AI Business Transformation with Gerard Murtagh

Foreign. So today we're talking about an AI business transformation. This is a real story about a real business who did real things that you could do, too. It's not some concept high futin AI carpet bagger out to tell you a bunch of snake oil that doesn't actually work or doesn't make a difference. That kind of thing is a real story about a real company that I met last year at Harvard and was really impressed by this guy. Humble, awesome. Well, sort of humble. He's proud of what he's built. He's going to tell you more about that. So hang in there just a second. We'll get right into all of what happened with his business and what it means for yours. So, hey again, everybody, Bill Gallagher, scaling coach and host of the Scaling Up Business Podcast. Our show comes here every week with stories about growing scaling your business with gurus, authors, experts, CEOs, you know, like all that. More than 620 shows now, wherever you're getting this right now, or@scalingcoach.com and our website, scalingcoach.com is where we also have monthly workshops. We just did one yesterday and we talked a lot through the basics of Scaling Up Now. But also we started to add in what are the AI prompts and the things that we're using with our clients? What are the methods we're using to refine strategy, to get the planning done faster than ever before with more ease? So all that and more@scalingcoach.com all right, all right, all right. So I want to welcome now he's on the screen already. If you're watching Gerard Murtaugh. Gerard, wait, what city are you in?

I'm, I'm on the Gold coast, so I'm in Australia. So good morning. Good morning to me. Good night to you. Good afternoon. Wherever you are in the world right.

Now, listening or wherever you're listening right now, right? Like people may be listening live, they may be listening on a recording or watching later. So whether you're watching us, however, Gerard joins us from Gold Coast, Australia, where he's got a company, he's a CEO of a company called Moldman. And he told the story of how their business really transformed and being ongoingly transformed with AI in a whole variety of ways. And it kind of started with a surprise, kind of a crisis that he'll share more about. We'll get into all that in just a minute. The surprise, the thing that led it to him, what they're doing now. But you guys, this is a cool story of, you know, not just one thing about how their marketing got a little bit better with AI, but like across the board in all areas of the business. So thanks for joining us.

You're welcome. Thank you for having me.

So you started as an entrepreneur at age 17. Your family had a business, right? There's a lot of that before we go into the crisis. And what led you into AI, Talk a little bit about kind of that entrepreneurial upbringing.

Yes, I come from an entrepreneurial family. My father had always owned businesses, my mother had owned businesses. And at a young age, I worked out that I wasn't sort of going to be going down the path of a normal. A normal career. You know, I was lucky to have a number of different neurodiversities that made learning very difficult, but they also gave me an opportunity to lead and to use my voice as a way of achieving my goals. And I was very lucky to have some great mentors around me that said, Jared, you're probably not going to get a job somewhere, but you can own the company. So if you want to be an architect, start an architect firm. If you want to be a doctor, then own a surgery, but you're probably not going to be doing the actual thing. So that was a sort of my upbringing. My father and mother were in their small business and then coming out of school, I was like, well, I'm just going to be owning business. I'm not going to be getting a job, so I won't be able to compete. So I started my first business, then sold that. And then a year after I finished school, my father passed away and, and his small business needed someone to run it. And so I was, yeah, 19 years old and thrown in the deep end. And, and it was probably, you know, it was battle. It was a, you know, baptism of fire. And, and that business still runs today. And I run that with my mother. And that's not Moldman, but it's. I'm very proud of that, that start. But, you know, that gave me a huge opportunity to, you know, to. I wanted to learn about business. Well, the way to do it is to, to, to be in it. And, and I was from a very early age and, and it set me up for where we are today.

So Moldman is a mold remediation and restoration company.

Yes. Yeah. So Moldman came out of a flood that we had. We hadn't had had a flood since the 70s. In 2011 was the first flood that we'd had in our city. And nobody really knew what to do. Like, everyone was like, what are we going to do? And obviously there was some incumbent mould remediation companies, but they were all taken by the insurance companies very quickly. I at that point owned a pressure washing company which was just another entrepreneurial venture that I got into at that point. And we'd been running for two or three years at that point and we had all the contracts with the city councils around our area. So they were calling us and saying, hey, you need to come and pressure wash this or that. But then they started talking about mold and I was like, okay, well when was the last major flood in the world? And that was in hurricane Katrina over in New Orleans. And so I jumped straight on a plane, met some people, went to the city council and said, I'll work for free, can you just teach us, teach me how to how you remediate homes after a flood. And after about two weeks I thought I knew everything and came back to Australia. And after about three days of being called the mold Man, I, I changed the name to Moldman and the rest is history. So we now are a national business here in Australia.

That's a remarkable thing that not everyone would do. You heard about a related event on the other side of the world and you got on a plane and you went and rolled up your sleeves and learned firsthand. Right. That's not a normal way that people jump into a business. Right. It's a remarkable thing in and of itself. Like just actually digging in and doing something.

