Some of the most underrated AI Business Ideas right now don’t look like “businesses” at first. They look like weird, fast, addictive videos.
Think: a plain empty room turns into a luxury bedroom in seconds, the floor becomes a beach, seashells appear, epoxy gets poured, furniture pops in, then the camera does a slick pan at the end. It’s the kind of short you watch twice because your brain goes, wait… how did that happen?
Behind the scenes, creators are spotting what’s trending, copying the format quickly, and using a small set of AI tools to publish time-lapse style Shorts that can rack up tens of millions of views. And once a channel meets monetization requirements, the math can get kind of wild.
The “viral AI animation” business model (and why it’s blowing up)
The model is simple to explain, even if the output looks insane:
A creator notices a viral Short trend, then makes their own version of it using AI image generation plus frame-to-frame animation. Right now, one of the biggest trends is time-lapse renovation videos, especially “home glow-up” clips where the changes are dramatic and a bit unrealistic on purpose.
A few examples floating around in the space show how fast this can move:
One new channel (only a few weeks old at the time it was reviewed) posted a time-lapse style clip of a flooring renovation where an epoxy floor is “made from roses.” That single Short passed 50 million views.
Another fresh channel (around a month or two old) leaned into the trendy bedroom renovation niche with a clip where a room transforms into a bedroom with an aquarium on the floor. That one passed 60 million views, and the channel was pulling in roughly 1 to 4 million views per day during the spike.
There are also creators publishing 10-second Shorts that are not one animation, but multiple small clips stitched together. One example in the flooring niche crossed 200 million views in about a month, mostly by chaining several mini “steps” into one satisfying timeline.
Before AI, making animation like this was expensive. If you weren’t an animator yourself, you were hiring someone, and paying something like $500 to $1,000 per video wouldn’t be shocking.
Now the production cost can drop to cents per video (depending on the plan you use), because the workflow is basically: generate frames, animate between them, then speed them up so it feels like a time-lapse.
The truth about YouTube monetization for AI videos
A lot of people avoid this whole category because they’ve heard a rumor: “YouTube doesn’t monetize AI videos.”
That rumor keeps spreading, but it’s not a blanket rule like people think.
One quick way to sanity-check whether an AI-heavy channel is in the YouTube Partner Program is to look for partner-only features that some creators enable:
- A “Join” button (channel memberships)
- A “Super Thanks” button (donations on videos)
If you see those, the channel has to be partnered. If you don’t see them, it doesn’t prove anything, because creators can leave those features turned off.
This monetization panic really took off after a monetization eligibility update announced around mid-2025, when people started interpreting it as “AI equals demonetized.” In reality, the update was more about reducing spam and mass-produced low-quality clutter than banning a tool.
If you want a readable breakdown of what that policy chatter was about, this article summarizes the intent pretty clearly: YouTube’s policy shift targeting mass-produced “AI slop”. There are also compliance-focused writeups aimed at creators trying to stay safe: AI monetization policy and practical compliance tips.
What Shorts RPM can look like (and why views matter so much)
Most creators using this strategy publish YouTube Shorts. Shorts RPM varies, but ranges like $0.10 to $0.50 RPM get discussed often, with many creators landing around $0.20 to $0.30.
Here’s what that means in simple numbers.
| Shorts views | RPM estimate | Rough revenue range |
|---|---|---|
| 100,000,000 | $0.10 | $10,000 |
| 100,000,000 | $0.30 | $30,000 |
| 100,000,000 | $0.50 | $50,000 |
So when you see a brand-new channel pull 100 million views in a few weeks (it happens), even conservative RPM math can land in the “serious side income” zone fast.
The 4-tool workflow behind these AI time-lapse Shorts
What’s funny is, the workflow isn’t complicated. It’s more like a little assembly line.
