym operators right now. You know, that seems to be a very real thing. And I think a lot of people are suffering from it. And it's like every time you, I don't know about you, man, I mean, this is the world you live in, but I work with AI every day. And every time I feel like I get a grasp on it, I'm like, okay, I think it's starting to really start to optimize here in my workflow. And then if I just say, it makes a jump forward, right? And you're like, God, I gotta learn that. And so anyway, how is our industry doing? Like what's the state of AI in our industry overall? Yeah, I get asked this question a lot. I think like the first thing is that, you know, our industry is a bit of a dinosaur industry. And it's just because it's a passion industry, right? A lot of people open up gyms because they love fitness and, you know, they're not, you know, tech people. So it's always going to be behind. I think for me personally, the question of like, what is AI should I be looking at it? I think if you're still asking that in our industry, you're probably going to be in trouble very soon. That's definitely here to stay. I think the gap between the people who are pioneering, you know, a year or two ago, especially in automation and AI and machine learning, the gap between these guys and the ones who still aren't looking at it is increasing at a rapid rate for my personal experience. But I think people are starting to look at, you know, look at how they can do this seriously. And I think, you know, now's the time to do it, even with all the hype around it kind of disappearing. We're quite far behind, but lots of opportunity to be had. You know, I had a team on Erwin on this podcast, I think it was about six months ago. And one of the big topics that we got into, which I've used this term often since they brought it up, because I liked it so much. But being data aware versus data ready, I think that's, you know, an issue like I know most operators, a lot of people in the industry, even like in the online coaching space or, you know, anything digital, like they know a guy, a lot of data. Right. And it's there. But they don't know exactly how to access it, how to make it unified. So the did is not really ready. So maybe explain what that means and how you guys, how you guys address that issue. Yeah. I think, you know, I can give two perspectives on this. One as an operator and one as kind of like what we're trying to do as a solution provider. I think first, like the organization and the sea level need to understand the value in the data first and foremost. Like there's so much value to be had in it. Once you understand that, the first thing you need to get after that is quality over quantity and it goes back to your point of quality also means, you know, being able to access in user and is it clean? That's something that we do. Obviously, we take care of that with our clients is making sure that you have one source of truth. But there's still many operators out there that have, you know, fragmented systems. They don't control their data. They don't even know where their data lives. They don't know how to use it to access it. And I think a lot of that comes down from not understanding the value and the power behind it. Because once you see that real life, you're like, okay, I have to unleash this data and learn how I can do it. it. So I think it first, understand the value and then kind of really think about how you can control it, own it, use it. I'm packed out a little bit when you see understand the value, like what's the value that you think we're missing? You know, most people are just looking at retention, right? That's like the big thing, like 90% of the focus. Like what are the opportunities that we're missing? There's there's there's there's many. There's there's a lot and there's a lot that still hasn't been found. And I think you you just kind of alluded to one of the things, you know, the first thing that people look at is more of the negative side of, you know, the service industry is like, okay, predicting people leaving or dealing with, you know, potentially complaints and stuff like that. There's a lot that can be done on the other side of, you know, rewarding members, staying in touch with your members, engaging with them. It's harder to do and it's harder to track because it's very difficult to quantify lifetime value from interventions. There's a massive amount you can do on sales. There's a massive amount you can do on cost optimization. And there's a massive amount you can do on optimizing your team's capability. And when you look at these from a commercial aspect, not only are making your business far more profitable, you're making it more scalable and your members are staying for a longer time. So you're you're kind of future-proofing your business. It's just like if you if you can't see this right with with data, then there's a fundamental problem because if somebody opens up next door to you and they have all of this in place, you're probably going to be in trouble quite quickly. That's that's that's my kind of harsh draconian connection, but I truly believe it. Yeah. Yeah, well, I've noticed like last year, when AI came to the conversation, a lot of it was to your point retention. Like how do we predict when someone's going to turn, how do we intervene, you know, through