Automotive AI Citation Study: 1275 AI Answers Measured

The short answer

In Automotive, 1275 AI answers were measured between May 2026 and August 2026. The most cited platform is Wikipedia at 4.39%, ahead of YouTube at 1.25%. That ranking differs from the general one: Wikipedia is cited 2.7 times more here than in the general ranking.

Automotive is the sector where encyclopedic sources still lead, well ahead of reviews, video and social platforms.

Key figures

• 301025 AI answers analysed between August 2025 and August 2026
• 1820738 citations extracted from those answers
• 131349 distinct domains cited at least once
• 5 models measured separately: ChatGPT, Gemini, Perplexity, Claude and Grok
• 79% of the questions asked in French, the rest in English

Which platforms the AIs cite in Automotive

• Wikipedia: 4.39%
• YouTube: 1.25%
• LinkedIn: 0.71%
• Facebook: 0.55%
• Instagram: 0.47%
• Trustpilot: 0.23%
• Shopify: 0.08%
• Leboncoin: 0.08%
• Indeed: 0.08%

What this sector cites more than the average

• Wikipedia: 4.39% here against 1.62% in the general ranking, 2.7 times more

The leading source model by model

• ChatGPT: Wikipedia at 12.71%
• Gemini: YouTube at 2.12%
• Perplexity: LinkedIn at 2.12%

How to read these numbers

A citation rate of 2% means the source was cited twice for every 100 measured answers. Rates are computed per model against the number of answers of that model, so a model with a smaller sample never distorts a column. A source cited several times inside one answer is counted once per company block, which keeps a single verbose answer from dominating a month.

The distribution is worth as much as the ranking. The top three sources hold 81% of the citations counted in this table, 2 platforms sit above 1%, and Wikipedia is cited 3.5 times more often than YouTube. A market where three sources hold most of the citations rewards depth on those three rather than presence everywhere.

This sector was measured on 1275 answers, 92.7% of them in French, across 3 of the five models (ChatGPT, Gemini, Perplexity). The language mix matters when you read the ranking, because local platforms weigh more in French speaking markets.

What changed over the measured period

This sector was measured over 4 months, between May 2026 and August 2026, on 1275 answers, and 9 platforms recorded at least one citation. Its leading source, Wikipedia, rose from 0.27% in May 2026 to 10.67% in August 2026, which is the kind of movement that makes a ranking older than one quarter unreliable.

Wikipedia month by month in this sector

• May 2026: 0.27%
• June 2026: 0.33%
• July 2026: 7.33%
• August 2026: 10.67%

What this means in practice

Vehicle questions are largely factual, and the models answer them from reference entries about models, engines and specifications. Dealer and brand sites appear far behind. For a business in this sector, that makes specification accuracy the visibility lever: the reference entry about a model is the source, and the dealer page only competes when it carries information the reference cannot, such as availability, local pricing and service detail.

How to use this study

1. Publish complete specification pages for the models and services you actually sell.
2. Keep local availability and pricing in text, since that is the gap reference sources cannot fill.
3. Do not rely on video: it is cited far less here than in comparable consumer sectors.

How this study was measured

1. We run a panel of buyer questions every month, the questions people type before choosing a supplier.
2. Every question is sent to five AI: ChatGPT, Gemini, Perplexity, Claude and Grok.
3. Every answer is parsed, every cited source is extracted and normalised to a domain and a platform.
4. The citation rate is the number of citations of a source per 100 measured answers, computed per model so an uneven number of answers per model never distorts a column.
5. The month is closed, the dataset is rebuilt, and the public files are republished on data.sorank.com.

Limits of this study

1. This panel is not a neutral sample of the web. The questions come from the sectors our users operate in.
2. The panel leans French: 237930 answers come from questions asked in French and 63095 from questions asked in English.
3. Model coverage is uneven: 87008 answers from ChatGPT, 87004 from Perplexity, 87000 from Gemini, 20011 from Claude and 20002 from Grok. The two smallest samples are read as direction rather than as precise values.
4. A citation is not a click. This study measures what the AIs cite, not what a reader does next.

The dataset behind this study

Every number on this page comes from the public Sorank dataset. The underlying figures, the monthly detail and the filters are available here:

Open the source data on data.sorank.com

Data updated on 2026-08-26.

How to cite this study

This study is free to quote, in an article, a deck or a report. Please cite the source and the measurement period, because the numbers move every month.

Sorank (2026). Automotive AI Citation Study: 1275 AI Answers Measured. Sorank GEO studies, measured on 301025 AI answers collected between August 2025 and August 2026. Available at https://www.sorank.com/data/automotive-ai-citation-study

Related studies

The same panel, read from another angle:

• AI Citation Study: Which Platforms the AIs Cite Most
• Wikipedia AI Citation Study
• Directories in AI Answers: Data Study
• All GEO studies

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