Business owners commonly face five mindset blocks that prevent them from implementing AI: (1) believing they need to learn AI themselves rather than delegating to specialists, (2) waiting until they're bigger or more ready to implement AI, (3) fearing AI will replace their team rather than recognizing it will increase efficiency and revenue per head, (4) not seeing clear ROI because AI benefits compound over time through lagging indicators, and (5) believing AI is moving too fast when in reality, the exponential growth of AI makes early adoption essential for competitive advantage. The key insight is that business owners should focus on determining what to automate (the 'what') rather than learning how to use AI tools (the 'how'), as their time is more valuable when spent on strategic decisions rather than technical implementation.
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Starting From ZERO With AI? Watch THIS firstAdded:
Every single business owner I know, without any exceptions, feels behind with AI. They don't know where to start.
They don't know if it's worth implementing. They don't know if it's a distraction. And when I ask them how much they're burning on manual processes, on follow-ups they never send, on leads that go cold, on team members spending half their day doing work a machine could do in 30 seconds, >> [music] >> or if they have all of their data consolidated in one place with AI analyzing it, they say they have none of that in place, or they're spending a [ __ ] ton of time, money, energy, and resources on people where AI could probably be doing majority of what they do. Now, I've now spoken to over 300 business owners doing six, seven, eight, nine figures a year, and across all of them, they all have the same five mindset blocks around AI and implementing it inside of their business, and every single one of those blocks was costing them money. So, in this video, I want to break down those five things, and you really want to listen to number three cuz I would say out of all of them, after taking hundreds of sales calls with people that we've personally built out AI infrastructure for, and speaking with hundreds of business owners on this as well, that is the one that holds a lot of them back the most. So, the first and most common thing that I see grabs these business owners by the balls and actually makes them resistant to implementing AI into their business is them thinking that they should do it themselves, right? And as a result of that, they think they need to become a master at Claude. They need to be taking 5, 10, 15 hours a week to learn how to use Claude, Claude design, Claude code, just Claude in general. They need to keep up to date with if they're going to use Manas or Claude or ChatGPT because they're in a constant race where one minute Claude is at the top of the hierarchy, then it's ChatGPT, then it's Manas, and then Manas has been blocked because for some reason Mark Zuckerberg was unable to acquire them. The one thing that you must understand when thinking about you learning AI yourself is it's the equivalent of really any other key role in your business. If you're doing 200, 300, 400 grand a month, are you doing your own accounting?
Probably not. What are you doing? You're either doing one of four things with it.
You're delegating, eliminating, automating, or pushing. The exact same thing applies with implementing AI into your business. The way that I see it with a lot of business owners is they think they need to figure out both of these things, the how and the what. Your job as the business owner is to figure out the what. What do we automate? What takes up a [ __ ] ton of our team's time?
What is costing us a [ __ ] ton of money in payroll that is recurring and admin heavy work that AI could probably do faster, better, or cheaper, okay? And I'll give you some examples of that very shortly. But the point I'm trying to make is you do not need to figure out the how. You do not need to spend 5, 10, 15, 20 hours a week trying to figure out how to use Claude, how to figure out what the terminal is, how to code. All of these things are below, more than likely, a key metric in the business, which is, honestly, the most valuable thing in a business, which is the founder's cost per hour. Now, the way that you're going to calculate this is very simple. You're going to take the amount of profit that you make on a yearly basis, okay? Or a monthly basis. And then you're just going to divide that by the number of hours that you work. Now, I'm not talking about the number of optional hours that you work.
If you're anything like me, you're probably a business owner that sits at their desk all the time. And reality is if you went on a vacation, you'd probably be good. If you've already got infrastructure, a team, you're already at a decent level, let's say six or multi-six figures or seven figures a month, your hours worked is probably like 70% unnecessary, 30% absolutely necessary. So, let's say for example, you make 100k a month in profit and you work 50 hours a week. Great. Now, if we do the division on those two numbers, that means that your cost per hour is 2K an hour. And when I say, "Oh, well, you should you be figuring out the how?"