a text message or a phone call or a meeting or something like that? The conversation is this year so far, I've been very different. It's about member experience. It's about like how do you get way ahead of this, right? And and really make this, you know, a valuable component of our members lives so that this turn, this point of turn doesn't happen or it gets pushed way down the road or it happens for good reasons like someone's moving, right? Or you know, there's a life event or whatever it may be. And that's been that's been a very strong note saying that language has changed very clearly over the last six to eight months, I would say a question on you for like most operators have fragmented text acts, right? It's kind of been this this Frankenstein thing that's been pulled together. It's like over the years and like cool, I want that future and they plug it in, plug it in. Like what's the danger there? Is that is that a huge problem for people who are listening like oh shit, that's me. Is it solvable? Like yeah, give us a second. What is what happens with fragmented text acts that a lot of operators have at this point? Yeah, it's definitely solvable. It just takes a little bit of time and focus to be able to fix it. I mean, and it depends how fragmented it is. So generally, if you use, you know, a solution like one of us, like Magic Runaq, perfect gym, most of it can be centralized within that solution. But then if you know, you start adding in, you know, your own custom app and you know, you've got different analytics platforms outside and you know, depending on if you're taking that data route or if you've got other sources of data and then you've got your lead pipeline elsewhere as well, it can be quite sticky and the longer you leave it, the harder it is to kind of centralize all of that and use it. So I feel there now, consider doing a migration plan and planning that out to be able to use it or get a solution that does that for you. I'd say that's probably my best advice. Yeah, it's good advice. I'm always curious about this question too. It's like when you look at the US market, as you guys, you know, enter full steam ahead, what are the differences? Like how are we doing? Like US operators versus European operators? Are you a, like, are we behind? Are we ahead? Are we comparable? Give us, give us your grade. Yeah. Yeah. Yeah. Now that's a really good question. It's something I've actually thought about. So I've interviewed a lot of people when I was doing my master's dissertation. So I was interviewing a lot of people around the world and the differences I noticed. So I would say the Middle East, by far, is the most open when it comes to pushing the frontiers of technology. The US is the most willing to adopt technology and I think they are, you guys are doing quite well in exploring that. I think the Europeans in general are a little bit kind of, you know, hesitant to kind of dive in. There's I think a little bit more of a higher risk, you know, adverse kind of attitude in general. But everyone seems to be moving that direction. I've had conversations across Europe, US, Middle East, Africa, everyone starting to have these conversations. I think some of the conversations now are, okay, do I build or do I buy? And how should I go about this? Which is something we can touch on as well. Yeah. Yeah. What was your, yeah, refresh my memory? What was the master's dissertation? What did you, what were you interviewing people about? I was interviewing people about how to unlock ROI and AI. What are the barriers, success patterns, what are people doing differently? So yeah, I've spent a lot of time digging into the literature and I just published my, well, I just submitted my dissertation a couple of weeks ago. So yeah, I'm heavy into the topic. Oh wow. Yeah, you're really into it. Yeah. Yeah. Yeah. I'm in the area coming. That's what you do with your free time. Yeah, I got it. All right. So you're at FIBO not too long ago. As we record this, you guys had a pretty big unveil. You know, I think in the US, we would call it perfect AI. We gave us insight like, what was that presentation about? What were you unleashing on the industry there? Yeah. Yeah. There's a couple of things. I'm going to tie it back into one of the points you just mentioned earlier about retention. So we are moving into a domain of adding a system of intelligence to our operators. So, you know, we've got this platform, which is, you know, their CRM and ERP and it enables our clients massively to run their business. But we want to make that step now into supporting them in their actual day-to-day operations and our value. One thing I will caveat, our strategy in AI, which I'm going to unpack, is very much revolved around enabling our operators to have more members stay for longer and have better experiences. That's really what we're trying to do. But what we're not trying to do specifically and always like to start with what we're not trying to do is we're not trying to step into this social human experience of fitness. So once you're in the gym, enjoy it with people around you, train, do your class and have fun. Everything around that, we're starting to try and find ways to support. So there's two products we've got that we're launching very soon. The first one we're launching is Perfect AI Chat. Now this is our