After analysing 2,525 "AI creators": 42.8% have audiences that are general consumers, not practitioners
"Find AI creators" sounds like a well-defined brief — until you notice that two creators both covering AI tools can have audiences that barely overlap: one talks to media buyers, one to engineers, and one to people who are simply entertained by AI.
We ran deep content analysis on 2,525 creators in the AI category — an average of 65 recent posts each — to determine who their audience actually is and what job that audience does. Here is the distribution.
| Audience function | Creators | Share |
|---|---|---|
| General consumers (not practitioners) | 1,080 | 42.8% |
| Undetermined | 388 | 15.4% |
| Content creators | 228 | 9.0% |
| Automation / agent builders | 197 | 7.8% |
| General AI enthusiasts | 188 | 7.4% |
| Developers | 145 | 5.7% |
| Design | 89 | 3.5% |
| Sales / lead gen | 56 | 2.2% |
| E-commerce ops | 56 | 2.2% |
| learner | 35 | 1.4% |
| Paid media buyers | 29 | 1.1% |
| Data analysts | 21 | 0.8% |
| SEO / GEO | 7 | 0.3% |
| Recruiting | 3 | 0.1% |
| Customer support | 3 | 0.1% |
What this means for campaigns
The largest bucket is "general consumers" (42.8%). These creators make good content and their followers are real — but the audience is people entertained by AI, not practitioners who buy tools. Putting a B2B product in front of this bucket is mostly wasted spend — not because the creator is weak, but because the people are wrong.
Only 41.9% map to an identifiable professional function. That is the pool B2B tools should be competing for, and it needs slicing further by function: an automation-for-paid-media product belongs with media-buyer audiences, an API product with developer audiences. Swap them and the result is the same as a mismatch.
A further 15.4% could not be determined. When the content is too sparse or too scattered we mark it undetermined rather than inventing a plausible-sounding persona — a fabricated persona is more dangerous than none.
How to avoid the trap
Searching by content topic lumps these groups together, because on the surface they all post "AI" content. The only way to separate them is to look at the audience: what the comments are asking, whose problems the creator keeps addressing, what the content assumes the reader already knows. That requires reading enough posts — a bio and a follower count cannot tell you.
Methodology
The sample is 2,525 creator accounts indexed and validated inside Koinon Link. It is not every creator on these platforms, and it is not a random sample — it comes from our keyword-driven collection, which skews toward AI software, e-commerce and gaming.
"Suspected inflated" is our own anomaly detection, not a platform-official flag: it looks at whether follower growth arrived in vertical steps, whether the engagement-to-follower ratio sits far outside the normal band for that platform and size tier, and how templated the engagement looks. It means "worth a manual check", not "this account is definitely cheating".
All figures are recomputed daily; this page shows the most recent run.