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

[00:00:02] Hey friends, welcome to the Future of Fitness, a top-rated fitness and wellness industry podcast for over five years and 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'd love it if you took three minutes of your day to leave us a nice, supportive review wherever you consume your podcasts. If you're interested in staying up to date with the Future of Fitness, go to

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[00:00:47] Hey friends, I've had hundreds if not thousands of conversations with gym owners and industry entrepreneurs. One 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 U.S. market.

[00:01:15] Now I've seen this movie before, but here's the difference. They've opened up a U.S. 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.

[00:01:36] 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 feed is.

[00:02:01] 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, if you want to use your own app, your preferred payment processor, ClassPass 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.

[00:02:30] They've invested a ton into this platform. Now, they're bringing that European engineering excellence to America. The migration experts have arrived. Check out perfectgym.com where enterprise-level sophistication meets operator freedom. All right, here we go. Karl Foster, welcome to the future of fitness, man. How are you? Good, thank you. Pleasure to be here.

[00:02:55] Yeah, a pleasure. And you got the black t-shirt memo. So, check. We're both looking sharp. I think that's 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 Sport 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 that I think a lot of operators are dealing with at this point.

[00:03:22] So, you know, 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 a member's experience and AI that's just basically a chatbot 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?

[00:03:50] So, I think it all starts with, you know, how you're approaching it as an organization. Are you serious about this? Is a 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 in my experience. Should be on the member's 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.

[00:04:21] I think that's the best starting point. Yeah. Yeah, great. Great. And we're going to dive into all this stuff. And maybe 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 an awesome role. 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 I started out as a PT when I was 18. Been in the gym space a long time. I'm just a natural nerd. My brother's a software engineer.

[00:04:50] 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 I kind of went into, you know, commercial space, operations, sales. And then managed to get more involved in kind of the data side of things. Became a 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.

[00:05:19] And yeah, and then I had the opportunity to join Sport Alliance to kind of push AI in a much bigger scale. And I absolutely love it. Yeah. 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.

[00:05:48] 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 quite a lot. We have MagicLine, 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 software.

[00:06:15] And we also have Finian Capital, which is a fintech vertical and payment vertical. And we have the app to go with it, my sports app. So those are our companies. I guess they're 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 serious, like all business.

[00:06:43] 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? Like 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.

[00:07:07] And every time I feel like I get a grasp on it, I'm like, okay, I think it's starting to, like, it's really starting to optimize here in my workflow. And then it just makes a jump forward, right? And you're like, God, I got to 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 this is just because it's a passion industry, right?

[00:07:34] A lot of people opening 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. It'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,

[00:08:01] 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 deal and Erwin on this podcast, I think it was about six months ago.

[00:08:27] 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 are in the industry, even like in the online coaching space or anything digital. Like they know 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 data is not really ready.

[00:08:57] So maybe explain what that means and 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 C-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.

[00:09:26] And it goes back to your point of quality also means, you know, being able to access and use it 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.

[00:09:52] Because once you see that real life, you're like, okay, I have to unleash this data and learn how I can do it. So I think at first, understand the value and then kind of really think about how you can control it, own it, use it. Unpack that a little bit. When you say 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 many. There's a lot.

[00:10:22] And there's a lot that still hasn't been found. And I think 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. It's like, okay, predicting people leaving or dealing with, you know, potentially complaints and stuff like that. But 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.

[00:10:52] There's a massive amount you can do on sales. There's a massive amount you can do on cost optimization. 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 you making your business far more profitable, you're making it more scalable and your members are staying for a longer time. So you're kind of future-proofing your business. It's just like if you can't see this, right, with data, then there's a fundamental problem.

[00:11:18] 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 my kind of harsh, draconian, but I truly believe it. Yeah. Yeah. Well, I've noticed like last year when AI came in the conversation, a lot of it was, to your point, retention. Like how do we predict when someone's going to churn? How do we intervene, you know, through a text message or a phone call or a meeting or something like that? The conversations this year so far have been very different.

