Finding 1
Buyers looking for a designer to license from almost never heard her name. She was named in 1% of the assistants' answers and 0% of Google's AI answers.
Case study · Design licensing · United States
Described well, and almost never named
An independent designer licenses her artwork to brands and sells design files. The question was whether AI assistants send buyers her way.
CategoryDesign licensing and design files
MarketUnited States
Where we lookedAI assistants and Google's AI answers
FieldworkAugust 2026
1%of the assistants' answers named herWhen buyers looked for a designer without a name in mind
0%of Google's AI answers named herThe same searches, on Google
97%of what the assistants said was rightWhen they could read about her
01What she believed
She thought the problem was how she was described.
She believed there was little public material about her.
She believed the brands she had worked with kept quiet about working with her.
And she believed that if she had a problem with AI assistants, it was in how they described her.
02What surprised her
Her description was never the problem.
Getting into the answer was.
Brands she had worked with credit her in public, and some of that material was more substantial than she knew. The study found it before she did.
Almost never in the answer
Share of the assistants' answers that named her, when buyers looked for a designer
Source: study data, August 2026
03What we found
Right about her when they can read her.
Absent when they cannot.
Six findings, each with the exhibit that shows it.
71%
of the praise for her offer was an echo
One assistant repeating her own description word for word. The assistants that read her offer themselves described it differently.
Finding 2
When she was named, she was described well. Where an assistant could read about her, it got her right 97% of the time.
Reading her beats remembering her
Share of claims about her that were wrong
An assistant that read her site3%
An assistant working from memory45%
Another assistant working from memory51%
Source: study data, August 2026
Finding 3
Her two kinds of buyer meet different winners. People buying design files are sent to a marketplace. Brands looking to license are sent to named individual designers, who take 25% of those recommendations against 19% for marketplaces. One fix would not serve both.
Two buyers, two winners
Who gets recommended when brands look to license
Share of all recommendations, by kind of supplier
Named individual designers25%
Marketplaces19%
Licensing agents14%
Design studios13%
Stock libraries11%
Trade shows7%
The designer herselfunder 1%
Source: study data, August 2026
Finding 4
The assistants repeated an old fact about her that was no longer true. The biggest source was her own site: the words on her about page said one thing, and the data behind the page said another.
One page, two stories
What the page says
dctlpcgytk
What the data behind the page says
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What the assistants repeated
todxtntkty
Finding 5
One assistant invented at least eight different people under her name.
8+
different people invented under her name
By one assistant working from memory
Finding 6
Most of the praise for her offer was an echo. 71% of it was one assistant repeating her own description word for word. The assistants that read her offer themselves described it differently.
Praise, or an echo?
Where the positive statements about her offer came from
71% her own words, repeated29% the assistants' own reading
Source: study data, August 2026
04What she is doing
Every change made.
Every month measured.
She got a prioritized and clear action plan: strategy, content strategy, positioning strategy, messaging and copy, a technical improvement and schema kit, site navigation restructuring, and more, and had made all the changes. We're now monitoring the results every month, with a new and updated, adjusted action plan per month.
- Strategy
- Content strategy
- Positioning strategy
- Messaging and copy
- Technical improvement and schema kit
- Site navigation
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