Yeah, it is potentially for most people might seem a little bit odd, but the reality is that for me, for me to really understand a business, I have to be able to do it. And a lot of my businesses at that point were about doing so. The business that I had with my family was exporting different products into Asia. So getting on a plane wasn't really that hard. It was five weeks after my father had passed away, I was in Asia meeting clients for the first time and shaking hands and trying to navigate streets that had no English on them. And so for me to just jump on a plane was by that point in my life I was about 26 years old. I've been doing that for a number of years and for me business is always about the E. Myth is another is a great book that most people have read or should read if they haven't. Oh, that's amazing. Well, that shows like as business owners develop a business from scratch, they sort of need to understand and then once they can document it, iterate it and, and then be able to then train it, they can Then move on to the next thing. And as the business grows, and that's. We'll come back to that because that links into what everybody needs to be doing with AI. But that's how I learned. And I thought after two weeks I knew everything about mold. But it was, it was a great experience being in New Orleans and. But it was time to come home. And like I said, there was a. There was 200,000 homes that had been inundated. The insurance companies were backed up for years, and there was an opportunity to help people that were underinsured or that houses had just gone mouldy because it was just so wet here. And then from there we realized, okay, there's a real business here, and there's no one servicing these different segments of the market, which are property managers. They're like the people that haven't been flooded, but their houses have gone moldy, their bathrooms are poorly ventilated, subfloors, basements. No one was really servicing these clients. And so as we've gone on for the last 14 years, we've been able to continually grow the company by making sure that we address our core market segment, which is property managers. And now we have over 6,000 around the country that use us, and they control 2.8 million rental properties. So for us, our goal is to be the first choice in mold. We are the largest now in the country. And, you know, there's, there's no sort of stopping us from, from growing. So it's just ourselves.

You, that you had a crisis, you had a thing happen and that led you to your first dabbling with AI. Talk about what happened.

Yeah. So as businesses go through these different changes, you know, we, you know, you start a business from scratch, you know, one man band, and you go through these different stages as a business. We were growing at like 50% a year, year on year, on year. And then we had, we were in three cities and we had, we had just, we had a flood in every single one of those cities in one year at the same time. So this big weather system came through. And so we went from a really good local business in our state, you know, doing really well, to three states and at the end and during COVID as well. So you're in the middle of COVID you can't really travel. You've got these three floods that are happening. You're the first choice in for a lot of companies to use. And we grew that year over 300%. So for anybody that's been in a hyper growth market or A hypergrowth industry. You go through these things where we all get told, and we get told this perfect, beautiful line and it's awesome, which is what got you here is not going to get you there. But no one finishes the sentence. They never give you the context. And that is you need to throw everything out and start again. And some of those things you'll put back. But the reality is, is that a lot of what you throw out that got you to say 1 million to then to 2, to 4, to 8, to 16 to 20, those different iterations, you actually need to step back and throw everything out and then rebuild the business for a $20 million business or wherever you're going. And that's where your strategic plan and that's where scaling up comes in. And, and that. But I, for many years I thought, okay, well we were here, that worked. So let's just add on another process and add on another process and add another process.

Did that come at the same time as the fraud or was that an earlier event?

No. So the fraud happened because of the 300% growth. Because as we had created all these processes for a business that I could eyeball, everybody, everybody knew my name, they knew my family's name. We were a close knit group that had grown this business very well up to that point. And then you start introducing different people, but we had the same processes in place for a business that was three times as small, only like nine months earlier. And that gave people the opportunity to join our business. And we're Talking more than 80 to 100 people joining a business in a year. They've got the opportunity that go, well, how do you, for instance, how do you make a credit card payment? Or we go into Jared's office and you get his credit card and you buy the flights and you go, or if you need something, you go and do that. And so for me, as a business owner, I was extremely naive. I made a lot of mistakes. And what I did is I transferred that trust from 40 people that I knew their names to 120 to 160 people. And there was too much opportunity for people to do the wrong thing. And unfortunately, you know, good people got, you know, probably got too tempted. And by the time, because we were growing so much, the jaws of margin were just creeping up. But the margin wasn't, was, was not getting any bigger. It was still. But for a business that was, you know, making, you know, say, net profit of five figures a month, and now it's going and making six figures a month, you're like, wow, we're doing so well, but we should have been doing way better. And that was where that was. Unfortunately, by the time we did work out what was actually going on, it was just rampant. And I was on a plane probably three to four times a day. My accountants, once they picked up on it, we, you know, it was. It was wildfire. But, yeah, it was that. That. I think at the end of the day, we. There was over $600,000 misappropriated, and there was a lot of acts and other things that weren't lodged and paid for that were documented but then weren't done. So in the end, it's been about a $1.4 million hole that we had to dig ourselves out of. And to go from a business that had always been profitable, and then you think that the profits are going to be in those seven figures to then be going the opposite way. It was a massive learning experience and one that has shaped me and has now made this story.

I think it's useful to point out just the basic phenomena. So you work on things, and then either your strategy is right or suddenly fits world circumstances, something shifts in the world, and then your business is flooded with business. Right. When you go through growths, when you start to hit 100% or more a year, it's, like, really overwhelming. Now it's a little bit different if you're, say, a SaaS business or something where the scaling is a little more automatic. You could just turn on more servers. It's different if there's a lot of doing, if there's a lot of people and trucks and things running around, it can be more overwhelming. Even in a SaaS business, you've got new customers to make sure they turn on right and get successful. But in anything, there's a moment in inflection when everything gets overwhelmed. And in that space, you had this lack of control, and then things got out of whack and through direct and indirect actions, now you've got a $1.4 million hole.