You use:
- a chatbot to brainstorm ideas
- an image generator to create a “before” and “after” frame
- a frame-to-frame animator to create motion between those frames
- a free editor to stitch clips and speed them up into a time-lapse
Here are the exact tools referenced in the workflow:
- ChatGPT for brainstorming video concepts
- Gemini for AI image generation
- Kling referral link with bonus credits
- Clipchamp video editor
On the image side, Google has shared updates about the underlying image model options over time, including Imagen releases that power parts of the ecosystem. If you’re curious what’s happening under the hood, this is a solid reference: Imagen 3 availability in the Gemini API.
If you want more broader, non-YouTube options for AI income paths too, this internal roundup pairs well with this idea: 5 best AI business ideas for 2026
Step 1: Find a trend, then use ChatGPT like a creative partner
This part isn’t automated, and that’s the point.
The “edge” is noticing what your feed keeps showing you. Time-lapse renovations. Wacky room transformations. Flooring makeovers. Anything that’s oddly satisfying and easy to understand with the sound off.
Once you’ve got a niche, a chatbot helps you move faster, because it can throw 20 ideas at you in seconds.
A simple prompt pattern that works well is:
Describe the trend clearly, then ask for variations that fit the same format.
For example, you might tell ChatGPT you’ve noticed “crazy epoxy floor renovations presented as time-lapses,” and ask it to brainstorm unusual floor concepts. Then you pick one idea you like (say, a beach theme), quote that part back, and ask for a bunch of specific add-ons that match the scene (sand, shells, color palette, decor style, stuff like that).
One small but important mindset shift here: the chatbot isn’t the boss. It’s more like a writer friend you can ping at 1 a.m. who never gets annoyed. You still decide what’s good and what’s trash.
Step 2: Generate your “before” and “after” images in Gemini (Nano Banana Pro)
Next you create the raw material for the animation.
The approach used here is:
- Generate a clean starting frame (the “before” image).
- Create a modified ending frame (the “after” image).
- Then animate between them.
The image tool used in this workflow is Nano Banana inside Gemini (there’s a free tier and a Pro tier). One practical detail mentioned: Pro images do not have watermarks, which matters if you’re publishing.
The steps look like this in real life:
First, generate an empty room frame in a vertical format (the workflow referenced a mobile-friendly 9:16-style setup). If the image is too dark, you don’t restart from scratch, you just ask for a small edit like “make it lighter, keep shadows neutral.” That kind of small tweak is usually easy.
Then you start a new chat, upload the before image, and request the change that becomes your after image.
Example: “Add sand to the floor.” Download that result. Now you have the two frames you need.
From here on, you’re basically building a time-lapse in small steps, like stacking dominoes.
Step 3: Turn frames into animation clips with Kling (frame-to-frame)
Kling is the frame-to-frame animator used in this workflow because it’s relatively beginner-friendly and priced cheaper than some alternatives.
The setup is straightforward:
You create a new video, drop your start frame and end frame into the timeline slots, then write a prompt telling it what should happen between those two images.
You can usually keep audio generation turned on, and for simple changes, a 5-second clip is enough (and cheaper than 10 seconds).
One thing that gets brushed under the rug sometimes: frame-to-frame tools can produce weird little glitches. Hands warp, objects melt, shadows jump. It happens.
The trick is you’re going to speed these clips up later, so the imperfections often become hard to spot. At time-lapse speed, the brain forgives a lot.
If you want an extra reference on Kling’s feature set and controls, here’s a walkthrough style guide: step-by-step Kling Motion Control guide.
What it can cost per video (real numbers, not vibes)
Kling isn’t free, and the workflow mentions something important: free tools generally don’t come with a commercial license for this kind of generation (at least, not in a way you should blindly rely on).
The pricing example given compared two common plans:
- A lower plan around $7 for the first month with 990 credits
- A higher plan around $26 with 4,500 credits
If most videos use 4 to 7 clips, and each clip costs 25 credits, you can estimate cost per finished short roughly like this:
- With 990 credits, you might create about 5 to 9 videos, so roughly $0.78 to $1.40 per video
- With 4,500 credits, cost can go as low as about $0.58 per video depending on clip count
That’s the core “business unlock.” You’re not gambling $500 on a single animation anymore.