[00:11:47] It's about member experience. It's about like how do you get way ahead of this, right, and really make this, you know, a valuable component of our members' lives so that this churn, this point of churn doesn't happen or it gets pushed way down the road. 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 a very strong noticing. That language has changed very clearly over the last six to eight months, I would say.

[00:12:13] A question on you for like most operators have fragmented tech stacks, right? It's kind of been this Frankenstein thing that's been pulled together. It's like over the years, they're like, cool, I want that feature. And they plug it in, plug it in. Like, what's the danger there? 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 happens with fragmented tech stacks that a lot of operators have at this point? Yeah, it's definitely solvable.

[00:12:41] 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 a solution like one of ours, like Magic Line or Perfect Gym, most of it can be centralized within that solution.

[00:12:57] But then if you start adding in your own custom app and you've got different analytics platforms outside and depending on if you're taking that data route or if you've got other sources of data and 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 that and use it. So, if you're 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.

[00:13:26] I'd say that's probably my best advice. Yeah, that's good advice. I'm always curious about this question too. It's like when you look at the U.S. market as you guys, you know, enter full steam ahead, what are the differences? Like, how are we doing like U.S. operators versus European operators or UAE? Like, are we behind? Are we ahead? Are we comparable? Give us your grade. Yeah, yeah, yeah. No, that's a really good question. It's something I've actually thought about.

[00:13:54] 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 U.S. is the most willing to adopt technology. And I think they are, you guys are doing quite well in exploring that.

[00:14:19] 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 in that direction. I've had conversations across Europe, U.S., Middle East, Africa. Everyone's starting to have these conversations. I think some of the conversations now are, okay, do I build or do I buy?

[00:14:48] 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 just published my, well, I just submitted my dissertation a couple of weeks ago.

[00:15:17] So, yeah, I'm heavy into the topic. Oh, wow. Yeah, you're really into it. Yeah. Yeah. Okay. Yeah, I'm a nerd, Eric. I'm a nerd. That's what you do with your free time. Yeah, I got it. All right. So you were 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. Give us insight. Like what was that presentation about? What were you unleashing on the industry there? Yeah. Yeah. There's a couple of things.

[00:15:46] 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.

[00:16:11] 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 I always like to start with what we're not trying to do, is we're not trying to step into the 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.

[00:16:41] 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 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.

[00:17:06] So being able to do things 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.

[00:17:32] 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. 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 third-party platforms and they are things that have to connect to your system somehow, generally APIs.

[00:18:01] 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, it's not non-deterministic and it has to understand your business process, 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.

[00:18:30] 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 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.

[00:18:56] 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. So engage is a customer data platform that we can automate communication with the right context, with the right time for the right person.

[00:19:23] 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 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 to one. Or it could be coming to a contract renewal and so on. So we understand when and then we can activate. And what's really exciting is when you use the two together.

[00:19:51] So if you know when and where to contact someone, you know, Eric has started to drift off of his membership. We know that Eric loves, you know, mixed 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. Is everything right? You say, yeah, look, works is caught up with me. I'm coming back. But it could be a case of, no, actually, everything's not okay.

[00:20:20] Someone at reception was rude to me. And then the agent will be able to know to identify that and 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 someone asked me this question. I was fumbled through an answer. I don't think I got it right. So I'm like, they're like, what's agentic AI? Like, what does that mean exactly?

[00:20:46] And, you know, compared to, I guess, an LLM or, you know, what we traditionally know as a Claude or Chachupiti or Brock or something like that. So, yeah, maybe help us with that. What is what is agentic mean? Yeah, sure. Agentic basically just means that the AI can do things, right? And technically, they're just API calls.

[00:21:05] So you've probably heard of like, you know, MCP, Model Context Protocol and all this stuff and like Claude Desktop and, you know, being able to even just check the weather in real time when you talk to ChatGPT. So 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 agentic AI is.

