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The AI Business Model That Will Create Millionaires in 2026

16m 34s3,162 palabras463 segmentsEnglish

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0:00

Okay, so right now there are three

0:01

mainstream ways to make money with AI.

0:04

The first one, building chatbots and

0:06

automations for businesses. That's a $14

0:08

billion market. Most people on YouTube

0:11

are telling you to start right here,

0:13

okay? The second one is building AI

0:16

software. The whole like software

0:18

product is SaaS. That's a $315 [music]

0:21

billion market. And then there is this

0:22

third tier, the one almost nobody is

0:25

talking about, a market worth over $3

0:27

trillion. And here's what's crazy, you

0:29

don't need to know how to code [music]

0:31

to capture it. I know because I'm doing

0:33

it right now. I run three businesses.

0:35

I've never written a line of code in my

0:37

life, and today I'm going to show you

0:38

the exact framework that makes this

0:41

possible. [music] I call it the AI first

0:43

framework. And by the end of this video,

0:45

you're going to understand why this is

0:47

the biggest business opportunity of our

0:49

generation. If you're new to this

0:51

channel, my name is Bogdan. I've been

0:52

building AI businesses for the past 2

0:54

years. I scaled my AI agency to $36,000

0:57

a month in revenue, and I've been

0:58

sharing everything I learned along the

1:00

way here on YouTube. I come from sales

1:03

and marketing, and the framework that

1:04

I'm about to show you is how I operate

1:07

all three businesses right now today.

1:09

Let me break down these three tiers

1:11

quickly because understanding where the

1:13

real money is, that kind of changes

1:15

everything about how you approach AI.

1:17

So, tier number one is the AI automation

1:20

agency. This is the entry level, a

1:22

roughly $14 billion market. So, you use

1:25

tools like N8N, make.com, Zapier to kind

1:28

of connect different software together

1:31

and automate workflows for clients. You

1:33

charge a setup fee, maybe a monthly

1:36

retainer. And look, it works. It's a

1:37

legitimate way to make money. The

1:39

problem here is that the barrier entry

1:42

is extremely low. Anyone can learn these

1:44

tools in a few weeks. Competition is

1:47

brutal, and your margins are capped

1:49

because you're still selling your time

1:51

technically. Every new client means more

1:53

hours or more people. Tier number two,

1:55

the SaaS market. So, now we jump to 315

1:58

billion. This is where you build

2:01

and sell monthly subscriptions. So,

2:02

instead of selling time, you're selling

2:04

a tool. But, here's the issue. This

2:06

space is like a complete red ocean

2:08

today. With Vibe coding, with an ability

2:11

to code using just plain English, pretty

2:13

much anyone can create a new product,

2:15

and obviously a lot of people are

2:16

building similar tools. And with AI

2:18

specifically, your margins are getting

2:20

compressed because every user prompt

2:22

costs you money in compute, right? You

2:24

pay for the AI for AI tokens. So,

2:26

traditional SaaS companies, traditional

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SaaS margins used to be 90%. Now, they

2:32

are closer to 60%. And tier number three

2:35

is the service industry, and this is

2:38

where things get really interesting.

2:40

Over $3 trillion. This is the money that

2:43

businesses spend on outcomes, not tools.

2:46

So, medical billing, recruitment,

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accounting, logistics, customer support.

2:50

And the model here is completely

2:52

different from anything on that list,

2:54

okay? So, stay with me here because the

2:55

third tier is where the entire game

2:58

changes. Most people on YouTube right

3:00

now, they are still telling you to go

3:01

start an AI automation agency. Like,

3:04

learn automation tools such as N8N,

3:06

make.com again, Zapier, start building

3:09

workflows for clients. And just 6 months

3:11

ago, I was saying the same thing. But,

3:13

here's what I realized since then, and

3:14

the shift just happened. The automation

3:16

agency model is getting squeezed from

3:18

both sides. On one side, the tools are

3:21

getting so simple that clients can just

3:23

do it themselves, and the AI will adapt

3:26

to us, to people, to clients. So, we

3:28

will be able to pretty much create new

3:30

tools without knowing all the AI tips

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and how to prompt, all of that.