chat agent that we've been working on for some time and we're releasing it this month. And then we've got So Perfect AI Chat and obviously we've got Magic AI Chat for the two different platforms. This is our chat agent and we're starting with a couple of channels and we're starting with a low-hanging fruit. So being able to do things like sort of like member services, freezing contracts, stitching and booking free trials and sales and kind of supporting the member service domain. Our future and the more we develop, the more agents and the more parts of the member journey we're going to start to integrate into. Now this is our first platform and this is the first stage of being what we call a reactive AI agent system. So it's sitting there waiting for when a member comes and interacts with your business. It's going to add a lot of value and we're doing things a little bit different and we've taken our time building this a little bit different. I can unpack this in a couple of ways. We have built everything into our solution natively and why is that important? A lot of platforms out there are our third-party platforms and there are things that have to connect to your systems somehow, generally APIs. They live outside. You don't control the data. You don't own the data. It's with someone else, different platform. These things sometimes work well to begin with but they tend to break down over time because the thing about AI is not non-deterministic and it has to understand your business process and understand your data. So what we've done, long story short, is we've built everything into our architecture natively. So when our customers scale, the AI scales with them. So that's perfect AI chat and the next frontier is something we're really excited about is perfect AI and magic AI engage and this is where we're going from a reactive AI to a proactive AI and this is something I'm really excited about. So one thing that's absolutely key in the service industry and we're going back to your point now about retention, everything is time sensitive. If you can influence behavior in a member journey, it's all about time. It's about time of how quickly and at the right time with the right context can you engage with a customer. Very difficult when you have a limited amount of people and staff to do that and a limited amount of data and a limited amount of knowledge going back to that value of data again. Engage is a customer data platform that we can automate communication with the right context, with the right time for the right person. So think of it as a communication tool that has been designed around key parts of member journeys. So all the way from a prospect to a new joiner to when your a visit frequency might drift off, you know, you've been coming two times a week for the last six weeks and all of a sudden you've dropped one or it could be coming to a contract through new all and so on. So we understand when and then we can activate and what's really exciting is when you use a two together. So if you know when and where to contact someone, you know Eric has started to drift off of his membership. You know that Eric loves, you know, mixing martial arts and CrossFit, we can fire off the communication to Eric at the right time, but if we add in chat at the back end of that, then our agent can also pick up that conversation and have dialogue. Now, it might just be a case of saying, "Hey, Eric, we miss you as everything right." You say, "Yeah, look, works is caught up in me coming back." But it could be a case of, "No, actually, everything's not okay. Someone at reception was rude to me." And then the agent would be able to know to identify, then, escalate to one of the staff members. So this is kind of where we're going with our AI solutions. So very exciting stuff and coming soon. Yeah. You know, maybe I would like to get some clarification on some terms because I was so an asked me this question, I was fumbled through an answer, and I don't think I got it right. So I'm like, they're like, "What's a gentick AI? Like, what does that mean exactly?" And, you know, compared to, I guess, an LLM or you know what we traditionally know as a cloud or a chat up to your rock or something like that. So, yeah, help us with that. What does, what does the "gentick" mean? Yeah, sure. A gentick basically just means that the AI can do things right? And technically, they're just API calls. So you probably have like, you know, MCP model context protocol and all this stuff and like, "Claw desktop and, you know, being able to even just check the weather in real time when you talk to chat GPT." What's basically happening is the AI in the background is calling an API and taking an action. So it understands, right, I need to do something right now and I need to hit this API and take action. And basically, that is what "Agentick AI" is. So you can have an agent that has a specific task and a specific set of tools. So, for example, in our context, you could have a sales agent that would have a tool to be able to book free trials into your software. So it'll detect that Eric is interested in coming to try the gym. He's given me a date and time. The AI then has a tool set to book it and go and create it. And that's really what "Agentick AI" is. Right. Versus like an LLM is basically just one big answer machine, right? Just