Research Report

AI Visibility Benchmark Report 2026

We measured our own brand six times across three AI engines and publish it with its margin of error. It did not come out well.

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By Ömer Cenk Tokgöz, Founder|May 2026 · Updated 2 September 2026|Original Research
Kısa Yanıt

What did the 2026 AI visibility benchmark measure?

Botfusions measured its own brand six times between 29 June and 2 September 2026. The last four scans ran across ChatGPT, Gemini and Google AI Overview. On 6 October 2026 we withdrew the zero results we had published for Gemini and Google AI Overview after our measurement provider reported an error. The measurement that stands: on 15 September 2026 we were mentioned in 11.2% of ChatGPT answers (249 answers, ±3.9 pp). Every figure is given with the margin of error of the engine it belongs to.

11.2%ChatGPT mention rate, 249 answers (15 Sep)

The measurement series

Between 29 June and 2 September 2026 we measured our own brand six times. The measurement tool is a third-party platform; the last four scans ran across ChatGPT, Gemini and Google AI Overview. Correction (6 October 2026): The first version of this report published zero mentions in 1,075 Gemini and 1,052 Google AI Overview queries. Our measurement provider reported that these zeros were a measurement error and that brand matching failed in the 13 August scan. We have withdrawn these figures. On 15 September 2026 we were mentioned in 11.2% of 249 ChatGPT answers (±3.9 pp). ChatGPT measurements that stand: • ChatGPT — 14.3% on 31 August (n=300), 6.5% on 2 September (n=214), margin ±3.4 pp We also mapped 50 demand themes: we lead in 0, contest 11, and 39 are entirely unclaimed.

Methodology

Each scan runs commercial-intent queries across three AI engines and records, for every response, whether the brand was mentioned, its position within the answer, sentiment, and citation share. The score is a weighted average of four dimensions: mention 40%, position 30%, recommendation 20%, citation 10%. Margin of error: for each engine, a 95% confidence interval computed from that engine's response count. In this series: ChatGPT ±3.4 pp. Comparability rule: two scans are comparable only when run with the same engine set and the same scan type. A difference between two scans of different types cannot be read as improvement or decline.

What we do not claim

This is the most important section of the report. We claim no trend on ChatGPT. Our two measurements (14.3% and 6.5%) come from scans of different types and are not comparable. We present the difference as neither improvement nor decline. We hold an older, higher Gemini figure; we do not use it, because it was measured with a different engine set. Broad market claims — 'brands doing GEO are N times more visible', 'AI traffic converts at X%' — do not appear in this report, because we cannot verify them with our own measurement. We also no longer claim the zero finding on Gemini and Google AI Overview: our measurement provider reported those zeros as a measurement error, and we withdrew them on 6 October 2026.

Sources

Every measurement figure on this page comes from our own scans and is given above together with the engine, query count and margin of error. For academic findings on the relative effect of GEO techniques, see the Princeton study published at KDD 2024 — 'GEO: Generative Engine Optimization'. Its figures are peer-reviewed and reproducible; they must not be confused with our measurements. A summary with attribution is on our /methodology page. This report contains no figure without a stated source.

Cite this research

Use the citation below when referencing this report (APA):

Tokgöz, Ö. C. (2026). AI Visibility Benchmark Report 2026. Botfusions. https://botfusions.com/research/ai-visibility-benchmark-2026

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