How to Write an AI Video Script People Watch to the End

Ask any AI model for a “video script about our new feature” and you get the same thing back, almost word for word: “Introducing the all-in-one solution that helps you…” It reads like release notes with a voiceover attached, and most viewers are gone before the second sentence. That is not the model failing. It is doing exactly what it was asked: write about the feature. Nobody asked it to write about the person watching.

The problem with AI-written scripts

A feature brief describes what was built. A script that holds attention describes what changes for the viewer. Those are different documents, and feeding the first one straight into a prompt produces exactly the generic, feature-first copy everyone has learned to skim past. The fix is not a cleverer prompt — it is changing what goes in before you ask for anything.

The three-question brief

I actually run a full nine-section product video brief with Product Marketing Managers before a script starts — goals, ICP, positioning, tone, the works. But before I ask AI for a single line, it is three questions from that brief that do the real work:

• What problem is this audience actively trying to solve right now? Their pain, not your solution yet — and the specific friction, not the category of problem.
• What frustration or risk should open the video? The hook. What does this audience want to avoid at all costs?
• What is the #1 takeaway, if they remember only one thing? If the answer takes more than one sentence, it is not ready yet.

Getting five hooks and keeping one

With that brief as context, I ask for five different opening lines, not one. Most AI output regresses to the mean on the first try; asking for variation and then choosing is far more reliable than asking for perfection once. Four of the five get thrown away. That is normal, and it is faster than editing one mediocre line into a good one.

What stays human

The one decision I never hand over is which single idea the video is built around. AI is good at generating options and reorganizing a mess into a structure; it is not good at knowing which option matters most to a specific audience at a specific moment, because that judgment comes from sitting in on customer calls and watching which features people actually struggle to explain to their own teams. Handing that decision to a model flattens every video into the same shape.

A before/after example

This is from a real feature launch video I worked on, for GetResponse's AI Course Creator. First pass, straight from the feature brief:

“Introducing our new AI Course Creator, the all-in-one solution that helps you build and sell online courses faster than ever.”

Generic, feature-led, could be about any product in the category — nobody watches past the second sentence. Running the three-question brief first changed the opening line entirely:

“Staring at a blank course outline, not sure where to even begin? That blinking cursor is the hardest part of building a course — and it's the first thing AI Course Creator gets rid of.”

Same feature, same product, same length. The only thing that changed is where it starts: not with the product, but with the exact moment of friction the viewer was in five seconds before they clicked play.