answer questions and give you some feed you information. Yeah, because I listened to a Lex Freedom podcast recently about OpenClaw and that was a very fascinating event in history. I don't know if a lot of people follow, but it was, it's pretty wild and how much like people are basically saying like, "No, it's not really. These are people doing it behind the scenes." Right? And do you follow that? I thought it was really. Yeah, of course you did. That's agents unleashed, right? So, funny enough, some of that philosophy is what's spired engage, right? Because OpenClaw, for people that don't know it was, you know, basically unleashing an agent that kind of just continually goes on a loop. It never turns off and it can just go and do its own thing. And it says like, "Okay, hang on. That's the dawn of like proactive AI." And there was massive value in that. Okay. There was lots of security risks as well for people that aren't aware of it. But yeah, that it did inspire us and it was really interesting to see. Yeah. Yeah. When you go back to this combination of engage and chat, maybe give me like a tangible example that an operator could really feel and understand, right? So, you know, a pain that they experience often. I can give you a few. And I was lucky enough in gymnation to be able to test this stuff, which is, you know, not that easy to do. Okay. I give you one example. So, when you join a lot of the research has found that the first end number of days could be seven days, three days is the most critical time to determine if you're going to stay for longer or not. So, outreaching to a member in that time, checking that, you know, did the onboarding go correctly? Did everything go smooth? It's really important. One thing is also there was a really exciting test we did and we published the results. We took, in this was in gymnation a couple of years ago when I was a CTO there. We took around 6,000 members and this was the first agent to AI that was unleashed in the fitness sector. It was called Albus. An Albus was a WhatsApp and voice agent and we decided we designed Albus and Jenny. We don't ask what their names come from. To engage with members that were dormant. And so we set a, I think it is like a specific number of days like 15 days. I can't remember exactly of dormant members. Exact same cohorts. We split them 3000 3000. We took the 3000 in the control group and we got the AI to engage with them. Checked in with them, called them, WhatsApp them, tried to get them back to the gym, escalated if they had any issues. The others, we did nothing with them. The guys who we did that stuff with, we managed to prove that their lifetime value increased by about 0.8 months. It might not sound a lot, but when you extrapolate that, that's massive. We could see that they actually were coming back to the gym twice as much as the people who didn't get any messages. So we like, this really works. It took six months to do that study. It was no joke. But this is just one of many examples and just member experience. The sales is another element. We had, and this is something that we're actually doing in our magic AI and perfect AI chat and engage. Also the use case that inspired just before this. Sales. Right. Sales is another time sensitive thing. If you go on to an Instagram ad, you see, "Oh, this is a pretty cool gym. I'm looking for a gym." You put your information in. You press submit. If that goes through traditional gym, maybe best case four hours in the next day, you'll probably get contacted. The sales agent might be good. Might not be good. He might be having a bad day. He might be trying to close his commission at the end of the month. You don't really know the quality of what happens and might go cold. They might not get contacted. If you have an agent reaching out in seconds to book in a free trial or price present, we found that not only did the answer rates go up, the conversion rates went up. It was like a win all round. And these are very tangible things. There's loads. There's loads you can be doing. There's real value to be had. Going back to the first example you had, so in additional point eight months, I get that. If you extrapolate that over thousands of members, that's a tremendous jump in revenue. What's the psychology behind it, though? How through this outreach, what are we doing? Are we just reminding people, like, "Hey, we're still here. Are we giving them more incentives?" Are we trying to link them up with other people in the community? How do we see what we're here to do is change human behavior? That's a complicated thing. How does AI start to walk that line of like, "Hey, we're really getting into the psychology of the member. Everyone is unique." Sure, it's got a long way to go because that's a complicated thing. Walk us through that component of it, the human part. Yeah. The first thing I'll tell you is a massive learning I had. The holy grail I thought was to increase visit frequency. I'm going to find some way to increase visit frequency on a group of members because it looks like visit frequency is the highest correlating factor towards lifetime value. It's way out there. What I found is that I haven't found out how to do that. It was almost impossible. I tried a million things, but what I did find is that you can maintain visit frequency. It's obviously