The "Boring" AI Niches Making New Millionaires in 2026

The key difference between those that are succeeding with AI and those that are not is actually very simple. The

winners understand that AI is not disrupting software. It's disrupting

disrupting software. It's disrupting labor. And what we're seeing is

labor. And what we're seeing is literally the first time in human history where we can code real physical tasks in the real world. Now, don't get me wrong, the SAS opportunity is still a

massive opportunity. It's generating

massive opportunity. It's generating around $700 billion a year just in the US alone. But the labor market makes the

US alone. But the labor market makes the software market cap look like a bug on the windshield. I mean, in North America

the windshield. I mean, in North America alone, the industry is raking in a whopping $12 trillion a year. And the

best part, guys, is that this entire market is literally up for grabs for the first time in our entire lives. Now,

this opportunity became so obvious that the biggest AI companies are now starting to compete for this market share. I mean, look at Tesla. They're

share. I mean, look at Tesla. They're

creating robots to literally go and do physical tasks in the real world. Look

at Chai GBT. They're trying to create their own AI computer. And even that little robot that's cleaning your dog's stain right now is trying to dominate the cleaning space. And in this video, I'm going to break down the most

simple industries that used to be pretty boring, but are now extremely lucrative opportunities. And we're seeing the

opportunities. And we're seeing the newest AI startups come into these industries and build multi-million dollar businesses in a matter of months.

And like I was saying earlier, people still think that AI is disrupting software. So literally no one knows

software. So literally no one knows about this. So in this video, I'm going

about this. So in this video, I'm going to be breaking down multiple AI service opportunities that currently have little to no competition. And I'm going to break down a whole list of examples of

AI service agencies that are doing this in a variety of industries. And then I'm going to finish off by explaining which AI service niches I think would be the most exciting for you guys to start

heading into 2026, as well as all of the learning materials that you may need to be as successful in 2026 to make it your best year ever. If you don't know me yet, I'm Kev. Most recently started my

own AI startup, Creator OS, and it's absolutely taken off. And our AI service niche is in the video content production niche. On top of that, I teach

niche. On top of that, I teach everything that I know to my no code academy. We have over 2400 members and

academy. We have over 2400 members and so I try my best to give you guys everything that I'm learning as fast as I can so that you guys can win alongside me. Now today guys, I prepared an

me. Now today guys, I prepared an absolute masterclass of a presentation.

Buckle up, like this video and let's dive right in. All right, so the first slide we have today is the traditional software opportunity. And this SAS

software opportunity. And this SAS market is a $1 trillion market in North America. And these companies are just

America. And these companies are just the companies that we all know and grow up with, right? to like Amazon, Microsoft, Adobe, Salesforce. And

essentially what these businesses have done is they've systemized information and they've automated workflows. So

Adobe, for example, was the go-to name, the household name for anything to do with photo editing, video editing, 3D design, and this took a lot of work

before the AI boom. And so these are just the examples of the SAS markets of the past. And the reason why I bring

the past. And the reason why I bring this up is because the AI software opportunity is eating up the traditional SAS opportunity, right? So the labor market is a 12 trillion market and the

AI software opportunity is absolutely eating this alive. And I have some examples for you. So like Hen for example is an AI video production software company that is absolutely

changing how videos are made. Imagine a

traditional social media agency that had to manually go to their clients, film them, and then grab that content, take it to an editor, edit it, and then manually take those edits and upload it.

You compare that with something like Hey Jen, it's a night and day difference.

You just grab their clone, and now you can produce content on their behalf 24/7. Same thing applies for software,

24/7. Same thing applies for software, right? So developing software with

right? So developing software with cursor allows the developers to actually charge a lot less, build products a lot faster and in that way the market for software development labor has

absolutely exploded especially in 2025.

Now something like 11 Labs changes the game for voice. So now we're talking phone agents, outbound and inbound.

We're talking podcasts. We're talking

real time customer support. There's a

bunch of ways that that voice and audio production also gets involved. And the

most slept on opportunity right now is the physical labor and transportation era. And this is why I'm really trying

era. And this is why I'm really trying to knock home that you guys should learn AI development and AI no code before the robots get here because we're going to be able to program the robots. And so

the key difference between the traditional software opportunity and the AI software opportunity is that AI is

systemizing labor. It's customizing

systemizing labor. It's customizing automations specifically for a business's needs. Now, let's break down

business's needs. Now, let's break down how this actually plays out in the economy. So, we have these traditional

economy. So, we have these traditional businesses Amazon HubSpot Microsoft Adobe, Salesforce, and they are all seeing this ridiculous boom happening in real time as well. And they want to get

involved or else they're going to get out competed and replaced. And so, what these companies are doing is they're teaming up with the biggest LLM companies in the world. you know, the anthropics of the world, the open AIs of

the world, and they're combining their powers to create enterprise level value.