Step 4: Build a full time-lapse by chaining multiple clips (before becomes the next before)
The viral Shorts in this niche rarely rely on one single animation. They’re usually a chain of mini-scenes.
Here’s the exact pattern used:
Your last “after” image becomes the next scene’s “before” image.
So you might build a beach bedroom renovation like this:
Scene 1: Empty room becomes a room with sand on the floor
Scene 2: Same room, now turquoise painted walls appear
Scene 3: Seashells get scattered across the sand
Scene 4: Clear epoxy is poured over the sand and shells
Scene 5: Beach-themed bedroom furniture is added
Each one is its own tiny frame-to-frame clip.
Optional final touch: a camera pan clip
A very common format beat is ending with a camera move. Instead of another “change,” it’s just a pan that reveals the final room.
The workflow here is simple: upload the final finished image into Kling by itself, then use preset pan options (like “boom up and push forward,” slowed down a bit). Generate that as the last clip.
It adds polish without extra design work, which is… honestly, kind of perfect.
Step 5: Stitch, speed up, and hide imperfections in Clipchamp (free)
Once the clips are generated, the time-lapse effect is mostly created in the edit.
Clipchamp is the free editor used here. You upload clips, drag them into the timeline, and then adjust speed clip-by-clip.
Here’s the key idea: speed hides problems.
If one clip has more weird AI motion, push it faster. If another clip looks clean, let it breathe a bit.
A sample speed mix used looked like this:
- Clip 1 at 2x to 3x
- Clip 2 faster (because it had more oddities)
- Clip 3 faster again
- Clip 4 slower (less oddities)
- Clip 5 fastest (most oddities)
- Final pan clip at 1.5x (since it’s smooth)
Then export at 1080p.
If you want the official guide for the exact speed controls and time-lapse style edits, Clipchamp has a clear tutorial: how to make a time-lapse video in Clipchamp.
A quick side path: using AI images for print-on-demand (ebook and course links)
The same image generation tool used for these Shorts can also be used for product designs, especially print-on-demand.
The resources referenced alongside this workflow were:
There were also a few linked case study videos showing that business model in practice:
- how a 1-person AI business was built
- how money is being made with AI
- passive income sources breakdown
- selling AI art for 90 days experiment
- from $0 to $3k per week in a new Etsy store
That’s a different lane than YouTube Shorts, but the “core skill” overlaps: getting good at prompts, taste, iteration, and making outputs people actually want.
If you want a fast, zero-budget style walkthrough on building an AI offer quickly, this internal guide is also worth bookmarking: build AI business in 24 hours with $0
My personal experience (and what I learned trying this workflow)
When I first tried this, I assumed the hard part would be the tools. Like, I thought I’d get stuck inside settings menus, or credits, or some annoying export issue.
Nope. The hard part was picking a concept that’s simple enough to read in 10 seconds.
The best results came when I stopped trying to be clever and started thinking like a viewer who’s half-asleep scrolling. Big changes. Clear before-and-after. No clutter. I also learned that my “perfect” prompt usually wasn’t the winner. The winner was the second or third run where I asked for one boring fix, like brighter lighting, fewer objects, cleaner walls.
And yeah, the weird AI glitches happened. A lot. But speeding up the rough clips really did hide most of it. I had one scene that looked almost broken at normal speed, at 4x it suddenly felt like a jumpy time-lapse, not a mistake. Funny how that works.
The biggest surprise was how much the workflow rewards repetition. Once you have the first two scenes done, the rest feels like, okay, same dance again. Upload, edit, animate, download. It’s not “easy money,” but it is a repeatable system, and that’s the part I didn’t fully appreciate at the start.
Conclusion
This time-lapse Shorts model is one of those AI Business Ideas that feels obvious only after you see the workflow. Spot a trend, generate before-and-after frames, animate in small steps, then edit fast enough that it becomes satisfying instead of glitchy.
If you try it, keep it simple for your first run: one room, a handful of changes, and a short final pan. Then publish, review what people actually watch, and iterate from there.