Now, if your cost per hour was 20 or $50 an hour, yes, you should absolutely be allocating time to figure out the how, not the what, the how. That should be you because your cost per hour is below the amount or the equivalent it would cost to hire somebody in-house or just pay somebody like our team to do it for you. But in the event it is higher, which I assume if you're watching this video it is, then this is below your cost per hour. So, you've really then got two options. Either you hire an agency or you hire somebody in-house. I usually recommend that if you do truly believe that you have number one, if you have more than like 50 to 100 K monthly expenses, you should absolutely hire somebody in-house. Cuz realistically, to hire an AI specialist in-house, I know it costs this cuz we've already placed like 20 or 30 different AI specialists into other companies, usually it's going to cost you anywhere from 3 to 10 grand a month. And this just really depends on how good you want this person to be.
It's going to cost you like 3 grand a month if you just want a VA who's knowledgeable on Claude, who knows how to use the terminal, who you are going to have to guide and babysit a little bit more. This is better if again, you're a smaller company, and you are already very knowledgeable on AI. You just need somebody to do the grunt work, whether that be consolidating data into one centralized place, whether that be just executing on figuring something out that you've already fully documented on exactly how the process works, and you just need them to go and again, do the grunt work. But if you're looking for somebody to come in and also help you figure out the how and the what, what do we automate? Because at the end of the day, you don't know what you don't know, and they're the things that [ __ ] you over the most in business. The things that you don't know are the problems.
The things that you don't know can be automated. You are going to be looking on the higher range of around 10 grand a month. I usually see the average of what we pay when we place into other companies and ones that work on our team, we've got many, many AI engineers on our team, you're going to be looking at between the range of around 4 to 6 grand a month for somebody who's like a happy medium in between this one and this one.
So, TLDR, this in itself of I'm not going to bother implementing AI to increase my margin, increase the efficiency of my business, and ultimately get ahead of my competition, this is a massive limiting belief that holds people back. Because again, simply put, if your cost per hour is below that 20 to $50 an hour mark, yes, absolutely allocate time and attention to figuring it out yourself. And by the way, you should know on a basic level how to do it. You probably shouldn't be, if you're just doing a couple hundred grand a month, be hiring an AI specialist if you don't know how to use Claude, or you've at least played with it or made something to some degree, okay? But again, if you want to pay for the shortcut, hiring somebody in-house is going to be the best way of doing it. I know many, many people that have this exact same problem where either they thought, "I don't have enough work to hire somebody in-house, or it's just not a role that I think has a considerable ROI." Of course it does. Why do you think the biggest Fortune 100, 500 companies are spending hundreds of thousands of dollars on really good CFOs and really good AI engineers? Reason being is because the CFOs are able to identify who can be cut and what the AI specialist can automate. And then the AI specialist goes in and figures out how to actually do it in the first place, okay? So, that's the first piece of the puzzle that you need to get out of your head. You do not, and I repeat, you do not need to figure this stuff out yourself. You should not be watching all of these fancy AI YouTubers and influencers that tell you how to build these fancy vibe coded dashboards that can make you $300 a day. It is below your cost per hour and it is a distraction.
Your job as the founder is one thing, to focus on the money. That is usually going to be direction and vision of the company, and it's also just going to be RDX.
