How to Keep AI Images On Brand.

To keep AI images on brand, write the brand down as rules a model can follow and a reviewer can check, then run every image against those rules before it ships. Most teams skip the first half. They hand the tool a guidelines PDF and a few mood words, and the output drifts with whoever’s prompting that day.

I built this system for a major visual platform’s content department, then trained the whole team to run it. It came down to seven steps.

I’m Drew Brucker, an AI Creative Consultant. Through Brainchild, I build the brand spec and review gate for brand teams that use AI images.

1. Write the brand spec in checkable terms

Your designers know what “premium” and “warm” look like because they carry years of context about your brand. A model carries none of it. So translate the mood words into things you can point at: hex codes, lighting direction, color temperature, how people sit in the frame, what the rooms and streets look like.

Read every line back and ask whether a reviewer could check it without pinging anyone. If they’d have to ask, rewrite it.

2. List what the brand never does

On that engagement the anti-pattern list did more work than the rules. Stock-photo flatness, oversaturated backgrounds, hands holding phones at eye level, the glossy plastic skin that screams AI. Whatever “too AI” looks like for your brand, write it down.

People agree on what’s wrong much faster than on what’s right. The model needs both lists anyway.

3. Build prompt recipes per use case

A landing page hero and a social tile have different jobs, so they get different recipes. Each one holds the subject framing, scene rules, composition defaults, the references to pull, and what to avoid. Someone who joined last week should get an on-brand result on day one by running the recipe, with zero history behind it.

Write the recipe around the outcome and list the tool settings underneath. When a better model ships you swap the settings and keep everything above them.

4. Lock dimensions and safe zones before you generate

Set the aspect ratio for each placement first, then mark where the headline and logo sit and where the platform’s own buttons will cover the frame. An image composed for one shape and cropped into another is how approved work quietly goes off brand on the way out the door.

5. Add text and logos after generation

Generate the image clean. Drop in the real logo file and set the type in your design file, in the brand typeface. Image models still drift on small type and exact logo geometry, and one warped wordmark is enough to sink the whole asset in review.

6. Run every image through a yes-or-no gate

Six checks, same order, every image:

1. color correct
2. logo correct
3. safe zones clear
4. dimensions right
5. text legible
6. no artifacts

Yes or no only. Anything stuck in between goes back for another pass. A creative director should be able to sign off on whatever clears all six without opening the prompt.

7. Train the team on the system and keep it current

The spec and recipes only hold if the people using them can judge output and know when to scrap it and start over. Typing the prompt is the smallest part of that. But it’s where most trainings spend their time.

Then give the whole thing one owner. New models will keep shipping and the brand will keep moving, and someone has to update the recipes when they do. The gate is the one piece nobody touches.

Where to go deeper

Field Note 03 covers what goes inside the brand spec and why most AI visuals feel off to begin with. The case study shows the full system this came from, down to the two custom agents and the course every new hire takes.