Yeah, that's exactly how it happened. And you know what it's been like. I call it the best lesson I could ever learn as a business owner. I'm constantly learning, and I learned from failure. And we try and fail fast and heard all those stories, but, you know, we had to work out what our plan was to. What's the. You know, what's the problem? You know, what did we learn? How do we make a quick call, and then how do we make sure we don't do it again? But in that we also have to make sure that you don't just add another layer of process or add another layer of stopgap or employ somebody to be my gatekeeper, you know, at six figures a year, to just make sure that things, people aren't stealing things. Like there's gotta be better ways. And unfortunately, when you look at a business that have been around for more than 10 years, you do have a lot of these legacy processes that you just hold onto. And that's where something I learned through this is that don't add another process, actually throw it out. So we'll start again and there'll be parts that you'll put back, that's fine. But what you really need to be looking at is there may be some technology out there that you can use that actually stops 20 steps and saves you a lot of money. And for instance, we found a credit card company called Air Wallix, which was an Australian based business that we never knew about. That means I can put a credit card on your mobile phone within like 10 minutes, I can give you a certain amount of funds and then I can cancel it immediately or freeze the card also. And that was just the one. Instead of having more credit cards or more stopgaps or more problems, we were just. Everybody had like people that needed to buy things, you know, were given different processes. So that still, still meant that we could run fast, but it meant that we had control over the spending because there was, there was. I can run it on my phone, I can turn people's things off, my accountant can turn things off.

You use some AI to investigate the fraud, right?

Yes, you. Yeah, we did. So when we got our. So we knew that we had a problem. And so what we did is we downloaded all of our everything into a CSV file and then we uploaded that into a, into pretty much into a chat GDP wrapper that said these are all your anomalies. And one of them was $9,000 in Uber Eats. In one month we had 19 subscriptions for Spotify. We had. There was people taking flights that weren't my flights, but booking them under my name. There was. And so using that was like the first step of like, okay, this stuff's really amazing. It can get me information quicker than someone, someone else can. And being a business owner that had been sort of, had been so focused on process. And for me personally, don't get me wrong, I'm the guy that said put another layer of process like these, A lot of this stuff comes from me. Like there's definitely no amazing Genius here. It's like, let's put a process in so that it doesn't happen again. Well, those processes then, like I said, had to be removed. But because I loved what actually AI is, which is train a model, get the data, train the model, give it the outcome or the prompt, and then be able to then make a decision. I started to realize very early that this was my dot com boom. This was somebody that wasn't, wasn't in business during the dot com boom. This was the dot com boom. But it was something that I needed to invest in every, every single day. And then I harp on it a lot to my team and to people that, anybody that listen is that this is the thing that we all need to be like, be leaning into. And it's not just for the big companies, because if you left it up to the big companies though, they'll run this. They'll create businesses that are so much more efficient and profit and then the little guys will be left with less than 10% of the market. And so what you need to do is make sure that you get into that 90% because if not, you'll be just left with the crumbs. But we can talk a little, we can dive into that a little bit more. But that's how, like going back to your question about. That's exactly how we found out that there was a lot of abnormalities because we were able to compare data from a few years earlier where the accounts were not being abused right to now. It's like, well, yeah, there might have been some things like, yeah, your sales went up and your cost went up. But what was we, we dove into that and we found all these different anomalies.

So let me just throw another little teaser out. Your business now, across operations, across scheduling, across customer interactions, has AI processes running, hiring, other kinds of parts of it. What came next after the, the fraud analysis and starting to look at the mess that was there.

So we, we'd grown an admin team to 36 people. So that's people answering phones, booking in jobs. And that's a really, really expensive component of a trade business because you need them to do the business to and to be able to run a company. However, they can also drown the business. And that was one of the parts of the problem. When you've got so much process, you can throw people at a problem, but usually you've got the process that you've got to then identify. Then you've got, can it be automated, can it be done through AI or automation? And then You've got the human element, but before AI it was you've got a problem. Either perfect the problem through process or throw people at the problem. And a lot of people, especially in businesses that aren't looking at AI, will throw somebody at the problem. Like Jared. We need somebody to make sure that no one's defaulting the credit card. Let's go out and buy that and go get a new CFO or a CFO's assistant or a bookkeeper. And you're like, hang on a minute, we're just spending all this money on somebody to do that. We're just throwing people at a problem. But when we were growing so quickly, there were some days that we doubled the size of the company in an eight week period. You're like, just throw something, just hire somebody, just hire somebody, just hire somebody. So once AI, so there was this inflection point of you've just found out that you've got, you've been defrauded or there's been a misappropriation of funds right through to hang on. But you've got this tool now that can absolutely revolutionize the way that you're going to run your business. So what we. So the next part after that was what is our admin process and how do I cut down those, that number of admin that we have in the office A. Because I can't afford them anymore. And we have to perfect the process because if we don't perfect the process, then we're going to send ourselves broke, we're going to grow broke again because we would have just continually thrown people at the problem. So the first part of the process was that, and that's where we messed up as well. So at that point, most companies that were previously building a website changed their website around and said they were building AI. And so I was, yeah, we can revolutionize your admin process, Jared. And I was just doing all these projects and none of them worked. And it took me a few mistakes to get to the company and to find the team of people now that we're now using, that we actually trust and that have actually started to build it. So the first part of, to go back to your question, the first part of our process and the first part that anybody needs to be looking at if they're running, if they're looking at investing heavily into AI as they should, is to look at your process and what can you get rid of. So we have a five step process with that, which is the first step is what is the process and what is the problem that you're trying to fix. So identify that the next thing is to, you must remove, you must cut it back. You need to cut back. And Elon Musk said if you don't have to put 10% back, then you haven't cut hard enough. And so we live by that. Like I would prefer to something to break because we didn't or a process to break because we, you know, we took a cog out of the wheel to speed it up than to, than to worry about having too many cogs. So that's the next thing. Then you start looking at, at AI and automation. Because if you start building AI for an old process that is redundant, then you'll end up building things that you don't need.