when you think about it, people have schedules that they're working around and that's genuinely how it is. What it boils down to from what I've seen is just staying in touch with the members and keeping relevant with them in a lot of cases and identifying, going back to the thing, time is everything. If you can influence behavior, you have to act quick. It doesn't matter how bad it is. If they had really shitty time. If you act quick, you can fix it. If you leave it, it's a lost cause. I think the other thing is we don't in this industry reward people individually enough when they're doing well or staying consistent. It's something that completely slips you to the crack. It's always kind of the negatives and negatives. When you do that, you stay relevant in the mind and it really helps people stay consistent. It just comes down to human psychology, getting a pat on the back at the end of the day really works. That's what it comes down to. Yeah. That's such a key point, man. We used to, you and I talked, we have CrossFit background. I was a CrossFit operator for a long time. One of the things we would do, and anybody who's an operator, I challenge you to do this because it was magical. We would sit down as a coaching staff on Fridays. Maybe this Thursdays doesn't matter. But we would go through our entire roster of clients. At our GM, you know, on average, had 150 to 200. We would write out of boys or out of girls. We would take a little postcard and we would just be like, hey, great, Susie, great job this month, or hey, congratulations on your first 5K, whatever it would be. We would send these. They would go out. I would go to a barbecue or something like that. It's someone's house. I would go into their kitchen and I would see on their fridge, three of these, four of these that they kept. It became like a seedling. People got really fired up. It was just, it was a simple thing. It took two minutes and a stamp to get that mailed out. I think that's something in our industry. I forget about that. I'm like, oh, that was so valuable. We just kept doing it and doing it. Sometimes on Fridays, you're like, I don't know, I do this. But even if it was nothing, for just like, hey, it's been great to see you being more consistent lately. People loved it. It went a long way as far as retention. That human component is very real. If we can do that at scale and still keep that, that's the challenge. How do we keep that human component by doing it with AI to assist it? I'm sure that's a challenge that you think about constantly. It's the human part. Yeah, definitely. I think a big part of it is also being personalized. You don't want to receive a mass communication. It just doesn't resonate. Eric, well done this week, coming three times again, congratulations. That really resonates. It's not on that personal level. I think there's two aspects. Again, we We want to enable the social element of the gym. So we're even, and I've done this work before, like I published this, it was kind of like a hobby project. It was, I wanted to build a Tinder algorithm for gyms, but not for the obvious reasons of like trying to hook people up. I managed to find a way to match people's habits and behaviors, and it kind of clicked as a hang on. If I can find a group of people that go to the gym at the same time at the same time, you know, weekday, the same interests, couldn't we create a campaign around these for a event where we could group people to have social interactions, you know, so they're making more friends and like amplifying that. And another thing that we did at Gymnation is we did, we copied the Spotify wrapped. You Spotify at the end of the year, you get that really cool kind of wrapped, you know, in the top 1%. So we did that with the members and, you know, we said, you're in the top, you know, 2% globally of, you know, attendees, you've been consistent 90% of the last six months. And like we just did it as an experiment. And what we found is it just completely went socially viral. They were, you know, without any, you know, push everyone was sharing it on their channels and kind of building that social element, just using some data, right? So yeah, I fully agree. It has to be a mix of both. Yeah. And that's going to be how it's, that's going to be the winners. Like when you figure that out, right? Consistently over time. And you know, I think the other thing is like if it's tough, like if you're a personal trainer or a coach, like to motivate one of those employees to take extra time to do these things, like to do the outreach, it's a big aspect. So if you can make it simple, like even just if it's a simple list at the end of the week, you're like, hey, here's three people you should contact them. Why? Like that's a very powerful thing too. You know, it's kind of the best of both worlds because, you know, like I said, the post, the adaboy example, like we just sit there and literally think about it. But if it was prepared every Friday for us, right? We knew exactly what it was going to be. We didn't have to think about it too much. It was to be done. And we could probably do more of them. We could probably do 10 versus three each, right? So yeah, that's an interesting thing. Just going to see on the full. Go ahead. Just just on that, right? I mean, it's one of the things that engage or allow people