Global AI chatbot brand recommendations vary significantly based on the language of the user’s query, influenced by cultural values and regional AI model behaviors, new research revealed.
This linguistic divergence in AI-generated suggestions poses a notable challenge for global marketing strategies and brand visibility tracking, particularly in non-English speaking markets where AI referrals are substantial.
AI models like Claude, ChatGPT and Gemini are widely used in non-English speaking regions, accounting for more than 90 percent of AI referrals in countries such as Saudi Arabia, Kazakhstan and Singapore, according to data from Statcounter.
These AI chatbots reason and compose responses in the queried language rather than merely translating, which introduces cultural values and other localized factors into their recommendations, experts said.
Research conducted by Anthropic on its Claude model found that the AI’s inherent ‘values,’ such as warmth or rigor, shifted based on the language used in the query. Queries in Hindi and Arabic reportedly led to responses exhibiting greater warmth, while English and Russian queries resulted in greater rigor.
Duane Forrester, an industry expert, indicated that this linguistic nuance means brands need to consider how their messaging translates not just literally, but culturally, within AI systems.
Independent tests on Claude Sonnet 5 across six scenarios and five languages—English, Arabic, Russian, Simplified Chinese and Persian—demonstrated that brand recommendations differed significantly by language.
The tests showed that AI models might recommend different brands for the same product or service depending on the language of the request, potentially affecting a brand’s visibility in various markets.
Some international brands, especially airlines, have established local-language forms of their names or services. AI models may utilize these localized forms in non-English responses, which could affect how brands track their visibility and mentions across different linguistic contexts.
Companies like Baidu in China, Naver in South Korea and Mistral in France also develop AI models tailored to their respective linguistic and cultural contexts, further fragmenting global AI recommendations, according to DataForSEO.
Source: Search Engine Journal