Revenue-driven actions. For example, if you know that your show rate right now is 40% and it should be 70%, well you shouldn't be spending 20 hours a week on figuring out [ __ ] Claude code, you should be figuring out how do we get our show rate back within KPI, cuz that will give us a 30% additional throughput onto sales calls, just as an example with an online-based business. Now, the second most common example is you're going to wait until you're bigger or you're more ready. Now, this one is also extremely expensive because right now AI implementation is, the way I see it is like SEO in 2010 or Facebook ads 15 years ago. The people who moved first had an insane advantage. They were able to capitalize on something that people saw as a distraction at the time. For example, I spoke to a guy who runs a meat processing business, like complete third generation, has more than 80 employees, eight butcher shops, 1,500 products. And what he said to me is that implementing AI in his industry is like inventing fire, because his competitors are 55 to olds who don't even know what ChatGPT is, right? So, point being is if he can implement that, he has a significant advantage over all of his other competitors. Another example would be a courier business that was doing around 30k a month, 16k profit, who wanted to scale, but if you left the business for an hour, it can't run without him. He's manually dispatching and pricing for two or three hours every day, and he said to me, "I think of like Uber. I don't think the CEO of Uber is out there dispatching and managing stuff." So, the cost of waiting isn't zero, it's cumulative and it compounds over time. If you look at the rate of investment in AI from, let's say, 2010 to 2026, what's happening is it's going up exponentially. What do you think is also going up exponentially in correlation to the amount of money that is being invested in AI? The rates of development with AI. What's happening is the smarter the AI gets, if we just rate this on like intelligence, let's say IQ, and time.
What's happening is through time, if I just draw this again to make it even more tangible for you, this is exponentially going up. Reason being is because as AI gets smarter, it's able to perpetuate what we call a self-learning loop, an SLL, which basically means that through time it's going to be able to adapt quicker, learn quicker, and once we achieve a point of what we call AGI, which means AI can learn at a level that humans can't even comprehend, this graph is only going to continue to get steeper and steeper, which means that's why you've probably seen over the last two or three months that the rate of AI growth has gone up far faster than the last like three to 10 years combined.
Because it's continuously getting smarter. The smarter it gets, the faster it learns. Which means if you ignore this, what's going to happen is we're going to get to a point where the delay or the lag that most people experience with AI, if it's exponentially growing like this, let's say like most people here, let's say like 10% of people actually start using AI at a level that they understand they need to. Let's say basic things like I'm going to use it to build a sales funnel, write sales scripts. I'm going to use it to help me as a founder be more efficient. What's happened is over the last like 3 months, the amount of people using AI has gone up by like an additional 10 to 20%. And this is only going to continue to climb, right? The way that I see it is there's something in business called the spectrum of uncertainty, which I love this as an analogy. Which basically means that most people make decisions in this bucket, which is the top 10%. These are the people that usually make the most money. Because what they do is they take risk and take action with such a high degree of uncertainty that the payoff reward on that is huge, but the risk is obviously high. These are the first movers. This is what we call the FMA. The first mover advantage. Then you've got the medium average kind of business owner. This is like 70% of people, who then wait for the first movers to validate that something works, to validate that in AI as an example, it can make them more efficient. They can start laying off team members. They can be more profitable. Then what they do is they're basically sheep and they just copy the first movers. And then you've got the other 20% who wait for hundreds, if not thousands and millions of people, to eventually then decide, "Oh, I'm going to now start implementing AI into my business." It's like the people that invested in Bitcoin when it was going on an upward trend, or in that 70%. The people before the upward trend that took a high degree of risk, had an extreme disproportionate payoff as a result of them taking a high degree of risk that other people weren't willing to take.
And then you look at people now that are investing in Bitcoin that are in this bottom spectrum, they're going to get nowhere near the level of payoff that this top 10% did. So, the point I'm trying to make here and to articulate to you is AI is only going to get smarter.
It's only going to get faster. And the faster it gets, the smarter it gets, the more people in this bottom spectrum are going to look up and go, "Ooh, maybe AI can actually truly help my business.
Maybe I can probably lay off some team members. Maybe it can automate all my data reporting. It can automate my processing, my billing. It can manage my ads for me. It can build my funnels."
But the top 10% are already doing this stuff. In fact, they've already been doing it for a long time. Like us as an example, we've been doing this for a very long time now because I knew that this was something that was going to make me a [ __ ] ton of money, and that is why we are moving extremely fast. You have to understand that in 2026, and this is only going to continue to get even more prevalent, the people that win in business are the people that possess the trait of adaptability.
