How Consistent Are AI Answers? We Asked 3 Times
Ask Google's AI the same question three times and the cited sources stay fully stable only 81% of the time — about 3.2 sources shift on every repeat.
CiteLens Research · 500 prompts · 2026-06-21Can you trust a single check of "does AI mention my brand?" Because generative engines are probabilistic, the honest answer is: not entirely. To quantify how much AI recommendations move, we asked Google's AI the same 493 questions three times each and compared the sources it cited on every run.
AI Overviews turned out to be fairly stable but not deterministic. Across three immediate repeats the set of cited sources was fully identical only 81% of the time, with about 3.2 cited domains changing between runs even when the wording was exactly the same. Average source-set similarity was 84% — high enough to see clear patterns, low enough that a single snapshot can mislead you.
This is why measuring AI visibility properly means sampling, not spot-checking. If you ask once and see your brand, you might have caught a lucky roll; ask again and a competitor may take your place. The reliable approach is to run each query multiple times and report a rate with a confidence interval — which is exactly how CiteLens measures visibility. Below are the full consistency results and what they mean for tracking your AI presence.
Key findings
- Across 3 immediate repeats, the set of cited domains is fully stable only 81% of the time.
- On average ~3.2 cited domains change between repeats, even with identical wording.
- The average pairwise similarity of source sets is 84% — high, but not deterministic. A single snapshot can mislead you.
What this means for you
Because answers shift between asks, a single check of "does AI mention me?" is noise. You need repeated sampling to know your true visibility.
This is why CiteLens runs every prompt multiple times and reports a rate with a confidence interval — not a one-off yes/no.
Methodology
Each English prompt was queried three times (cache disabled on repeats). We compared the set of AI-cited domains across the three runs: "fully stable" is the share of domains present in all three; similarity is the average pairwise Jaccard across runs.
Download the data (JSON)Measure your own brand in AI answers
Run the same engine that produced this data on your own brand — see where you're cited and where you're missing.
Frequently asked questions
Does AI give the same answer every time?
Not exactly. In our test, Google's AI Overview returned a fully identical set of cited sources only 81% of the time across three repeats; on average 3.2 sources changed between runs.
Are AI search results reliable for tracking my brand?
Only if you sample repeatedly. A single check is noisy because answers vary; running each query several times and aggregating gives a reliable visibility rate instead of a one-off yes/no.
Why do AI answers change when I ask the same question?
Generative engines are probabilistic and re-retrieve sources each time, so the exact mix of cited domains shifts run to run — average similarity in our data was 84%.
How many times should I check my AI visibility?
Enough to separate signal from noise. CiteLens runs each prompt multiple times and reports a mention rate with a statistical confidence interval, rather than a single, potentially misleading snapshot.
Does this mean AI recommendations are random?
No — they're variable, not random. Patterns are stable enough (84% average similarity) to optimise against, but you need repeated measurement to see the true picture.