You know, working with the biggest banks in the world, the biggest lawyer companies in the world, the biggest insurance companies in the world, the biggest e-commerce brands in the world.

And that is also tying into the 12 trillion service economy. And so, the portion of the service economy that has already been eaten up is only like 1% of

the entire labor market. And we are slowly seeing different AI services start to eat up this space. And so

currently we can see like I said earlier like 11 Labs, the Hen example, the Tesla example, the Cursor example. They're

already starting to dive into the 12 trillion economy here. But the next wave that's going to be coming is these previously built enterprise companies are going to start tapping into this

market as well. But the good news is is that they're only going to be working with the enterprise level businesses, the businesses that are in the multi-billion dollar a year in revenue.

And so with that being said, no matter what, this leaves a massive window of opportunity for us to actually tap into the rest of this blue ocean opportunity

because no big enterprise company will be able to tap into the things that I'm going to show you today because it's too small for them to want to go after. So

you may be asking at this point, where is the opportunity in the new AI economy? And I actually created a math

economy? And I actually created a math equation to make this very simple for you. So the oneliner that I have is you

you. So the oneliner that I have is you need to systemize a high return on investments labor system for a niche that the enterprise AI companies don't

give a about. And so this is Kev's AI economy opportunity equation. The

first thing that we need to be looking for is a form of labor that can now be automated for the first time ever. So

whether that's generating sales, whether that's creating content, whether that's highlevel copywriting, business operations like receptionists, doing cold outbound like instant leads, email

marketing campaigns. And so once we

marketing campaigns. And so once we figure out which forms of labor can actually be automated, the next step is to understand that we need to be in an industry that is non-monopistic, meaning that there is no number one dog in the

space. And so a good example of this

space. And so a good example of this would be like insurance agencies or you know vets that are taking care of animals because they fundamentally cannot have a number one leader. These

are all local businesses and it's tough for any one business to just dominate the rest. And so that is step two. The

the rest. And so that is step two. The

third step in the equation is that it's a non-enterprise business. Meaning there

is no traditional SAS that is already trying to dominate this niche. There is

no Amazon in this niche. there is no sales force in this niche. And in the next slides, you guys are going to see a whole bunch of examples of this. But

most importantly, we need to think about what are the niches that the LLM companies like OpenAI and Enthropic and Gemini are not going to disrupt. And so

when you have all three of these, you have an absolutely huge opportunity to disrupt a specific industry. So now

we're going to grab that equation from the last slide and we're going to put it into practice. Right? So the best AI

into practice. Right? So the best AI agencies and the best AI startups are already using this equation to print millions of dollars. And so if a business can build some type of later

labor automation in a non- monopolistic industry that it doesn't have an enterprise company that is dominating the scene, then you can actually take take it over in a matter of months. I

know it sounds kind of ridiculous, but let's go through some of the examples.

So my AI startup, Creator OS, helps people in marketing agencies. We help

you automate content at scale. We help

you build your personal brand without you actually doing anything. And in this way, we're competing and we're trying to take over the space because the previous AI marketing companies only offered the

systemized information. They didn't

systemized information. They didn't systemize the labor. And so, we're tapping in and systemizing the labor.

And we're going to dive into that a bit later. But some other examples, and one

later. But some other examples, and one that's actually up for grabs right now, is like automating the entire dental office business, right? So, what kind of labor can we automate here? Well, we can automate the receptionist. we can

automate the customer experience. It's

non-monopistic because a bunch of different dental offices are spread all across the all across the world, all across North America. And it's just fundamentally not a business model that could be, you know, built in in a

monopolistic way. There's no apple of

monopolistic way. There's no apple of the dental industry. Now, let's get into some other AI operating systems that are already starting to dominate their niche, right? So, for veterinarians, we

niche, right? So, for veterinarians, we have Vetneo. And VetNo is a full stack

have Vetneo. And VetNo is a full stack software application that helps veterinarians scale their service, scale their business. So they really just have

their business. So they really just have the focus on taking care of their animals, taking care of their patients, and in that way it streamlines their business. We have the same thing with

business. We have the same thing with hotels and Airbnb by this company called Aura. They are doing the exact same

