Turbulence
Brand Drift
A photocopy of a photocopy.
Every answer a machine gives about you is also material for the next answer. Leave the AI’s version of your brand unattended and it does not stay still — it is quoted, summarised, rewritten and, eventually, trained on. Each pass hardens the errors. Each iteration makes recovery slower.
What is happening
Brand Drift
A photocopy of a photocopy.
The longer the image is left alone, the more of the world is built on it.
What we see
Brands engaging with AEO and GEO tactics without knowing why their machine image looks the way it does — optimising the surface while the root cause keeps feeding the loop. The text the models return becomes the text other people publish, which becomes the corpus of the next model.
Why it compounds
Training is a ratchet. A wrong description in one answer is a nuisance; the same description in ten thousand generated articles is a fact the next generation of models learns from. Recovery is possible at every stage, but the cost rises with each cycle — and the cycles are getting shorter.
What it looks like from inside
Nothing dramatic. Search traffic looks fine. A prospect mentions something you never said. A journalist’s draft carries a phrase you have never used. The description is not hostile, merely slightly wrong — and it is everywhere.
What to do
Read it. Correct it. Keep it corrected.
In that order — the instrument before the tactic.
Read it
Establish what the major models believe today — verbatim and scored — before touching anything. Drift can only be measured against a baseline.
Correct it
Repair the sources the machine trusts, not the surface it returns. Root cause first; tactics afterwards.
Keep it corrected
Re-read on a cadence, because the loop does not stop when you do. The Pitot Index and a standing Audit exist for exactly this.
What this asks for
Drift is measurable.
A baseline, a cadence, and a reading that separates your movement from the model’s. That is the Measure practice.