The Advertised Price Is Never the Real Price
Most AI video tools advertise cost per clip — $0.50 for 8 seconds, maybe $1 if you want higher resolution. That number assumes every generation works.
It doesn’t.
Hit rates vary. Some clips come out perfect on the first run. Others take four or five attempts. On average, expect to run two or three generations for each usable clip.
This isn’t a workflow problem you can optimize away. It’s the business model.
Every platform selling AI-generated video on a credit system makes more money when your prompts fail, because failed generations still cost credits. The incentive isn’t to give you a usable clip on the first try. The incentive is to keep you generating.
After Effects Automation Scripts Charge Once, AI Video Tools Charge Per Retry
When you write an After Effects automation script or build a data driven animation template, the setup cost is front-loaded. You spend time building the logic, testing the expressions, making sure the template handles edge cases.
Once it works, it works every time. You can run it on as many assets as you need and the cost stays flat.
AI video generation flips that. There’s no setup cost because there’s no deterministic system. You describe what you want, the model interprets it, and you find out whether it worked only after the credits are gone.
If the first generation gives you a character facing the wrong direction or text that’s unreadable, you adjust the prompt and try again. That’s another set of credits. If the lighting’s wrong or the motion doesn’t match your brand’s pacing, that’s another generation.
You’re not paying for output. You’re paying for attempts.
On an internal historical piece, we needed roughly 15 clips. We ran 32 total drafts — running them at 720 first to save money before generating the final clips at 1080 (roughly 6 seconds each). There are other solutions if you care less about the outcome.
The Credit System Hides Iteration Cost Until You’re Already In
Most platforms don’t show you the per-generation cost up front. They sell you a credit bundle — and then reveal how many credits each generation actually burns only after you’ve committed to the platform.
A single 8-second clip might cost different amounts of credits on different services. You don’t know the real unit cost until you’ve already bought in.
Then the iteration starts. The first prompt gives you something close but not usable — maybe the pacing’s off, maybe the framing cuts off the product, maybe the AI hallucinated a logo that doesn’t exist. You tweak the prompt. That’s another charge. You try a different seed or adjust the style parameter. Another generation, another charge.
The platforms know this. The credit bundle model exists specifically because showing the real per-usable-clip cost would make the sticker shock visible before you commit.
Selling credits in bulk makes the individual burn feel smaller, even when the total spend is higher than hiring someone to build the asset once in After Effects.
What This Means for Production Teams Evaluating AI-Assisted Video Editing Workflow
If you’re running a production team and evaluating whether to add AI video generation to your workflow, the cost model changes the decision. The question isn’t whether the tool can generate video — most of them can.
The question is whether the cost per usable clip, including all the failed attempts, is cheaper than the alternative.
For some use cases, it still might be. If you need many variations of the same product shot and you’re willing to accept whatever the AI gives you without art direction, the per-clip cost even after multiple attempts might beat shooting and editing all versions manually.
But if you need specific framing, consistent brand treatment, or any level of control over the final output, you’re going to iterate — and iteration is where the credit model punishes you.
The other cost is time. Every failed generation is time spent waiting for the render, reviewing the output, adjusting the prompt, and waiting again. That’s labor cost on top of the credit cost, and it’s labor that doesn’t build any reusable asset.
When you build an After Effects template, the time investment creates something you can run again. When you iterate on an AI prompt, the time spent on failed generations produces nothing you can use later.
The platforms will tell you the tools are getting better, that future versions will have higher hit rates, that prompt engineering will improve your results. Maybe.
But the credit system doesn’t get cheaper when the models improve — it just means the platform can charge the same amount for less compute. The incentive structure doesn’t change.
About the Author
Kevin Baer is VP of Production at CGI Digital in Rochester, NY, with 26 years in video production and motion graphics.