You quite literally need to be like a chameleon in business. You need to be able to change states. You need to be able to adapt to your environment. If you do not adapt to the environment of the fact that AI is going to take over majority of businesses in the next few years, you will be left behind and you will be beat by the competition that do implement it, that do let go of what we call the sunk cost bias, which is what holds most people back from actually investing the time, the money, and investing in somebody full-time to actually come in and help them with this stuff. It basically means they're so stuck on their current way of doing things, their current processes, their current automations, their current tech stack, that they don't adapt. And as a result of that, eventually, it will hit them like a truck. New competitors will come in, will be able to outspend them cuz their margin are higher, can move faster, can adapt quicker. Adaptability is something you must possess now more than ever. Now, the third thing, and I don't really understand this one, which I do to a degree, but it is what it is, which is AI is going to replace my team.
We're going to lose the personal touch, right? We work with a client, they have a care home, they have 13 homes, 170 staff, they're expanding to around 300, and he said to me that compliance audits could be automated, like most of them, right? But the personal touch is you could have a template that populates most of it, and then has a human eye just sort of run through it. Another example would be a real estate broker client with 4,000 leads in their CRM.
They said they didn't want to expose their database to a third party such as AI. Now, the truth is that every one of these business owners eventually realized that AI is not replacing their team. It's replacing the $15 an hour work that your $150 an hour people are currently doing, Okay? So, you way you want to see it is AI again is not going to take your team of let's say this is you, your operations manager, you got a media buyer. I'm just giving an agency example cuz this is something I'm clued in on. Media buyer, a tech person, a CSM, and maybe you have a bunch of other people in the team. It's not going to start just firing these people right away. It's going to increase a key metric in the business called RPH, which drives the number one thing that you want, which is profit. RPH is revenue per head. So, if you take your revenue, let's say for example as a business you're doing 100K a month.
And you have 10 people on your team, which would be a very lean team at 100 grand a month, which is a great position to be in. That means your revenue per head is 10K. That's great. The higher this number, the higher your profit.
Simply put, the less team members you have, not only the more profit you make, but the less headache you endure. If your revenue per head is high, that signals to me that you have better team members. So, the way that I see it with AI is again, it's not going to take a team member, let's say a customer support agent that handles 50 clients and calls them and manages them and makes sure they're happy.
It's not going to remove this person completely. It's going to take them from being able to manage 50 clients to let's say 100, which doubles their efficiency, which means it doubles their revenue per head. And if we double their revenue per head through enough time, that means we only need to hire one person for every 100 clients instead of 50. Again, we are not firing this person, we are making them more efficient. When you double your efficiency of that person, you double the revenue per head and you incrementally through time start to incrementally increase the profitability of the business. And what happens when you increase the profitability of the business? It means that you can hire better people. Nobody on their team wants donkeys. There's three different types of team members that you can have and I'm going to abbreviate them between D, C, and S. You've got the donkeys.
Donkeys are the people that you don't want that are being paid a low salary that are doing admin recurring based [ __ ] A lot of these people will and can get fired and you don't want these people on your team anyway. You might have heard of the analogy that one bad apple spoils a bunch. The donkeys on your team that don't really do anything, that don't really act on initiative, that cry about every single situation that they're incapable of solving themselves, and rely on everyone else in the organization to solve them for them.
Nobody wants to be around those people.