to do. You'll be able to see, you know, the members that will need that care. It doesn't mean you have to use the automation and, you know, AI to do that. You could just give that list to your PTs by identifying who those trainers, who those people have been trained by and still having that human touch. But you get the AI and the kind of data to do the guesswork for you to have that personalization. I think that's really kind of where the power is. I want to get started back on a point that you made that I talk about a lot right now for different factors too, is, you know, build versus buy. You know, how a lot of operators and it's not just, you know, an AI, it's also, I think, in the world of GLP ones and peptides, like, you know, and putting these medical clinics inside the gym. You're smiling. I'm guessing you have a take on some of that stuff too. Yeah. Now you're going to see what that got, smart. So yeah, build versus buy. Like, what is the advice that you have for operators? Yeah. There's no right and wrong, firstly, and I've done both. And as a CTO, we built everything from scratch. And I did consultancy work and now as head of AI for sport alliance, we are offering this as a vendor. And I've seen the pros and cons of both worlds. So let me cover both. When should you consider building? If you are the top, you know, 5% of tech savvy, you know, fitness commercial operators and you have a very creative way and a million ideas to create competitive advantage using technology, yes, do it. As long as you understand, you will create a lot of value, however, there will be a lot of overhead. And generally, the chances of you driving that value are a bit lower because you have to learn everything yourself, right? When you're going to a vendor, they've already done all that hard work for you. And now with the dawn of AI, it is cheaper, it is quicker, but people forget you have to maintain this stuff, you have to grow this stuff and it's not a joke. So you have to be serious about it. So that's one option for you. Buying is the other option. I generally advise this, even though I know I work for a company that offers a vendor, but generally, if you're not that top 5%, you should be looking at buying. There's a few things you should consider when you look to buy. Now, when you buy, the ideal situation is you find someone you trust who has done the legwork, who's reputable. And again, you probably want to look for people that can really integrate or like we're doing, we'll talk about this in a bit. I'm sure it's native into the solution having that data controlled in one place. Generally, if you find a partner you can trust the overheads are lower, the learning has already been done. They will take care of the technology side of things and then you have to take care of the rest, which is actually the hardest part, which is the people in process. And maybe we can unpack that a little bit. That's by far the hardest thing to do. So it gives you the time to find someone to trust and do all the technology for you and you focus on the people in process. And even in the literature, I think the numbers were something like 33% success rate on building your own in terms of getting a positive ROI to 67% positive ROI chance when you actually go for a vendor that you can find and trust. So the chances are higher, the overheads are lower. You forgive a little bit of the creative freedom, but if you just want to drive value to your business and don't want to be a tech company, find someone to work with and buy. Yes, so let's get into that part. Locating the tech partner and licensing it and buying it is probably the simple part. But getting the staff to adopt it and actually use it and incorporate it into the facility's specific needs and membership details. It's the implementation. That's still very human components. So what advice or what guidelines would you give people and like, okay, if you're going to do it, be prepared to do it right. This is what it takes to do it right. Yeah. This was the biggest learning in my career is the people part. This is always the hardest part for me. So look, first let me cover the rest. There's this rule that came up in a literature and I've kind of used this because it's an easier rule than it makes sense. Is this rule of 70, 20 and 10? So the 10% is kind of real technical algorithms. The model is a frameworks. And 20% is a data foundation, you know, going back to what we were saying, controlling the data, making sure it's accessible, connectable. So that 30% of technology is the first part, again, work with a vendor in most cases. And you also need to just one more thing on the data before we cover the people. You also need to think about a future proof in the business. And this is kind of what we really focus on at sport alliances, building everything native, as I kind of mentioned, right? So it doesn't break down over time. Now the 70% on people in process, by far the hardest thing. And that element comes into two factors. One is cultural readiness, which is a whole problem to unpack in its own right. And the second one is senior leadership, an executive leadership sponsorship and buy in an involvement. This is a change technology and you shouldn't underestimate it. It's a fundamental change. And it's going into the skill and knowledge work of humans, which