Google AI Mode prompt volatility tracking
google_ai_modeprompt_volatilityAnonymous
Query fan-out makes AI Mode the most volatile Western surface we track. Volatility scoring is not optional here — it is how you avoid reporting noise as movement.
How it renders
Derived across the sample set.
Sampling
Volatility is what tells you the right n for every other field. We recommend using it to allocate credits: sample noisy prompts deeply, stable prompts lightly.
Gotcha
AI Mode volatility can exceed AI Overviews volatility on the same prompt by a wide margin. Copying an n across both surfaces will underfund one of them.
What the API returns
A single collection call against Google AI Mode for the prompt volatility field, sampled n times and returned as one object per prompt.
{
"engine": "google_ai_mode",
"field": "prompt_volatility",
"prompt": "best ai visibility tracking tool",
"country": "GB",
"language": "en",
"n": 30,
"volatility": {
"jaccard": 0.42,
"mention_variance": 0.11,
"recommended_n": 75,
"band": "moderate"
}
}Response fields
| Key | Type | Notes |
|---|---|---|
| jaccard | float | Mean pairwise citation-set overlap across samples. |
| mention_variance | float | Variance in brand presence across samples. |
| recommended_n | integer | Samples needed for a ±10 point interval on this prompt. |
| band | string | stable | moderate | volatile. |
Google AI Mode prompt volatility FAQ
- Why is AI Mode more volatile?
- Each sample re-runs fan-out, and different sub-searches surface different sources, so citation sets drift more between samples.
- What n does a volatile AI Mode prompt need?
- Often forty or more. The recommended_n field returns the figure per prompt rather than guessing globally.
Size AI Mode sampling from measured noise
We'll run a volatility pass and give you a per-prompt n before you commit budget.
Other Google AI Mode data
Across every engine
Compare how prompt volatility behaves on every engine we track.
Prompt volatility across all engines →