3:34

Actually, I don't even bother learning

3:36

all those tips right now. I understand

3:37

that in a month or in a few weeks, AI

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tools will adapt to fit my style. Now, I

3:42

communicate with Claude Code, and it

3:44

understands me. I don't bother, you

3:45

know, structuring my prompts too much. I

3:47

just try to get to the bottom of it, and

3:50

it just adapts. So, for example, Zapier

3:52

now has AI that builds automation for

3:55

you. You don't need to know how to drop

3:57

all those nodes. Make has Copilot. The

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things that you were selling, like

4:00

connecting tools together, the tools are

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learning to connect themselves now. On

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the other side, and this is the the big

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one. There is a new layer of technology

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that makes those middle tier tools

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almost irrelevant for anyone who

4:13

understands what's happening right now.

4:16

Think about it this way. We are watching

4:17

the same pattern that plays out every

4:19

time technology leaps forward. So, the

4:21

middle gets crushed. The small players

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who were filling a niche, they either

4:26

get absorbed by the platform above them

4:29

or get replaced by something simpler

4:32

below them. So, medium-size companies

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like 5, 10, 20% automation shops, they

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are the ones that's getting squeezed

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right now. So, it's the same thing that

4:40

happened with retail when Amazon came to

4:43

be. So, Amazon didn't kill the corner

4:45

store and the mega mall. Amazon killed

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the mid-size retailer. The corner store

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survived by being hyper-local. The mega

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malls, they just adopted. But, the

4:56

middle gone. That's what's happening in

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AI services right now. And if you're

5:00

still building your business on, you

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know, tools that sit in that middle

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layer, you need to hear what comes next.

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Because what comes next and what I'm

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about to show you isn't just a different

5:10

tool. It's a completely different

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business model. So, what replaces it?

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What's like the model that actually

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captures that $3 trillion service

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industry? I call it the AI first

5:21

framework. And at its core, it's built

5:23

on one simple shift. You stop selling

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tools, you stop selling access to

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software, and you start selling

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outcomes. Not like, here's a dashboard

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for recruitment. No, here's a hired

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employee. Not, here's a billing

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software. No, here's a result insurance

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claim. Not, here's I don't know, an

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automation workflow. No, here's the

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result done. And this is what I call

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services as software. You deliver the

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outcome of a service, but the work is

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done by AI and by automations. Humans

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supervise. They steer AI in the right

5:56

direction. They don't execute. And the

5:59

engine that makes this possible, it's

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called Claude Code. Today's Claude Code,

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big players, they change. So, maybe we

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will have a better tool, maybe more

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updated tool. It will remain the same in

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its core, and you need to understand the

6:11

framework to use any of those tools.

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Claude Code is definitely the tool, the

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go-to tool today for me, for all my

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peers. We just automated 80% of our

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businesses, and now I can sell this AI

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transformation to other businesses, and

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this is what I call AI first framework.

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It is like a sellable system, but we

6:27

will discuss this later. Now, I'm not

6:28

going to do a full Claude Code tutorial

6:30

in this video. That's coming in the next

6:32

one, so make sure to subscribe to not

6:34

miss it. Here's what you need to know

6:35

and to what you need to understand right

6:37

now. Claude Code is not a chatbot, okay?

6:40

It's not another AI assistant that you

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ask questions to. It's a coding engine

6:45

that you talk to in plain English, and

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it builds like real software for you.

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You describe what you want, it plans it

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out, it writes the code, it tests it, it

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debugs it, and you just give it feedback

6:57

along the way just by talking to it. So,

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this is what I call steering AI. Here's

7:00

how I think about it. So, every few

7:03

decades, there is a leap in how humans

7:05

talk to computers. We went from wiring

7:07

circuits to punch cards to assembly

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language to C to Python. Each step made

7:13

it easier, but the jump that we made

7:15

just recently is the biggest one. We

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