has never really been done before. So naturally what comes with that is fear, resistance, uncertainty, doubt. And that changes at different levels of the organization. You know, a general manager of the club will feel like he's losing control over his responsibility. Marketing executives will feel like they're losing creative ability. And there's a whole different, there's a plethora of things you need to navigate. So first thing, and I'm giving them jumping straight to the advice here because I've learned the hard and painful way. First you have to have a senior leadership team that's serious. And it can't be performative, but it has to be that the CEO is driving this first and foremost. It's cascading into KPIs, bonus structures, you name it, going through the transformation adoption and continuing from there. The rest of it on the cultural side of things, you have to really be careful of framing and how you do this. So there's lots of training involved. You have to make sure that you don't frame this as replacing people because it's a not, it's enabling people. It's more augmentation, not replacement. And you have to do this step by step and you have to think about every level of organization. That is where all the work is. Now if you crack that, if you crack that and you crack the technology part too, you are going to drive a serious amount of value in your business and it's going to open many doors. It's just not that easy to do right now. Yeah. Gosh, man, I've never had all the interviews I've done here about AI. I've never had someone lay it out. Maybe I've never asked the question, but how do you actually, we always look at like, okay, well, which feature is the best, which one, what's the best option? What can it do for us? None of that matters unless you get it properly adopted into the operations of the business, right? And you get the buy-in from the staff. Like that's everything. And that's not, like you said, people like all of my dwellings in business, the most challenging thing that ever always comes up is people all the time. I could have the best business plan, framework, programming, you name it, but getting the people right consistently is, and rightfully so. I mean, you know, we're humans, right? Like we have our own emotions. We have emotions. Yeah, emotions and, and to when goals change and so to get it, like I think that's like when you look at great leadership across any industry in the history of time, they've had this ability to get people really to fall in line with a vision, right, and be properly motivated too. to get there and do it with a certain amount of excitement behind it too. So yeah, I'm going to room it on that for a while. I was really good. Thank you for that. You're welcome. There's more, there's more, right? I mean, even if you crack it at the beginning, it has to be something that you perpetually look at. There's one interesting thing, there's two interesting things that came up in my research. One of them was familiarity bias, which is interesting. And I saw a few cases where they managed to do all these things. You know, senior leadership was involved. The team were, you know, accepting and willing to take this on. And they got their systems rolled out. And then what happened is naturally because they didn't have a follow up mechanism, people started to go back even though they had superior technology and processes because they were familiar and comfortable with Excel sheets and stuff like that. They would naturally revert back over time. So something you have to, you know, maintain is and it's not easy. Yeah. I mean, let's zoom back out. That was great. Thank you for that. Like if you look into the future here, sort of in 2026, let's say 2030, it's a nice round number. You know, and so much is going to change. I think in 2030, a lot of what we know now about the world is going to be look going to look very different. But what about gym operations? Like, what, where do you think we can go? Is there like a possibility for basically gyms? We kind of be on autopilot other than the staff? Like, is that a possibility? Or where do you think? What's your grand vision for where this can go at that time for it? Yeah. I mean, it's a good question. I'll give you my take. Well, caveat, you know, nobody knows, right? I think that I'm not one of these people that believe that, you know, AI is going to replace everyone's jobs and especially in the service sector. People like to be around people, you know, the whole COVID experience, the Peloton experience proved that. I think that was kind of the end of that chapter. But there's a lot that will be done in terms of around that, as I kind of mentioned, around the social experience of the gym. So I probably stopped optimization, being able to scale quicker, being able to optimize class schedules, being able to find more members quickly, being able to engage with them and keep them longer. So what I think what will happen is the people who adopt more and take the technology serious more, we just have far more bulletproofed businesses. And the only people in those cases that would be leaving are because they're leaving the country or moving away. You would know so quickly if something's having a bad experience and you'd be congratulating the people that are having a good experience and you would just have