Can You Really Make Money with AI Vids on YouTube?
A Detailed Experiment and Tutorial
I’ve seen tons of YouTube videos promising $10k to $100k per month using AI. These videos usually sport clickbait titles and flashy thumbnails promising easy money, but there's often a glaring lack of evidence to back up their claims.
And it’s not only AI Marketers who promote their products for easy money. Some AI agencies promise huge profits too, claiming they can boost returns by 300% or more. Of course, many of these claims are exaggerated.
Intrigued yet skeptical, I decided to dig deeper and found a YouTuber who actually put this to the test. His case study was eye-opening, and I couldn’t wait to share it with you.
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The AI Challenge
The YouTuber I found started a simple experiment. The objective? To see if an AI could run a YouTube channel better than he could.
To do this, he created two channels: one fully automated using AI and another where he manually crafted each video. On both channels, he posted videos of “Quotes of the Day” and “Interesting Facts” formats.
The AI Toolbox
To create the AI channel, he used a combination of tools:
ChatGPT to generate video scripts.
11 Labs AI for text-to-speech voiceovers.
Pexels API for fetching stock footage.
Vosk for subtitle generation.
FFmpeg for video editing.
The idea was to automate as much of the process as possible, including the entire editing workflow.
The idea was to automate as much of the process as possible, including the entire editing workflow.
The Experiment: AI in Action
He started by asking ChatGPT for video ideas. After some testing, he settled on two styles: "Quote of the Day" and "Random Fact Compilation."
For the AI channel, he:
Asked ChatGPT for thought-provoking quotes.
Fetched beautiful background footage from Pexels.
Used 11 Labs AI for the voiceover.
Created subtitles using Vosk and edited everything with FFmpeg.
The final product? A soothing video with an inspirational quote, serene background visuals, and calming music, all generated by a single Python script.
For the Human Channel videos, he:
Sourced interesting facts from ChatGPT.
Used Pexels for relevant stock images.
Combined these with gameplay footage from "Only Up" to keep viewers engaged.
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Manual vs. Automated: The Showdown
On the manual channel, he replicated the same types of videos but did everything himself. He gathered quotes and facts from the internet, did the voiceovers, and edited the videos manually. This setup allowed for a direct comparison between AI-generated and human-created content.
Uploading and Initial Performance
Both channels got off to a slow start. By the end of the first week, the human channel was clearly outperforming the AI channel, boasting over four times as many views and subscribers. The main reason? A fact compilation video on the human channel that went viral, amassing over 10,000 views.
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Adjusting the Strategy
Realizing that AI's strength lies in its ability to churn out content with minimal effort, he adjusted the AI channel’s upload schedule to three videos per day while keeping the human channel's schedule unchanged. This allowed the AI channel to leverage quantity, a key factor in gaining traction on YouTube.
Comparing Results
Learn about the experiment’s results and gain insights below
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