And that's expensive with so many companies. And this is a very old thing, this is not a new thing. Don't go automate a broken process. Right. If you have some weird around thing that you do in your business that isn't smart and you don't know any better, like you want to first examine is what we're doing, does it make sense? Is it as good as or better than our industry? Right. You don't go build software or routines around something that you shouldn't be doing in the first place.

Yeah. And Then so the four step of the 100% agree and the reason is, and this is the biggest problem that people are going to face as they're building AI is the people aspect of it. But I'll just go through this, the five steps of what is the process automate. I can get like cut it back. So what is the process? Identify what it is, get cut it back. Can it be automated or can AI be put into it? If it can't, can it be done by somebody offshore or in the Philippines or something else? And then if it can't, how do we optimize it for a onshore person? So what we're finding is that there is that element that we can automate a part of the process, send it to the Philippines and then have it double checked either by AI now or by an onshore team member. So for instance, something that would take eight minutes now takes less than 15 seconds to check. So they're those little like 1 percenters that we're looking at, which is, you know, 7 minutes and 45 minutes, 7 minutes and 45 seconds every single time. And if you're doing that by 300 action points a day or 400 or 500 action points, that time's up. But one of the big issues that people are going to face with this is that third step of can it be automated? And we've found in our business, and if people, my staff are watching this, they're going to either nod or they're going to say that was me. But we have had people that have created process because it has validated their role. And what people are going to find that CEOs and the COOs, the CTOs, any operations people in your businesses right now, your team members are going to fight back against AI and automation because it validates their role. You've got it. You can tell them till the cows come home, like I do, that I'm not getting rid of you, I'm just giving an eight minute task down to a 15 second task. That's what I'm trying to, I still need you. Because we need, it's called human in the loop interaction. You need to have a human in the loop. So I'm not looking at getting rid of people, what I am looking at doing is giving them the ability to do a vast array of different tasks that are high value tasks instead of doing that, but doing the low level task or the task that can be done via automation. And that's where we're finding the biggest struggle that we're finding in even our business today is that processes are being designed to validate people's value with inside a business. And they don't want to give it up. They're like, I have to check the credit card statement. And so like, no, you don't. You put it into our system. It checks, it looks for, it's got a, it's got its gates, we call them gates. Like, how much are we spending on Google? How much are we spending on subscriptions? How much are we sending on? And if those gates come back red, then you know, you got a problem. That takes checking a credit card statement right down to, you know, a minute task every day instead of it being a, you know, you know, an hour long or even a full week of someone's task. So that's the like, if anybody takes anything from this today, like there's a number of things that you can take away from it. But understand that the people that are inside your business aren't going to be as excited about AI as what you are, because you can do so much more with the team you have if they're engaged in the process or what they will do is they'll just go, you know, I'm out. I'm like, you're going to get, you're going to fire me. So I'm going to be the strong one and I'm going to remove myself from this place because I'm not going to have a job because you'll just get rid of me. And it doesn't matter what I say to people, I'm like, you're either going to be using this technology here for the first time or you're going to be using it in one, two, three years time. When your new CEO implements exactly what we're building here. Which might sound a bit arrogant, but the reality is that we're building things that we haven't seen and that's why we're having to build them, I think.

Around a lot of different AI applications that we're seeing right now that human in the loop checking is really important. When I think about planning, strategy, work in particular, that as a coach we're using with clients and that continues to evolve now. But we get really interesting, useful drafts of things. But it's not like the final thing. You can't just use a bunch of prompts and then go, okay, that's your strategy. It gives you sort of like Don said, but it gets you so much further down the road, so much faster. So we'll come back on that. Why don't you describe what it's like to do like, what's the customer experience today and then the operations behind the scenes and where is AI going on within that? Give us a picture of that.

Yeah. So most of our clients are property managers or real estate customers. So they send us a work order that comes through their job management system. And in the past we would have looked at, tried to create API links or zapier links between those. However, every time they've changed their technology or they update it, the APIs don't work and it just doesn't work. So our AI is able to read our emails and identify what is actually going on in that email. And if it says certain things and it can understand because it's got over 2 million emails inside our data lake, so it can understand what's going on. It can create, you know, it's, it's goes through, identifies it and then it puts it into, into a new folder, that folder then scans that PDF and puts it straight into our job management system. So what would normally take somebody a couple of minutes to put in a job into the system, an email comes through and they manually do it is all done within about 15 seconds. So that's all done now via automation and AI. So that's, that's that first part of.