They're going to go. But, the camels, these are the camels that are they see the vision, but they need whipping every now and again to take the action, but they're incredibly consistent. These people are going to stay. It's just going to make them more efficient. The people you want to now start allocating your time and attention to once you start using AI at a level that nobody else in your industry or niche is is the stallions. The stallions are the people that just need a target. They need to know we're here, we want to go here, and if you get in their way, they're going to run you over. So, you best move out their way. These are the best people, but also the hardest people to find, and the people that get paid the most. And the good thing is, once you remove the payroll of the donkeys, and you have the camels that can basically be more efficient, so you need less of them, you can start investing that capital into getting better people, which again means that the organization all round is more efficient. The culture is better, because the culture is always better when everybody is an A player. Everybody is absolutely crushing it in their specific division. So, that belief on like this is going to ruin the culture of my team is the complete opposite of what this is going to do. It's actually going to make the culture even better, cuz it's going to make the people even better. Now, moving on to the fourth one, which is I can't see an ROI from actually implementing AI into my business. Now, this is the thing. If you were to run a paid ad to acquire a client, and I said to you, "Put a dollar in, I'll give you $5 out." You would give me everything in your bank account, because I just gave you a predictable lottery. A way that you could put your money into a pot, and magically, in a specific window of time, let's say 30 days, 60 days, whatever it may be, you can immediately make $5 back. Now, the argument against this is, "Well, with AI, you can't really quantitatively say, within X amount of time, you're going to achieve Y amount of unrealized returns.
But, what you have to understand about AI is it is a quantifiable and unquantifiable return. It is really a non-binary. You could argue the same thing with saying, well, I got two different people that I'm going to hire.
One of them is an A star player, and I truly believe that they can help us grow the organization, but I don't know what that looks like. I can't quantify that, and this guy gets paid 10K a month, right? And then you've got option number B, who let's say they're good, they're not as good as this person, maybe they're a B player, but they want 5K a month. Now, if you were a smart business owner, you would understand that the best investment you can make is in talent. People in your organization drive everything. You look at the best companies in the world, you look at Amazon, you look at the Apples.
The founder of that business, Jeff Bezos, Bill Gates, they are not in the day-to-day, obviously. They sit on their boats, they think about the vision, they plan, and then they let other people do the [ __ ] for them and figure out what to do based on the vision of the company, okay? So, obviously, if you're a smart business owner, you would pick option A.
The exact same principle applies here.
Could you, and will you, if you're a capable business owner, grow your business without implementing AI? Yes, but again, it just goes back to the spectrum of uncertainty that I gave you.
Some of the best ROIs that you will get in business are from things that are unquantifiable, and things that take a little bit of time. Because most things in business operates through a law of what we call lagging indicators. Much like when you put popcorn in the microwave, the popcorn bag doesn't pop immediately. You have to give it a couple of minutes, and then all of a sudden, bam, you start to notice the outcome that you initially wanted through the time that you put in. Same with business. When you first start your business and you have no prior experience, usually what happens is the money that you make usually just starts going up exponentially. But, all this work that you put in for 3, 6, 12, 18 months beforehand, where you see no results, is you're just delaying the gratification because you understand that eventually the work that you put in will eventually compound. Like an example of that would be, one thing that we recently just built out internally for our businesses and many other businesses is a centralized source of truth of data where they can see every piece of data in their business from every sales conversation that takes place. Not only the quantitative data of close rate, show rate, cash per closer, cash per call, but as well also looking at most common objections, most common pain points, most common desires. We can also see all the ad data, organic data from videos like this, Instagram, LinkedIn, whatever platforms that business acquired clients through. And then as well we can see all the other stuff such as if they had payment plans, what was the payment plan collection rate broken down by customer support representative. What was the renewal rate by customer support representative.
Now when we build something like that out, it's not like the business is going to double overnight. Of course not because it's an unquantifiable thing.
It's like if you make an improvement in your operations, your systems, your fulfillment, you're obviously not going to double the business overnight, right?
But you understand that's the foundation that you build that allows you to shoot up far faster than everybody else.