[00:21:31] 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 will 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 agentic AI is. Right. Versus like an LLM is basically just one big answer machine, right? Just answers questions and give you some, feed you information.

[00:22:01] Yeah, because I listened to a Lex Friedman podcast recently about OpenClaw. And that was a very fascinating event in history that 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 real. These are people doing it behind the scenes. Right. Did you follow that? I thought it was really. I do. Yeah. Of course you did. Yeah. Of course you did. That, that, that's, that's agents unleashed. Right. But so, so funny enough, some of that philosophy is what inspired engage. Right.

[00:22:29] Because OpenClaw, for people that don't know it was, you know, basically unleashing an agent that kind of just continually goes in a loop. It never, it never, it never turns off and it can just go and do its own thing. So it's 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, that it did inspire us. And it was, it was really interesting to see. Yeah. Yeah.

[00:22:56] When you go back to like to this combination of, of engage and chat, maybe give me like a tangible example that an operator could really feel and understand. Right. Yeah. That they, you know, a pain that they, they experience often. I can give you, I can give you a few. And I was lucky enough in gymnasium to be able to test this stuff, which is, you know, not, not that easy to do. Okay. I'll give you one example.

[00:23:16] So when you join, a lot of the research has, has found that the first N 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 the, did everything go smooth is really important. One thing is also, there was a really exciting test we did. We published the results.

[00:23:43] We, we took, this was in gym nation a couple of years ago when I was CTO there. We took around 6,000 members and this was the first agentic AI that was unleashed in, in the fitness sector. It was called Albus. And Albus was a WhatsApp and voice agent. And we decided, we designed Albus and Jenny, we don't ask where their names come from, to engage with members that were dormant. And so we set a, I think it was like a specific number of days, like 15 days.

[00:24:11] 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, which might not sound a lot, but when you extrapolate that, that's massive.

[00:24:40] And 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're like, this really works, right? So, you know, and it took six months to do that study, right? It was no joke, but this is just one of many examples and just member experience, right? The sales is, there's 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?

[00:25:10] Sales is another time sensitive thing. If you go on to, you know, an Instagram ad and you say, oh, this is a pretty cool gym. I'm looking for a gym. You put your information in, you press submit. If that goes to a traditional gym, maybe best case four hours the next day, you'll probably get contacted. You know, the sales agent might be good, might not be good. He might be having a bad day, might be, you know, trying to close his commission at the end of the month. You don't really know the quality of what happens. It might get cold. They might not get contacted.

[00:25:39] 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 just, it was like a win all round, right? And these are very tangible things. So there's loads, right? There's loads you can be doing and there's real value to be had. Going back to the first example you had. So an additional 0.8 months. I get that. Like if you extrapolate that over thousands of members, that's a tremendous jump in revenue, right? Right.

[00:26:10] What's the psychology behind it though? Like how, like through this outreach, like 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? Like what, what's, I mean, obviously what we're here to do is change human behavior. Right. And that's a complicated thing. So how does AI start to walk that line of like, Hey, we're, we're really getting into the psychology of the member. Or who's all, everyone is unique, right? I'm sure it's got a long way to go because that's a complicated thing.

[00:26:39] But like, yeah, walk us through that component of it. The human part. Yeah. Yeah. Well, the first thing I'll tell you is, is a massive learning I had. So the holy grail I thought was to increase visit frequency. I was like, 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, it's way up there. What I found is that's, I haven't found out how to do that. It was almost impossible.

[00:27:08] I tried a million things. But what I did find is that you can maintain visit frequency. And it's kind of obvious when you think about it, you know, people have schedules that they're working around and that's generally how it is. And what it boils down to from what I've seen is just staying in touch with your members and keeping relevant with them in a lot of cases. And identifying, going back to the thing, time, like time is everything. If something goes, if you can influence behavior, you have to act quick. It doesn't matter how bad it is. If they had really, you know, shitty time.