Aura. They are doing the exact same thing, helping people book in their hotel check-ins, helping generate more leads for these hotels, and streamlining the operations for these hotels. So, not

only is this type of business model going to generate money for these b um for your clients, but you're also going to cut down costs, you're also going to streamline their operations, and all of that is a win for them. Even something

like car dealerships, right? So, this is a pretty new one, dealer.ai. Dealer AI

essentially uses a bunch of different automations, a bunch of different agents, but are tailored to car dealership industry. And one and one of

dealership industry. And one and one of my buddies on Twitter, his name's William, he's working on video editing.

And so this is something that if it could be automated, it would be absolutely gamechanging because like even for me right now, I have a whole list of editors that I'm paying a good amount of money for to edit my videos

and my client's videos. And so if he can go ahead and actually build an AI video editing software that streamlines that process, this creates an insane

opportunity. So now let's talk about how

opportunity. So now let's talk about how these companies are actually going from you know their idea to launching their product to then systemizing their product and then dominating their niche and becoming the AI operating system

that everyone thinks about when they go into their niche and actually start marketing. So the first step that all of

marketing. So the first step that all of these businesses are doing is that they're solving one specific task in a broader business category. And so that could be sales, that could be

operations, and that could be marketing.

There's other options as well, but let's just stick with these three for the time being. And so once these companies start

being. And so once these companies start automating and and solving specific tasks, they can then lead into a specific niche. And so for some sales

specific niche. And so for some sales examples, we have dealer AI. Dealer AI

will bring leads to the dealership, track the CRM, track the customers, track the inventory, track the revenue, and it's all inhouse. And so like the dealership client doesn't need to pay

for any other software. They don't need to be looking for the best AI services because the AI agency that they're working with is going to provide that to them. And so it's a win-win for both

them. And so it's a win-win for both teams. Another one could be our system will send leads to your booking appointments. And so this could be for

appointments. And so this could be for like insurance agencies. This could be for like local businesses that are looking to close clients or close other businesses in their local domain. And so

something like insurance OS would absolutely dominate here. And here are some marketing examples. Right. So for

creator OS, we will build your personal brand and we will generate your contacts and we'll generate your leads and we'll generate your sales all on autopilot. So

you just have to focus on scaling your business and serving your clients.

Another example of this is Slang AI.

They do the exact same type of service but for restaurants, right? So we're

going to bring you customers. We're

going to make sure that your marketing online is well represented and we're going to make sure that since starting working with us, we generate you more revenue than you ever had before. All

right, guys. Now, I really need you to focus up here because this is what's going over people's heads. And so, I wanted to give you guys two examples here of the pre-AI era business model

and the postAI era business model. So,

let's first start off with the preAI era. All right. So, let's say in the

era. All right. So, let's say in the preAI era, I was trying to build a car wash CRM and a car wash marketing SAS to

generate clients for all of the different car washes in the US, which is 60,000 different businesses. So, this

traditional software business offer would look something like a $100 a month retainer. And what this software will do

retainer. And what this software will do is streamline the operations but not streamline the labor, leaving a massive window for AI first startups to disrupt this industry. And so since we're only

this industry. And so since we're only systemizing the information in the pre-AI era, the total market cap is only something like 60 million for this type of business model. But it gets really

ridiculous once we enter in to the post AI era, right? So using the exact same industry, we would then be reaching out to the same 60,000 car washes, but instead of just delivering a software

that systemizes information, we're going to be giving them a software that systemizes labor, aka generating them leads, social awareness, sales, streamlining operations, and more. And

so all of a sudden, the pricing goes from $100 a month to $2,000 a month. and

your relationship with the client is going to be very very sticky because once you start delivering results, they would be absolutely crazy to then walk out the door. And that's the other

underlying advantage of the post AI era.