The process for a job, interpreting whatever the customer sends over, putting it into your job system. All that is happening by AI.

Yeah. And as we, as we train the model more, and we train it every single day, it's now being able to work out, hey, this doesn't have these things. I'm going to go back and ask it questions so you can ask the client, hey, can you send photos? Can you give us some more? Have you had a water leak? Do you have an exhaust fan? Do you have these? These, like different elements of the process that we need to make a decision so that when the, when it gets to the agent, the human in the loop, they can look at it and go, everything's there. This is. We can actually quote on this immediately. And we don't need to go out to this site. We have a photo. They don't have a water leak. They've got it. They've got no exhaust fan. The mold has been caused by a lack of ventilation. We know what to do. We've done tens and tens of thousands, hundreds of thousands of jobs. We know exactly what to do. Here's your price.

It gets it prepped, collects additional data if it thinks it needs it, and then the human looks at the thing and says, okay, here's what you got. They do the final check.

And so what we also do is we train the model based on what it did. So, well done. You did this. Well, like we talked with, its name's Ty, because we kept calling it the AI, so it's now called Ty. So Ty checks it and Ty will look at it and then it will give. It'll just, it'll wait. It has an alert. Somebody, a human in the loop, will check it and then we go tell Ty that it did a good job. Now, if Ty knows it's done a good job, it'll continue to learn that AI did that well. And just like we train a human being, you're training this brain, a model Ty, on how to make sure that it learns. So as we get further down this path, Ty won't need to ask somebody, it'll just send the quote. And instead of us having to check every quote, we'll check 95, then we'll check 90, and then we just keep iterating constantly and making it get better. So once the job's in the system, we then need to book it in. So what we've built is our own scheduling bot. Now, we're still training this, but it gets used Every day by our humans or a human in the loop basically goes in, build us a run. Instead of it taking a day to go, where do I want the technician to go? It doesn't have to do that anymore. You put in the, you ask for it to build a run. Tide builds the run. It then says, this is the most optimized run. Now Tide is, it's a 57% success, more optimization than a human, and it can do it within a minute when it can take a day to get a human to build a run. Like, where do I want to go now? Everybody, I want you to think about your local city and create a circle around it. You want people doing jobs either in that street or within a couple like 500 meters of that, that street. Now, if a job's come in right now and Ty knows that our technician is going there tomorrow, but it can fit in that inspection or that job. I will be able to then filter, put that in. And instead of the technician driving past that person's house, it gets that job in immediately instead of them having to wait two weeks when we're back in their street.

Because not everybody works in route scheduling and route optimization. Whether it's moving things around within a factory or a warehouse or being out in the world and dealing with traffic.

Think about Saturday sport when you've got.

Multiple kids like complex problem and difficult to do and manage. And people have played with software forever for this. But AI is a uniquely useful tool for this kind of route optimization. Scheduling.

Yeah. So the way that we've been able to do that is that we've been tracking our vehicles for many, many years. So we're able to use that data from our tracking, from our tracking. We also have got an API from Google so we know what traffic. We don't go near schools at 3 o' clock in the afternoon. You don't go over that bridge at 5 o' clock in the afternoon. You do all these different things. So you stay away from those shopping centers. On certain times, it knows where to go and what not to do. As we iterate and we get better at this, that data will be live from Google. So that means if there's an accident, it can reroute the guys, it can reschedule jobs. This all just takes time. And this is why, like we're 18 months to two years into this and we're still learning and we're still training and we're still, we're still getting better. It's not just we didn't just buy HubSpot off the shelf and we can start using it after, you know, you've really got it. We're working on this every single day. But Ty is like this, you know, it is like having an intern that you're trying to train on how to do a task and it never turns off. It's. It's next to every single person. And then over time, it'll just become, you know, it'll become much more intelligent and it'll be able to then make decisions based on real life data and not on people's work hours or availability or understanding that, you know, oh my God, the guys are, the guys are in that street right now, which is why the person's probably called us because they've seen the van and that's why they've called, because they've got mold and all they need to do is walk across the road. But, you know, they call a call center and no one knows that that will. They're not checking that we're actually across the road unless they ask the question, hey, how did you get our number? The tech guys are across the road. Perfect, I'll send them across. Ty doesn't need to know that. It knows where every van is right now. So that, that gives us that, that element of immediate action on what's coming in and what data is being. On what. On what data is being used to then make these, these decisions. From there, you've got customer experience on, you know, how to, like, what questions you have. So frequently asked questions are now all uniform, so I don't have to worry about anybody going off script. So as a business owner, you know, somebody over promising or saying we can do something when we can't, or, you know, or, you know, not telling somebody that we can do something like, hey, can you guys, you know, fix my bathroom? No, we can't. We only do this. Or, you know, yes, actually, we can fix your bathroom with mold. You know, we don't have to worry about those decisions not being made. And then from there, there's the customer experience going past that. So how do you stay in contact with people? How do you make sure that they know that you're still here? If there's a weather event in the city, we should be able to pick up on that very, very quickly and then be able to identify the clients that are in that area and then contact them and say, hey, do you need us? We're here if you do. So everything that we're doing now is instead of throwing a person at the problem, we look at the process, throw AI at the problem and then just try and get that smarter and iterate.