[00:27:39] If you act quick, you can fix it. If you leave it, it's a lost cause. And 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 through the crack. You know, it's always kind of the negatives, negatives. And when you do that, you stay relevant in the mind and it really helps people stay consistent. It just comes down to human psychology, you know, getting a pat on the back at the end of the day really works. So that's what it comes down to.

[00:28:09] Yeah. God, that's such a key point, man. You know, we used to, you know, you and I talked, we have CrossFit backgrounds. So I was a CrossFit operator for a long time. And one of the things we would do, and anybody who's an operator, I challenge you to do this because it was magical, right? We would sit down as a coaching staff on Fridays. Maybe it's Thursdays, it doesn't matter. But we would go through like our entire roster of clients, right? So at our gym, you know, on average had 150 to 200. And we would write attaboys or attagirls.

[00:28:36] So we'd 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. And we would send these and they would go out. And I would go to, guide it to a barbecue or something like that at someone's house. And I would go into their kitchen and I would see on their fridge three of these, four of these, right? That they kept. And it became like a stable. People got really fired up. And it was just, it was a simple thing. It took two minutes and a stamp, right?

[00:29:06] To get that mailed out. And I think that's something in our industry, like I forget about that. I'm like, oh, that was so valuable. And we just kept doing it and doing it. And sometimes on Fridays, you're like, oh, I don't want to 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. And it went a long way as far as retention. So that human component is very real. And if we can do that at scale, right? And still keep that human. That's the challenge, right? How do we keep that human component, but doing it with AI to assist it?

[00:29:33] So I'm sure that's a challenge that you think about constantly is like the human part. Yeah, yeah, definitely. And I think a big part of it is also being personalized, right? So, you know, you don't want to receive a mass communication. It just doesn't resonate. So when it's, you know, Eric, well done this week, you know, coming three times again, man. Like, you know, congratulations. That really resonates on that personal level. I think there's two aspects. Like, again, we want to enable the social element of the gym.

[00:30:03] 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 the 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. I was like, hang on. If I can find a group of people that go to the gym at the same time, at the same, you know, weekday and the same interests,

[00:30:32] couldn't we create a campaign around these for an 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 Gym Nation is we did, we copied the Spotify wrapped. Are you Spotify? At the end of the year, you get that really cool kind of wrapped, you know, you're in the top 1%. And so we did that with the members. And, you know, we said, look, you're in the top, you know,

[00:31:00] 2% globally of, you know, attendees. You've been consistent 90% over 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, you know, kind of building that social element, but 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.

[00:31:29] Like when you figure that out, right? Consistently over time. And, you know, I think the other thing is like, 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 ask. So if you can make it simple, like even just if it's a simple list at the end of the week, be like, Hey, here's three people you should contact and 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 attaboy example,

[00:31:58] like we had to sit there and literally think about it, but if it was prepared every Friday for us, right. And we knew exactly what was going on. We didn't have to think about it too much. We just 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 angle that we're going to see unfold. Go ahead. Just on that, right. I mean, it's one of the things that Engage will 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.

[00:32:25] You could just give that list to your PTs by identifying who those trainers, who those people are being trained by and still having that human touch. But you get the AI and the kind of data to do all the guesswork for you to have that personalization. I think that's really kind of where the power is. I want to circle 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, in AI,

[00:32:54] it's also, I think, in the world of GLP-1s 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. But yeah, like, now you're going to see what that is. Yeah, 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. When I was a CTO, we built everything from scratch. When I did consultancy work and now as head of AI for Sport Alliance, we are offering this as a vendor.

[00:33:24] 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'll be a lot of overhead.

[00:33:53] 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.

[00:34:24] 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.

[00:34:53] 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 and 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 and process. And even in the literature, I think the numbers were something like 33% success rate on building your own

[00:35:22] 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. Yeah, so let's get into that part. Locating the tech partner and licensing it and buying it is probably the simple part.

