How do AI chatbots handle requests for recommendations that include your competitors?

When the engines name competitors as recommendations, the question to ask is not whether to be offended but where the competitor is winning on the sources the engines read, not on the engines themselves. AIQ shows which sources the engines cite for the recommendation: a particular comparison article, a specific Wikipedia paragraph, an industry directory, a Reddit thread, a Wirecutter pick. From there the response runs on two tracks. On the brand’s own side: strengthen the entity signals (Wikidata, Knowledge Panel, schema), earn authoritative third-party coverage that gives the engines new material to weigh, and make sure the brand appears in the directories the engines are pulling competitor recommendations from. On the source side: work out whether the recommendation is genuinely earned (the competitor’s product is preferred for good reasons the brand needs to address) or structural (the source is dated, the engine is using an old comparison, or the competitor won a single placement that is now spreading). The work differs by case, but the diagnosis is consistent.