So how many people are you today?

So we've, we're, we're, we're lots. We're smaller than what we were a couple of years ago where I think we're just, we're maybe under 100 or 100, pretty close to where we are right now, about 100. So we got a lot higher than that. But again, you know we've got 15, 15 or 16 admins now and not 36 but we're doing more revenue than what we were doing when, you know, when the fraud happened. So it just shows that when you've got the systems and processes and you've got this in place, you don't need as many people because you're more efficient. Our technicians are doing more jobs, our admins are being able to do more with less and in the background the investments now we might be building a new piece of technology, a new part of Thai, but by adding a little bit more into tie, it may be maybe a quarter of the price of a full time employee for the year. So you know, we, it's a very good investment.

The customer service follow up, invoicing, emails collection, any of that stuff got AI?

Yes, email collection is definitely automation. Emails, they're invoicing? No, not just yet but it's, it's definitely in the pipeline. That's, that was offshore so that was one of those processes. What is the process? How do we can, can it be, you know, can we remove steps? What is the, could it be AI or automated? There's parts of it can, can it go to the Philippines? 100% it can. So it's in the Philippines and then an Australian based team member double checks and then, then they're sent off. But our team in the Philippines are amazing so you know they're getting 100% scores nearly every day. They're not happy. My team have turned an 8 minute task into a 15 second check per job.

There are so many companies that are doing offshore talent for a whole range of tasks and you can find some really lovely, competent and even highly educated people in some of those offshore folks. One of our sponsors, regular sponsor here, is probably not the company use, but we use a company called Doxa and recommend that to a number of our folks and worth checking out if that's something you're looking for. Tell us about the tools you've used and tried and what are the mix of tools and you said you went through a couple of vendors and that you finally settled on somebody that could be a good partner for you. Talk about that. Tools and partners.

Yeah, so the tools. So obviously we've all got access to chat GDP and Gronk and Llama 3 and all the others that are rolling around now. Claude, you know these, these tools are absolutely amazing and they need to be used. So I always recommend to people, part of my process is that I have like a separate Instagram account that I just follow AI people. And so every day I, I have time and you know, everyone, you get distracted with AI or distracted with technology, but I jump in and I go through everything that's come through that, either through X and on Instagram, of anybody that is of influence that is talking about AI. So that's one of my tools that I use on a daily basis to stay up with when are the announcements happening, what are they announcing and how do they work? And then what? And then I. Because it's not on my normal feed, it's certain amount of people and then I get through that feed that says you've seen everything you need to see. And then I, you know, I get out of it. And, and that's one of those, that's a very, very important tool because I wouldn't suggest you doing it in your normal feed because you'll get caught up with your best mates, trip to Tahoe or Japan or whatever, and you'll start going down a rabbit wall on that and you'll realize you've wasted all this time. So that's the first tool. The next tool is you need to be signing up to all these tasks and you just need to be looking and learning how to use ChatGPT or Chord or any of these others, because some are good for some of the tasks and some are better for others. But what we're realizing is that these big LLMs, they're going to become the engine for what we do. And then what we're going to have is these wrappers that are going to go around it. But what you need to be careful of is if you are using chat gdp, you don't have any of your identifying data. So if we put in a, if I put in my, say any of my financials into GDP like I did in the early days, which I don't do anymore. I made sure that we didn't have any of our company names or anything in that data. It was more about. We had obviously the Uber Eats and all of that, but we didn't have any of our data. And anybody that's putting their own company data into chat gdp. You're pretty much giving them access to everything that you're giving them. They own it now and they can use it to keep training their model. And that's how these models are getting very, very quick, are getting very good, very, very quickly. So be very careful how you use them. And if you, as somebody is building you one, make sure that they're not just building it on chat GDP or one of these others where you don't have, you don't have the security of your data. That's changing every day at the moment because people are working out how to do it without giving your data over and just using that LLM as the engine. And so what I like to say is like your car might be the, you know, let's say you've got a Mercedes Benz and you're going to go put a Bugatti engine in it and then the Bugatti engine might not work anymore. So you'll go and put a, you know, an Aston Martin in, or you'll put in whatever it is. The car is not going to change and the car is the data. And that's why, you know, we'll talk about what the process is for people to actually go through them, to start really investing in AI. But the car's not going to change the people, the contents, the data, but the engine that makes it go fast, that's what's going to change in the future. So being able to identify what works to go fast or slow or whatever you need it to do, that'll become very important. The other thing that we said that we then ended up going down, it was building our own LLM, our own data lake. So moving on from my last point, if you are really serious about transforming your business, you need to be looking. The first thing you need to do is your process and identifying that, but the next thing is to start looking at building your own data lake. And your data lake is like a brain. And maybe this isn't the right way of putting it, but you think about a brand new baby brain, parents pump information into it. It takes information in from everywhere, but it takes, as you raise a child, you are giving it the information that you want to give it. And an LLM is pretty much that it's a naked brain with nothing in it and you just give it the information that you want. So if you don't want it to know anything about, you know, goats in Africa, then don't give it that information, just give it the information for mold, like we did give it its emails, we put in our phone system. So it's got all of our phone calls, all of our scripts, every interview I've done, every podcast I've done, every email we've ever sent. And so Tye, which is our data lake, has everything that it has, our voice, so it sounds like us, our marketing can go into TY now and say, please write me an email, an EDM for the. We were in an awards night last night congratulating all the winners for this awards night that we addressed last night. Bang. It'll then write the email as if it was myself or my marketing team in our voice to do that. So the first step of anybody's transformation to AI is that data Lake, because then you will be able to then plug in the things that you need. So for us, it's the scheduling, it's also the email routing and replying, it's also the marketing side. So we've got the marketing component, we've got the phone system. That is. Within eight weeks, you'll be able to call Mould Men and speak to an AI agent, but it will be making decisions based on our data lake. So if you said, how did Mould men start? It'll give you. It'll tell you how mouldman started. You can talk to our. You will be able to talk to Ty for hours on end at 2 o' clock in the morning and learn all about mold. It won't know anything about anything else, but it'll know everything about mold men. It'll know everything about mold and you'll be able to ask a question. So some businesses will have to bring in their different operating systems, but if it's got. If you've got this core, this core brain, your developers will be able to get the API from your job management system or your operation system or your CRM, and then you'll be able to plug that in and every email you send, every message that goes out, every phone call, just makes that brain even better. And that's the first step of that. And we built ours on Azure, but the way that it's been built is that if Azure can't keep up or that engine can't keep up, we will plug. We'll take that out. And who knows, we may plug in Llama, or we may plug in Gronk, or we may plug in something else. It'll all depend on that. But your data lake is your secure lake of data that has everything in it. So if you're a CEO, that no one knows how to do anything inside your business. That's what you need to do. You need to clone yourself. So if you're Bill, you've got all of your, the way that you train people, your data, like your legacy is going to be your data lake. With everything that you've ever done, these 600 podcasts, the way that you speak, the way you write an email, that's what is the future of this. So people say, when will you give up business? And I said, well, I'll probably never give up on business because whoever owns my LLM or my data lake in the future will have, unfortunately they'll have my brain, so they'll be able to. That might scare the shit out of them.

