How do you manage AI reputation across multiple languages and markets?

Multi-language AI reputation work is not a translation problem; it is a separate-ecosystem problem. The engines return different sources in each language, the source authority signals are calibrated per-language, and the Wikipedia and Wikidata layers are language-specific (a strong English Wikipedia article does not produce a German AI response if the German Wikipedia article is thin). Programs that operate seriously across markets monitor each priority language’s AI engines as their own layer in AIQ, invest in language-appropriate authoritative content (press in local outlets, owned content in the target language with proper schema, third-party coverage in language-relevant directories), and ensure the entity infrastructure exists in each priority language: Wikipedia article in the target language, Wikidata labels and descriptions in the target language, sameAs links (identifiers that tell the engines your profiles are the same entity) across the language versions. Done properly, the engines treat the brand consistently across markets; done poorly, the picture varies sharply by language in ways that surprise CCOs the first time they look.