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

• OpenAI
• Anthropic
• Gemini
• Perplexity API

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)