AI Search Language Sensitivity
AI search language sensitivity is the way generative search results change when the same query intent is expressed in different languages.
Key points
- The paper tests translated ranking-style prompts across Chinese, Japanese, German, French, Spanish, and English, then compares cited domains, brands, source types, and website language [src-028].
- Cross-language domain stability is limited and engine-dependent: Claude reuses more authority domains across languages, while GPT swaps site ecosystems more strongly by language [src-028].
- Perplexity and Gemini sit between those poles, with some low-to-moderate cross-language overlap and vertical-specific variation [src-028].
- Brand overlap is generally higher than domain overlap, especially in categories dominated by global head brands; localized or long-tail categories vary more [src-028].
- The strategic implication is that multilingual GEO requires local-language authority coverage, not only translation of brand-owned content [src-028].
Related entities
Related concepts
- Generative Engine Optimization
- AI Search
- AI Search Citation Network
- Earned Media Bias in AI Search
- Big Brand Bias in AI Search
Source references
- [src-028] Mahe Chen, Xiaoxuan Wang, Kaiwen Chen, Nick Koudas — “Generative Engine Optimization: How to Dominate AI Search” (2025-09-10)
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