[00:35:51] 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, right? That's still very human component. So what advice or what guidelines would you give people when like, okay, if you're going to do it, be prepared to do it right and this is what it takes to do it right? Yeah. It's just 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.

[00:36:21] There's this rule that came up in the literature and I've kind of used this because it's an easy rule and it makes sense. It's this rule of 70, 20 and 10. So the 10% is, you know, kind of real technical algorithms, the models, the frameworks. The 20% is the 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.

[00:36:49] And you also need to, just one more thing on the data before we cover the people. You also need to think about future proofing the business. And this is kind of what we really focus on at Sport Alliance is building everything native, as I kind of mentioned, right? So it doesn't break down over time. Now, the 70% on people and process, by far the hardest thing. And that element comes into two factors. One is cultural readiness, which is a whole, you know, problem to unpack in its own right.

[00:37:18] And the second one is senior leadership and executive leadership, sponsorship and buy-in and 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

[00:37:47] 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 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 know, you name it.

[00:38:17] Going through, you know, 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 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 your organization. That is where all the work is. Now, if you crack that, if you crack that

[00:38:45] 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, out of 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, like 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

[00:39:15] 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 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 wants and desires. Yeah. We have emotions

[00:39:45] and goals change. 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 to get there and do it with, you know, a certain amount of excitement behind it too. So yeah, I'm going to remain on that for a while. That was really good. Thank you for that. You're welcome. There's more, there's more, right? I mean, even if, even if you crack it

[00:40:15] at the beginning, it has to be something that you perpetually look at. There was one interesting thing. There was two interesting things that came up in my research. One of them was familiarity bias, which was 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 start to go back,

[00:40:45] 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 it's something you have to, you know, maintain. And it's not easy. Yeah. You know, let's, let's zoom back out. That was great. Thank you for that. Like if you look into the future here, so we're 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,

[00:41:14] 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 in that timeframe? Yeah. I mean, it's, it's a good question. I'll give you my take, but I'll 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.

[00:41:43] 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 price 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

[00:42:12] and take the technology serious more would 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 someone'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 we're going to have these VR headsets

[00:42:42] and people are going to be training into augmented reality. 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. Just one thing I'll add and I always kind of take the commercial aspect because that's my expertise. The value, and I started with this slide in FIBO kind of like explaining where I think we are in terms of this AI hype cycle and so on. All of my research and all of my

[00:43:11] 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. Seriously looking at this technology takes one to two years to realize. So if you're starting now, you can do the math. You know, 28 is when you're going to start to really maximize the value that you're getting from this. So there's people that have already started two years ago. You know, Gymnation is a prime example. They are extracting

[00:43:41] 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're 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 Athletech the Athletech Innovation Summit coming up in, you know, as a recording just a few weeks away. So give us some insights, man.

[00:44:10] Like what are your expectations and hopes for that? Like what kind of conversations would you like to have? I know we're going to be on stage together. The details of that are still a little, we're figuring it all out but you know, maybe some ideas of, yeah, like what's your goal going into it? Who would you like to talk to you while you're there? And maybe give 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 Gym and Magic Line as Sport Alliance. I truly believe that we are

[00:44:39] 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 has always excited me because it's always the one that's willing to, you know, try things out and adopt and,

[00:45:09] 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 hold 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 on LinkedIn and we can connect there. 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

[00:45:39] specifically? Is it staff? Is it, you know, collaboration? 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 or 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,

[00:46:09] 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 was some really new perspectives that I gained from this. So really appreciate you doing it. I'm excited to see you in person in New York and sharing some stage time with you. So thank you. Ladies and gentlemen, Carl Foster. Thanks again. Cheers, Eric. Hey, wait, don't leave yet. This is your host, Eric Malzone and I hope you enjoyed this episode of Future of Fitness. If you did, I'm going to ask you to do three simple things.

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