Our day job is sending monitoring questions to AI engines on both sides of the Chinese/Western divide and parsing what comes back. As of this update, 8 engines are live in our scoring (ChatGPT, Kimi, DeepSeek, Gemini, Doubao, Qwen, Perplexity, Grok). What follows are first-hand qualitative observations — not a data report (we don't publish numbers before the sample size deserves them), but the structural differences you notice when you watch both sides' answers every day.
Observation 1: two citation ecosystems, barely overlapping
Western engines commonly cite Wikipedia, Reddit, industry media, review sites and company websites. Chinese engines lean heavily on Zhihu (知乎), Baijiahao (百家号), WeChat official-account articles and vertical media. The sources treated as "authoritative" for the same brand are two entirely different sets.
The strategic consequence: English materials built for the West are rarely cited by Chinese engines, and vice versa. A dual-market brand needs two independently built content estates — not one estate plus a translation pass.
Observation 2: answers have different shapes
Chinese engines generally prefer structured, aggregated answers — bullet points with reference links appended (Kimi's references are the canonical example). Western engines vary more between products: some cite sparingly, some inline heavily.
What this means for brands: on the Chinese side, getting into the reference-link list is the hard currency of visibility; on the Western side, being named in the answer body carries more weight. Measure and optimize the two sides separately.
Observation 3: the same question gets a different answer every day
Both sides share one trait: instability. In a University of St. Gallen study (April 2026), across ~3,000 runs of comparable prompts, the odds of seeing the same brand-recommendation list twice were under 1%. Our free checkup and continuous monitoring sample the same question set on a fixed methodology precisely to turn that volatility from a feeling into a measurable curve.
Observation 4: brand names are a real recognition problem
Chinese brands often live under several names at once (月之暗面 / Moonshot AI / Kimi are one company); Western brands entering Chinese contexts appear as transliterations mixed with the original. Engines vary widely in how well they merge aliases — monitoring must ship with an alias table, or it will systematically understate visibility. Our mention detection includes common aliases (full rules in the methodology).
Three takeaways for brands
- Monitoring only one side means deciding with half a map.
- Localize content estates to each side's citation ecosystem — translation alone does not transfer authority.
- A single search screenshot is not evidence — continuous sampling is.
For the full ecosystem tour, see A field guide to Chinese AI engines.