How to make money on neural networks in 2026 through Reels and Shorts
A step-by-step plan on how to make money on neural networks: from the first video to the first advertisers
If you look at the content market in 2026, it becomes obvious: today, it is not only experts, bloggers, and companies who are starting to make money. Increasingly, good money is being earned by people who have learned to quickly create entertainment content through a neural network and gather an audience around it. What is most interesting is that you no longer need production, a camera operator, a scriptwriter, or a designer to start.
Let's take a simple example. Suppose you launch a blog about cars. But instead of the usual reviews, you start making mini-cartoons from the perspective of the car itself. For example: “Today I changed my own oil and saved my owner 8 thousand rubles”, “The car repair shop wanted to rip me off for 15 thousand for repairs. Now I'll show you how I solved the problem for 900 rubles”
Such a format works for one simple reason: it is unusual. When the audience sees yet another person talking about cars, it is already familiar content. When the car itself starts talking from the screen, attention is automatically captured.
To create such videos today, a few strong AI models are enough. You generate a car character, define its personality, voice it over, and publish short videos every day. At the start, your goal is not money at all. First, you need to get your first thousand followers. Because roughly after reaching the 1,000–1,500 people mark, the next stage of the game begins — advertisers start to appear.
And this is where most beginners make a mistake. They wait for brands to find them on their own. In practice, it works the exact opposite way. The creator usually looks for the first clients themselves. The easiest way is Google Maps. You open the map of your city and start collecting contacts of car repair shops, tire services, car washes, auto parts stores, and detailing centers.
Next, you write a short and clear proposal:
“Hello. I run a car blog featuring an AI car character. The average reach of the videos is 15–20 thousand views. I can make a native video about your service in the format of a story from the perspective of the car. This format usually gets a high percentage of completion rates and saves. An example of a video is attached. I am ready to make a free test video for your task. If you are interested, here are my contacts.”.
It is important to understand one thing. You are not selling advertising, but the attention of the audience. Today, it is becoming one of the most expensive resources on the market. Especially if your content stands out from what everyone else is doing.
Where it is best to develop such a blog
The best part is that the exact same video can be published on several platforms at once. One character. One script. One generation. And several traffic sources all at once.
How to make money on neural networks in 2026: money, advertisers, and own courses
Now let's talk about figures. Because these are exactly what usually interest people after the question "does this even work?". The economy in the AI content market right now is quite clear. The larger the audience, the higher the cost of ad integration.
The average picture looks something like this:
And this is just direct advertising. Then additional sources of income start to connect: affiliate programs, own digital products, paid communities, consultations, and mini-courses.
The last option is growing especially fast now. Because the market is literally flooded with people who want to figure out AI but do not want to spend months experimenting. When should you create your own course? Usually after the first case studies appear. That is, when you have already gathered an audience and can show: here is my channel, here are my results, here is my reach, here are my advertisers. At this moment, trust appears. And trust always sells better than beautiful landing pages.
As for the cost, in 2026 most mini-courses on AI content cost from 3,000 to 25,000 rubles. A course can consist literally of 5–10 lessons. The main thing is not the volume, but the result and quick application in practice.
For example, courses can be named like this:
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“How to create an AI series over a weekend”
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“How to gather 10 thousand followers through AI Reels”
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“How to make Shorts through a neural network in 15 minutes”
It is these kinds of products that sell best right now. Because people are not buying knowledge, but a shortcut to their first income. But with your example in the blog, you must first inspire their trust — without this, nothing will work.
How much you can make on neural networks
Will every author earn such amounts? Of course not. But for the first time, the market allows a single person to launch a content production workflow on par with a small studio, practically without a team.
A digital aggregator instead of five services
Now for the most interesting part. Because this is exactly where many people lose a huge amount of time. Imagine that you decided to create a regular 40-second Reels. First, you need to come up with a character. Then open one neural network and generate the character. If you don't like the hero, generate them again. Then open another system and animate them. Then look for a service for the voiceover. Then do the video editing separately. Then manually compile the scenes. Then fix the errors.
If you do everything the old-fashioned way, as people still did in 2025, one video can easily take several days. Especially if you need to show the car from all sides, open the hood, show the engine, replace parts, and create decent dynamics.
That is why the market is gradually shifting to a new approach — to a single storyboard, where the entire project is assembled in one workspace. This is exactly how neural network aggregators from Russian developers operate today.
Instead of a set of disparate tools, a single system emerges. You create a character, immediately see the storyboard, instantly animate scenes, change dialogues, add voiceovers, and assemble the finished video. If you don't like the result, you simply rewrite the prompt and send the scene back for reworking. No exporting. No downloads. No endless tabs.
A good example of such an approach is the Doitong platform. It is important to understand that this is not just another new AI that generates according to its own rules. On the contrary, it is an aggregator of neural networks. Familiar AI models are already working inside: Nano Banana, Midjourney, VEO, and others. They simply work all together like a big team in an open-space office. Therefore, the result remains familiar and predictable, while the speed of work increases significantly.
In fact, it turns out that instead of five or six separate services, you get a single workspace where you can create a character, animate an AI hero, make animations, assemble a series, voice over a video, and edit a clip. Moreover, it is entirely realistic to assemble a full-fledged Reels in 10–15 minutes once you have all your processes set up on the storyboard.
That is why the market is gradually moving toward orchestrator platforms. It is faster and cooler. And while until recently a creator assembled a video like a construction kit from four different programs, today a good digital aggregator does most of the technical work itself.
And the author can finally do what they are supposed to do — come up with stories that people want to watch.
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