How to Keep AI Drafts on Brand: A Review Process

To keep AI drafts on brand, give every tool the same written record of your voice and facts, keep a short list of banned words and sentence shapes, run an automated check for those before a human reads the draft, and have one person read for facts and tone last. Put most of the effort before the draft gets written. Editing afterward is slower and misses more.

Why AI drafts drift off brand

Three people on your team use three AI tools. Each pasted in a different piece of the brand guide, or none. Each tool fills the gaps with the most statistically average phrasing available, which is why so much AI copy sounds like the same cheerful stranger.

So the tools aren’t ignoring your brand. Nobody gave them the whole thing.

Step 1: write the voice down where tools can read it

A PDF brand guide written for designers won’t do it. You need a plain text record that says how you talk, with examples. Phrases you use. Phrases you’d never use. Who you’re talking to. Facts that must be right: names, numbers, service area, what you don’t promise.

Every tool and every person draws from that one record. We call ours Groundwork. The general term is an AI knowledge base.

Step 2: keep a banned list, and ban shapes as well as words

Word lists are the easy half. Ours has a few dozen entries, the usual AI favorites among them.

The harder half is sentence shapes. The “it’s not this, it’s that” contrast. Lists that always come in threes. The closing paragraph that restates everything. The opener that compliments the reader. These read as machine-written even when every word is clean. Write them down with an example of each.

Step 3: let a machine do the first pass

People are bad at catching the fortieth em dash. Software is great at it.

We don’t allow em dashes anywhere, and we keep a list of retired claims that must never reappear. So our website build runs a search for every one of them, and the results go into the change request before anyone approves it. The week this was written, that check covered dashes, five retired phrases, a retired product name, and any dollar figure on pages where we don’t publish prices. It takes seconds and it’s more thorough than a tired reviewer.

You can do a simple version with find-and-replace and a checklist. What matters is that the mechanical errors are gone before a person spends attention on the draft.

Step 4: one human read, for the things machines miss

Now a person reads, and only for what needs judgment.

Is every fact right? Would we say this to a client’s face? Does it take a position or hedge everything? Does it sound like one of us wrote it? We read it aloud. If a sentence sounds like an agency talking, it gets rewritten. If it sounds like someone describing their workday, it stays.

Step 5: feed the misses back

Each time the reviewer catches something new, it goes into the record or onto the banned list. After a couple of months the drafts arrive cleaner and the reviews get shorter.

Where this breaks down

It fails when the record goes stale. It also fails when each person maintains their own private version of it. Give the record one owner and one location. And whoever hits send is still responsible for what goes out.

AI for communications teams · How to spot AI-written content

Questions we get

What’s a practical review process to catch off-brand phrasing in AI drafts?

Ground every tool in one written voice record, maintain a banned list of words and sentence shapes, run an automated search for those before human review, then have one person read for facts, tone, and position. Add each new miss to the record.

What steps ensure brand consistency across AI tools?

Use a single shared knowledge record that every tool reads, instead of pasting guidelines into each tool separately. Give that record one owner and update it whenever a fact or a phrase changes.

Can AI check its own drafts for brand voice?

Partly. It’s reliable for mechanical rules like banned words and formatting. It’s less reliable for judging whether a claim is true or a tone is right for a specific client, so a person should make the final read.

How long should an AI content review take?

With upstream grounding and an automated first pass, a few minutes per piece. If reviews are taking much longer than that, fix the record the tools draw from.

What is Groundwork?

Groundwork is MKTNG’s name for the structured record of a company, including its voice, that every tool and agent reads from.