You have the full autonomy to deliver results without your clients doing anything. And that's the value of the

anything. And that's the value of the labor. And so once you deliver those

labor. And so once you deliver those results, there's a whole AI consulting branch that opens up. There's a whole marketing branch that opens up. And you

can actually sell the software as a standalone product to these car to these car wash um businesses. And in this way, guys, a 2,000 a month retainer times

60,000 car washes all of a sudden becomes a 1.4 billion market cap. And so

this industry, for example, grew 15 times in the opportunity for AI agencies to disrupt. Now, it does get even better

to disrupt. Now, it does get even better because when AI labor is actually at scale, this is going to create abundance

and then abundance creates demand and demand creates growth. So now imagine a car dealership that was just starting off, just getting off the ground. They

couldn't afford a traditional marketing agency to just produce like 20 videos a month because they had to go manually film, then manually edit, manually do the copywriting, then post and manually

engage with the audience. And so for a car dealership that's just getting off the ground, doesn't have that much revenue in their pocket, this is going to be very difficult. In the post AI era, you could do the exact same price

offer, but what you're going to be delivering is going to be multiple times more effective. You're literally going

more effective. You're literally going to be able to produce a,000 videos a month instead of 20 because everything in the system is automated from filming to editing to posting to the customer engagement. And another quick and easy

engagement. And another quick and easy example here is just a software development agency. If we literally go

development agency. If we literally go back not even 2 years ago and you wanted to build an app like HubSpot or Salesforce or Cal.AI, these software

applications would have costed at least $20,000.

the person that you're hiring would have had to write a lot of their stuff by hand manually and the the delay of the product delivery would have taken a long time. Meaning that once the product was

time. Meaning that once the product was delivered, there wasn't even time for iteration. And that's what keeps the

iteration. And that's what keeps the market size the same because you can't sell your services to the car dealerships that are starting off. You

can't sell your services to the car washes that are starting off. But all of a sudden you can in the postAI era because your costs of delivering these labor services are much much lower than

before. So if at this point you're like,

before. So if at this point you're like, "Okay, Kev, I get it. The AI software service opportunity is the future, but where do I start?" Now, I want to give you a tip before I break down this

five-step road map. And that is to never look at where people are and look at where they started. Like when I was first learning AI development, AI no code, and all of this stuff, I was in

silence. I wasn't making content. I was

silence. I wasn't making content. I was

just on my computer learning 10 hours a day until I became proficient enough to then talk about it to the world. And so

this is my five-step road map. You want

to first learn AI agents, no code, and automations, right? Using platforms like

automations, right? Using platforms like naden, cursor, zapier, make.com. And to

make things easier for you guys, inside of the no code academy, I built a 30-day program to take you from building very simple automations to building very complex automations. And inside of this

complex automations. And inside of this program, you're going to learn all the terminology that is needed, all of the debugging that you might need, all of the API keys that you might need. And in

this way, hopefully it'll streamline your learning curve because what you're actually up against here is the learning curve. That is the actual competition

curve. That is the actual competition that you have. And so, the way that I see the future is that everyone's going to have an AI operating system. And so,

everyone's going to be creating AI operating systems. And so, all you really have to do is learn faster than the rest. And that's my goal. My goal is

the rest. And that's my goal. My goal is to help you learn faster than the rest.

And so after the 30-day program, you will be proficient enough to move on.

And once you do move on, you want to think about what is your niche? And you

can use the equation that I gave you guys earlier, right? So what is a labor that can be automated? What and and in what niche um can I dominate that doesn't have a monopoly? And in what

niche is there no enterprise company that is already dominating? Once you

answer these three questions, you can move on to step three, which is directly marketing. And that's where I gave you

marketing. And that's where I gave you guys another program. So, we have Kev's marketing master class. This teaches you the four proven marketing strategies to take your offer to market and actually convert and start generating clients.

Once you reach step three and you start generating clients, you start marketing, you start getting some interest, then you can actually productize and scale your offer, right? So, let's bring up the car wash example. What I would do is

I would learn AI agents in no code. I

would pick the car wash niche. I would

then I would then start marketing to that ICP and once I see what the actual pain points of that ICP are. What is

actually needed? What labor do they actually want, then I can turn that into a product and I can start scaling it.

And lastly guys, once you reach step five, you should really just become an industry-leading AI operating system.

When people think of your industry, they should think of your AI operating system. And in that way, you'll be

system. And in that way, you'll be generating leads without even thinking about it. And so that guys, in a

about it. And so that guys, in a nutshell, is how I'm seeing the newest AI agencies, the newest AI startups literally go from zero to a multi-million dollar valuated company in a matter of months. And this opportunity

is pretty shocking. When we think about companies growing this fast, in the past, it sounded like a fantasy. It

didn't sound real. But with AI, a lot of is now really, really possible. And

the AI service opportunity is going to be the pillar for the future economy. So

the faster that you learn this, the faster you get ahead. I hope you guys enjoyed.