But anyway, that's a good tee up for a little thing that I would love to sneak and offer people. It's not yet public, but we spent a lot of time looking at a variety of different tools and, and did some tests with a few of them and we've essentially built the Bill AI. And what I realized is that I have, you know, 12 years of blog posts and speeches and workshops and things like that and almost every last one of them I recorded and captured. And so I was able to upload more than 8 million words over that period of time to an AI and build bill AI that can answer scaling questions. And we have a few clients in using it now and we're using it for some of our company stuff in the back end, writing emails and posts and things like that and getting things ready. But we do, it's not yet publicly available. If you'd like to be one of the folks, if you'd like an invite, send me, and send me a request, say let me into your AI bill and send it bill scalingcoach.com and I will add you to our early list. We'll give a few people some trial to it and, and see what you think of it. I, I think mostly it's really surprising what you can build with that. And, and we have also a voice thing like it's trained, it talks, it sounds a lot like me when it, you know, you could talk to it and ask it, you know, things and it answers like Bill, which I don't know might give somebody nightmares.

But yeah, don't get me wrong, I've, I've been for many years being I, I've got through. I've been in Young Entrepreneur EO for nearly 20 years. 20 years is my 20 year anniversary being an EI and one of the things I learned early on was about journaling and writing and I've kept that up for many years. But you know, you've got all this information sitting in a, in a diary. It's pretty, it's pretty gnarly stuff. And I've got them locked away. And I was like, my kids will get these one day. But I changed it up recently when a couple of years ago and I went to voice notes. And so I sit here in front of my computer and I've got a designated phone and I just talked to my kids and I did it for my kids so that if anything ever happened to me, they would have all of this like the knowledge of these books that I've read and the podcasts that I've been on or, you know, I just talk to them as if I was having a conversation. And obviously it's somewhat one sided at this point, but I'm hoping that in the future that if anything does somewhat happen to me. Unfortunately, my dad passed away at 58 and I've only got like, I think maybe 10 minutes of him talking where my kids have now gonna have hours of my voice, which for them potentially will help them through their life. Because I'd love to call my dad and say, dad, my old man would have loved this time of humanity. He would have just been, this would have been his jam. And so that's what sort of forced me to do it. And so I encourage people to do that regardless because as you, as you, you can do this for business, but you can also do this for your family, can do this for your grandkids and your legacy can sort of live on and because we learn so much. But you know, there's nothing better than like, I got to. My grandmother lived into her 90s and she was so, so wise and you know, I loved, I loved my time with her because I didn't have my father to sort of help me through some of these challenges of my life or my, in my adult life. So, you know, I know that's a bit off track, but Bill, well done. Because it's not just about our business, Ackerman, and the things that we've done in business. It's also our ability to help our friends and our families and you know.

