AI Visibility in the Automotive Industry: Brantial Report Findings

The automotive industry is becoming one of the sectors where visibility in AI-powered search systems is being redefined at the fastest pace. To analyze this transformation with concrete data,
Brantial prepared this study, which sets out to reveal how, and to what extent, brands appear in AI answers. The comprehensive query sets built for the study were designed to represent different user intents, and those queries were run across multiple AI models in a standardized way.

The result moves beyond classic SEO metrics and turns “visibility inside AI” into something that can actually be measured.

The automotive AI visibility panorama

According to the report, the brands referenced most often in AI answers across the automotive sector separate from the pack clearly. Toyota, Mercedes-Benz, and BMW stand out with the highest total mention volumes.

The top 10 brands generated more than 59,000 references in total, and more than 35,000 of those went to the top 5 brands alone. This shows that AI visibility in the sector is heavily concentrated, with leading brands securing a serious advantage.

The gap between the highest-ranked and lowest-ranked brand also runs into the thousands of references, which means visibility is not distributed linearly but drops off sharply.

Brand reference distribution across AI models

One of the study's most critical findings is that the same queries produce different brand distributions in different AI models.

Some models reference certain brands far more heavily, while others show a more balanced spread. For example:

• In some models, Mercedes-Benz variants (AMG, Maybach, and others) are referenced in a more fragmented way,
• while other models concentrate on the plain brand names.

This points to two important conclusions:

1. Brand name variants directly affect AI visibility
2. Focusing on a single model can create a serious visibility loss

For brands, the critical goal is now achieving multi-model visibility.

AI Visibility Score and the gaps between brands

The AI Visibility Score used in the report measures how frequently each brand appears across the full query set.

Looking at this metric:

• Leading brands stand out with very high scores
• Mid-segment brands remain in limited visibility
• Brands in the lower segment do not appear at all in most queries

Unlike classic SEO, this points to a much sharper competitive model in the AI ecosystem: you are either visible or you do not exist.

The future of competition in the AI answer ecosystem

One of the report's most important takeaways is that competition has moved from Google rankings into the AI answers themselves.

When an AI system serves a single answer to the user, it is actually pulling data from many sources and selecting specific brands from among them. As a result:

• Winning rankings is not enough
• Being cited by AI is essential

This marks a new era in which visibility is evaluated on “presence” rather than “position”.

Strategic recommendations and vision for brands in AI search visibility

The study lays out the rules of this new era for brands in clear terms:

• Website content alone is not enough to appear in AI answers
• Wikipedia, forums, news sites, and third-party platforms have become critical
• Managing brand name variants directly affects visibility
• A multi-model AI strategy is required, not a single-platform one

The brands that succeed in the coming period will not simply be the ones doing SEO; they will be the ones that understand how AI systems work and feed those systems with data.

This puts the GEO (Generative Engine Optimization) approach clearly at the center of digital visibility.