a closer pulse on the business. That's where I think everything's going. Again, everything around the social experience, I'm not one of these believers that, you know, we're going to have these, you know, VR headsets and people are going to be training into, you know, augmented reality and that nobody wants that stuff. I want to work around people. That's why I go to a gym. That's where I see it going. It's one thing I'll add, you know, I always kind of take the commercial aspect, because that's my expertise. The value, and I started with this slide in in FIBO kind of like explaining where I think we are in in terms of, you know, this AI, hypercycling, so all of my research and all of my personal experience has shown that the time to actually extract value from AI and it could be machine learning, it could be the sexy, agentic stuff, but you know, seriously looking at this technology takes, you know, one to two years to realize, right? So if you're starting now, you can do the math, you know, 28 is when you're going to start to really, you know, maximize the value that you're getting from this. So there's people that have already started two years ago, you know, gym nation is a prime example. They are extracting serious value out of this technology. So I think it's, I don't want to say it's by 2030, it's going to be life or death. I don't want to be that draconian, but it's going to be a serious gap for you if you are an operator and you're not looking at technology by then. Wow. I'm letting that sink in for a second. So we're both going to be at Apple Tech, the Apple Tech Innovation Summit coming up in, you know, as a recording just a few weeks away. So I'll give us some insights, man, like what are your expectations and hopes for that? Like what kind of conversations would you like to have? And now we're going to be on stage together, the details of that are still a little refiguring it all out, but you know, maybe some ideas of yeah, like what's your goal going into it? Who'd you like to talk to while you're there? And maybe give us some insights if you know, like what we're going to be talking about. Yeah, I mean, yeah, it's a good question. I'm really excited about talking more about what we're doing with Perfect Jim and Magic Line as sport lines. I truly believe that we are building the future platforms for our clients to really extract value from their operations. I want to show people, I want to talk to people about what we're doing, especially in Perfect AI and Magic AI chat and engage. I'd love to also talk a little bit more about, you know, the stuff we've talked about today. And I'm really keen to get a closer pulse on the US market. I think the US market's always excited me because it's always the one that's willing to, you know, try things out and adopt and, you know, look at technology and look at doing things differently and looking at what's next. So I'm really excited about that and I'm looking forward to being there. Right on. Carl, if people want to reach out to you or get a whole of you or maybe schedule some time with you while they're at the event, what's how would you like them to do that? Yeah, probably the best is LinkedIn. Yeah, just reach out to me and LinkedIn and connect that. Right on. Last question for you. What do you need help with? And I always ask this in the spirit of like, if people are listening, are you looking for help with anything specifically? Is it staff? Is it, you know, collaborations? Is it, yeah, whatever it may be, what would you like to hear from people about? Yeah, I always encourage people, if you're doing cool stuff, share it. Let's talk about what we're doing. Let's collaborate. I've always been an open book, quite an open book at Sport Alliance as well. So yeah, come, come, you know, debate, come challenge, come show us your cool stuff. Let's talk about what we can do as an industry together. I think that's, that's what excites me the most. Yeah, right on. Well, Carl, sincerely thank you for doing this. There was a lot of value here. A lot of things that got me thinking and I talk about this all the time. There were some really new perspectives that I gained from this. So really appreciate you doing. I'm excited to see you in person in New York and share some stage time with you. So thank you. Ladies and gentlemen, Carl Foster. Thanks again. Cheers. Hey, wait, don't leave yet. This was your host, Eric Malzone. And I hope you enjoyed this episode of Future of Minus. If you did, I'm going to ask you to do three simple things. It takes under five minutes and it goes such a long way. We really appreciate it. Number one, please subscribe to our show wherever you listen to it. iTunes, Spotify, CastBox, whatever it may be. Number two, please leave us a favorable review. Number three, share. Put it on social media, talk about it to your friends, send it in a text message, whatever it may be. Please share this episode because we put a lot of work into it and want to make sure that as many people are getting value out of it as possible. Lastly, if you'd like to learn more, get in touch with me. Simply go to the futureoffinus.co. You can subscribe to our newsletter there or you can simply get in touch with me as I love to hear from our listeners. So thank you so much. This is Eric Malzone and this is the Future of Minus. Have a great day.