The kids coming, obviously the one that I've trained is really all of my business work. It's not all the little things but, but we think about that like that our friends and family who, who want to leave a legacy and there's that whole personal potential as well. It's Just getting better at, at the whole thing, at creating something that's useful so that you can remember. And that's obviously a very poignant experience for you to lose your dad at such an early age and really feel like, you know, you wanted more, you wanted him around for a little longer. So we've talked for a long time. I think we've given people a lot of things to think about. There are tools, there are partners, there are things. And it's not just getting your market right or banging out another blog post. It's a whole range of it in our world, strategy and planning and a whole lot of other things are getting done today behind the scenes with AI, we're getting more things done faster and up leveling the quality of it. But in your business, not only the financial analysis, the recruiting, the whole customer flow is all getting automated more and more, more at a faster pace. You've got a pretty big business to only have 100 people working on it. And it's, it's really an inspiring thing. I'm really glad to bring this to people that get them started thinking about maybe we could get it done and put some stuff in a lot faster. Right?

Yeah. Look, this is a, this is an arms race and I sort of mentioned it a little bit earlier on. We've going to have like your big think about your big 10 ton gorilla competitor that you might be in your industry right now. They're investing millions of dollars into AI because they know that that's going to be their competitive advantage. I did a speech recently and there was 500 people in the room and I said, who was expecting in the next two years to invest in AI? And only 20% put their hand up, 80% said they weren't interested. And then I said, well, the next question I asked was what? Who in the room is expecting their technology providers to build the AI for them? And they all put their hand up. Everybody put their hand up and said, I'm expecting HubSpot or our job management system or email or Microsoft or someone just to come up with AI. And that just makes, there's no point of difference with. If everybody's got the same technology, everybody's got it. So what the point of difference is going to be is going to be your data and the way you run your business. And that was the big eye opener to me is that people are still sitting back and saying it's going to be okay, I'll just wait for them. But what I'm, what I'm sort of really pushing to people to think about is if your biggest competitor, excuse me, if your biggest competitor is investing so much money into this and you're waiting for someone else, you will end up with the crumbs. You will end up with the worst clients, the worst paying ones, the ones you don't want, the ones that, you know, you learn at scaling up at EO and all these other IPO and all these other different people say these, you know, you need to go up these high value clients, the ones that pay you on time, the ones with the big ticket items, they're going to be going with the guys that can book a job in within 15 minutes or 15 seconds or that you don't have to speak to a human because you can do it all on your phone. Like for instance, in the future you will get onto either Mould Man's website or you'll call us and, and before you either put your phone down or stop talking to Ty, you will have got your quote and booked in your job and will probably have your credit card number. And then you'll think, wow, I've just booked in the job. I think I need to get two or three more quotes. You'll call the competitor and they'll say, I'll come out next week and inspect. And you've got, you've got. Moldman's already told you that they're going to be out there tomorrow and it's going to cost, you know, $400 and it's all going to be resolved. What are you going to go with? So that's just a real life case that Moldman, like we're right there where it's not fully turned on. There's lots of human at the moment, human in the loop. But there is a 10 ton gorilla that I'm worried about in trades building this before I do. So if you're in your industry and you feel like you can get somebody from Interact or from Lead to giving you their credit card in 15 minutes, regardless of whatever it is, then that's what you need to be focused on because if you're not, someone else will and then you'll just be getting the scraps.

All right, our show is running long. We've given people a ton of things to think about. Let me just point them to a couple of next steps and like, good, call it. So one, if you want to get into with Gerard, we'll put up a link for him. Gerardmartaugh.com it's on the screen if you're watching. It's also in the show notes, you'll be able to find it and check him out and get in touch with him if you want to know that. Let me just say from a lot of companies that I am currently working with and recently working with, working with, there's a lot of nervousness about doing stuff with your data and you probably have a lot more data that you realize like some of you have decades of transactional information, shipping information like in and there are patterns there. You can, we can create lookalike audiences, we can figure out where to go and who to do and what the best ones are and we can analyze financials, we can analyze transactions, we can look at your email, we can look at your voicemail. There's a whole bunch of stuff, stuff probably more than you realize that you have that could be gleaned in and you could start to build something. But, but get started. It's, it's not all done yet. But don't be the last one in figuring out how to do it. Or wait for your software vendor to give you something that everybody has and you have no specific real advantage beyond anything else. So those are some great things. If you'd like to try our little scaling up or my Bill Gallagher Scaling Coach AI, send me an email bill scalingcoach.com and we'll put you in the early the next batch of users that we let in to play with that thing and do it. Let me give a big shout out and thanks to my friend and mentor Vern Harnish Jordan. I met together with Vern at our Harvard CEO annual summit which is again late August. If you'd like an invite to that, you're a CEO, you're working with us now or regular fan of the show. Send me an email also and I will that that will sell out soon. It's not sold out yet but that that's a really great conference. And then of course thanks to Vern Harnish for starting this whole thing with the Scaling up framework and the YEO organization that we've been around for so many years. Thanks again to the folks at store on who get our show produced in and out every week. Seth, Christine, Dell, Cameron and the team over there. It's a lot of work to do this on a weekly basis for more than 600 episodes. So really appreciate our team wherever they are in in all realms and thanks again to all of you for listening for watching.

Until next time, keep scaling.

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