Because in my opinion, sales and marketing in a business, once focused on, especially in a service-based business as an example, it's pretty [ __ ] easy. Because it's a lot of the time a quantifiable result you're getting for a client. We'll build this, we'll do you this, we guarantee you this. But the thing that's unquantifiable that you know that compounds through time is the fulfillment, is the operations, is the team. The way that I see it is the sales and the marketing, yes, are what drive the money into the business. But if you're driving money in, if we give you an analogy of if I built a skyscraper on a couple of wooden poles like this, I would start layering on building blocks and layers. But eventually that skyscraper would fall down because the foundation was weak.
The foundation in this scenario is the operations, the fulfillment, the AI infrastructure that you have built into the organization. That being said, if you spend the time to build the foundation extremely sturdy, you implement AI at a level that nobody else in your market is. You're more efficient, you can move faster, you're more adaptable, you don't get stuck in the sunk cost bias. And on top of that, you have good operations, you have good systems, you have good fulfillment, you have good team. Then, when you start to layer on these building blocks, it makes things so much easier and so much faster. But you have to build these things out first. So again, you must see these things as something that is yes, quantifiable in terms of what it can do, but unquantifiable in the results, and operating through the law of lagging indicators, it will take time to see the return. And if you're not willing to wait for that, then great, just let your competition do it instead, who are willing to wait to bear the fruits of their labor. Now, the final one, which closely ties into a couple of others that I've articulated in this video, is AI is moving too fast.
Which means I'm going to build something out, and then it's going to break right after. Now, what you must understand is the rate of AI is never going to slow down. If anything, it is only going to get faster. We've already gone over how once we achieve a point of AGI, the self-learning loop, the rate of learning, the rate of investment, it is all going up exponentially through time.
I can almost predict that this time next year, we'll be in a position that we can't even comprehend right now with AI.
It will be able to do things that me and you as humans won't even be able to perpetuate or understand. So, the point I'm trying to make is this moving too fast thing is the exact reason why you need to do it because it's not going to slow down. I've already told you that there's really two types of business owners right now that we've analyzed after getting on calls with hundreds of other businesses that want us to build out this infrastructure into their company. There's business owner A and business owner B. Business owner A is adaptable, understands that this is an opportunity of a lifetime. This opportunity is never going to happen again, quite frankly. I see this as like the last Hail Mary attempt to drive as much revenue into your business as humanly possible because you look at the internet, yes, it was big. You look at Facebook ads. Yeah, it was decently big.
You look at SEO when it came out. It was big.
But AI is changing everything.
Everything. It's not just changing the online business world. It's not just changing the offline business world.
It's not just changing marketing. It's changing everything in the world. Now, you're the type of business owner is business owner B, who is resentful, who is like, "Oh, you know, I don't like AI.
I don't want to become an AI-led business. I just don't think that based on the way it's going that it's ethical or right." That's fine. But if you resent these things, the only way that you're going down, my friend, unfortunately, is down a path of going out of business. Because there will be people that are relentless, that are savages, that will implement these things faster than you, better than you, and will be able to operate cheaper. And let's say we have two types of businesses. Let's take a marketing agency. One of them does 200k a month.
The other one also does 200k a month.
But the difference is this one has 30 team members and a 20% margin. So, they're operating at 40k net. The other one has 10 team members and they're at a 60% margin. Which means for them, they're operating at like 120k net. That basically means they've got an additional 80k in profit every month to beat these people out of the market.
Which what do you think that means? They can hire better talent. They can invest in better fulfillment. They can invest more in ads, because the person that ultimately spends the most on ads gathers the most data and ultimately wins. The person who can pay the most to acquire clients always wins. And the people that have the highest LTV, which is what these people are going to be able to achieve. So, there you have it.
They're the five most common things that I see holding people back from implementing AI into their business. And if you want to know exactly what AI can and can't do in your specific business, you want us to pull apart the business, tell you what you can and can't automate, and even potentially even go as far as building out for you or placing an AI specialist in your business, check the link below this video. Alternatively, if you want to build an AI-enabled agency and you want to see exactly how we're doing it, you can click the second link in the description and I'll see you on the other side.
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