Brand Voice: How to Make AI Scripts Sound Like You
AI writing sounds generic because it is trained on everyone. Here is how to feed it enough of you to fix that.
Summary — the short answer
- AI writing sounds generic because it is averaging everyone — adjectives like "witty" barely change the output.
- Voice is learned from examples. Twenty of your own lines beat any description you can write.
- Collect ten hooks, five CTAs, five plain-language explanations and a short do-not list.
- Three dials matter: formality, language mix, and claim strength.
- Refresh your examples monthly, because voice drifts as your audience changes.
Key facts
- Minimum useful examples
- 20 lines
- Most effective input
- Your own best hooks
- Dials that matter
- Formality, language mix, claim strength
- Refresh cadence
- Monthly
- Biggest mistake
- Describing voice with adjectives
AI-written scripts sound generic for a boring reason: the model is averaging an enormous amount of text written by everyone. Telling it to be "witty and conversational" does almost nothing useful, because those two words describe a million different writers, most of whom sound nothing like you.
Voice is examples, not adjectives
The fastest way to fix generic output is to hand over twenty of your own lines — real hooks you have said on camera, real CTAs, real asides. Models match patterns far more reliably than they follow descriptions, and twenty concrete examples carry more signal than a page of instructions.
This is also why the output degrades when you feed it competitor content. You end up with an average of you and them, which is a voice belonging to nobody.
What to collect
- Ten hooks from your best-performing videos, ideally with their retention numbers.
- Five CTAs in your natural phrasing, including how you actually say "link in bio".
- Five sentences where you explain something technical simply — this teaches vocabulary level.
- Three asides or jokes that are recognisably yours.
- A short do-not list: words you never use, claims you never make, formats you avoid.
The three dials that actually change output
| Dial | Low end | High end |
|---|---|---|
| Formality | Bhai-level casual | Presentation-ready |
| Language mix | Mostly English | Mostly Hindi |
| Claim strength | Careful and hedged | Bold and absolute |
Most creators sit at different points on these dials depending on content type. Educational videos usually need higher formality and lower claim strength; entertainment tolerates the opposite. Storing two voice profiles rather than one solves this without any extra effort.
Language mix deserves its own decision
Hinglish is not a percentage slider between two languages. Most Indian creators keep emotional words in Hindi and technical words in English, and a model will only reproduce that pattern if your examples demonstrate it. Feeding it formal Hindi and formal English separately produces something that reads like a textbook.
Auditing whether it worked
- 1Generate five scripts on topics you have already covered yourself.
- 2Read them aloud. Anything you would not say out loud is a voice failure, not a content failure.
- 3Mark every phrase that feels borrowed, and add its correct version to your examples.
- 4Regenerate and compare. Two rounds of this usually gets output to about 80 percent final.
- 5Repeat monthly with your newest best performers.
Where AI should not write for you
Personal stories, numbers you have not verified, and claims about outcomes you have not seen. A model will happily invent a plausible statistic, and a plausible statistic in a finance or health video is a genuine risk to your credibility and, depending on the claim, to your compliance with advertising standards.
Use generation for structure, options and speed. Keep authorship of anything that only you could know.
Frequently asked questions
How many examples are enough?
Twenty is a good floor. Beyond about fifty you see diminishing returns unless you are splitting into multiple voice profiles.
Will my scripts start sounding repetitive?
Only if your examples are repetitive. Include variety in your samples and refresh them monthly.
Can one brand voice serve a whole agency?
No. Build one profile per client. Averaging several brands produces exactly the generic tone you were trying to avoid.
Does brand voice affect captions too?
It should. Caption spelling, code-mixing and capitalisation are part of voice, especially in Hinglish where romanisation choices are highly personal.
Sources and further reading
- ASCI — advertising standards in IndiaGuidelines on influencer disclosure and claim substantiation for Indian creators.
- Google Search Central — helpful, people-first contentUseful framing for how AI-assisted content should still be authored by a human.
- VerbCraft: writing Hinglish that does not sound translatedWhy code-mixed voice needs specific handling.
- VerbCraft: the 4-part script structureThe structure your voice fills in.
- VerbCraft pricingBrand voice training is included on Creator and Studio plans.
Use this article elsewhere
Copy a structured brief for ChatGPT, Claude, Perplexity or Gemini — it includes the key points and the canonical link so the assistant can cite VerbCraft properly.
https://verbcrafts.in/blog/brand-voice-ai-scripts-sound-like-you
