Train AI on Your Brand Voice or Watch It Sound Like Everyone Else

Lilach Bullock put it bluntly in a recent piece on scaling content with AI: "A voice document is not a list of adjectives." She points out that most teams skip the actual documentation step, then wonder why six months of AI-generated content reads like it came from a generic marketing robot (https://www.lilachbullock.com/how-to-keep-your-brand-voice-when-you-scale-with-ai/).

She's right. And the cost isn't just bland content. The cost is you stop trusting the tool entirely.

Here is the opinion: AI brand voice training is not optional. It is the difference between a content engine that scales your voice and one that slowly erodes it.

What Generic Actually Looks Like

You have seen the output. Maybe you have generated it yourself.

"We are thrilled to announce..." "In today's fast-paced world..." "This game-changing solution..."

The cadence is off. The enthusiasm feels forced. The transitions are too smooth. It reads like someone took all the marketing emails from the last decade and averaged them together.

That is exactly what happened.

Large language models are trained on the internet. They default to the median. Without intervention, they produce the most statistically probable marketing language. Which is, by definition, average.

Your brand voice is the opposite of average. It has edges. It has opinions. It has phrases you use and phrases you would never use.

The Voice Document Nobody Builds

Bullock's other article walks through the mechanics of training AI on your voice (https://www.lilachbullock.com/how-to-train-ai-on-your-brand-voice-so-it-sounds-like-you/). The process is not complicated. But almost nobody does the upfront work.

A voice document is not "friendly, professional, and approachable." That describes every SaaS company on LinkedIn.

A voice document includes:

• Actual phrases you use: Not brand values. Real sentences from your emails, your sales calls, your best-performing posts.
• Phrases you never use: If "leverage" makes you cringe, write that down. If "synergy" is banned in your Slack, document it.
• Sentence structure patterns: Do you write short, punchy sentences? Do you use parentheticals? Do you ask rhetorical questions?
• Tone markers: How do you handle skepticism? How do you express enthusiasm without sounding like a press release?

You need examples. Dozens of them. The best voice documents are messy. They are full of copy-pasted Slack messages and email snippets that made you laugh or made a customer reply.

The Training Step Most Teams Skip

Here is where it breaks down.

Most teams write a brand guidelines PDF once, during a rebrand, and never look at it again. Then they ask ChatGPT to "write in our brand voice" without ever showing the model what that voice sounds like.

The model guesses. It guesses "professional B2B software company" and gives you the same output it gives everyone else.

The fix is simple but not easy. You feed the model your voice document before every content request. You paste in your best examples. You tell it explicitly what to avoid.

Then you iterate. The first draft will be wrong. You correct it. You tell the model: "This sounds too formal. We say 'use' not 'utilize.' Try again."

Over time, you build a system. Maybe it is a custom GPT with your voice baked in. Maybe it is a prompt template you refine. Maybe it is a Claude project with your best writing samples attached.

The tool does not matter. The training does.

Why This Matters for SMBs

Large enterprises have brand teams. They have style guides and approval workflows and people whose entire job is protecting the brand voice.

You do not. You are the founder or the marketing lead or the operator running a lean team. You are the brand filter. Every piece of content passes through your edit.

AI can scale your output. But without voice training, it scales the wrong version of you. It scales the generic version. The version that sounds like a press release generator.

Your customers notice. They may not articulate it as "brand voice inconsistency." They just stop reading. They stop replying. They tune out.

Voice training is how you keep them.

A Practical Starting Point

If you have zero voice documentation, start here:

1. Pull your last 10 emails to customers. The ones where you were not trying to sound like anything. Just you solving problems.

2. Pull your 5 best-performing LinkedIn posts or blog pieces. The ones that got replies.

3. Write down 10 phrases that make you roll your eyes when other companies use them. Be specific. "Unlock potential" counts. "We're passionate about" counts.

4. Write down 5 things you actually say in sales calls. The phrases that make prospects laugh or lean in.

That is your raw material. That is what you feed the model.

Then you test. You ask for a draft. You compare it to your real writing. You correct the model. You try again.

The Alternative Is Not Scaling

You can skip this. You can prompt generically and edit heavily. That works for a while.

But the moment you try to scale, the cracks show. You hire someone to run content. They prompt generically. The output drifts. Six months later, your content library reads like it was written by a committee of marketers who never met you.

Bullock's point holds: almost no one does this work. That is the opportunity.

Your competitors are generating generic content right now. Their AI sounds like everyone else's AI.

Yours does not have to.