AI assistants like ChatGPT and Claude are recommendation engines, not search engines: they answer commercial queries by directly nominating brands rather than returning a list of links. Marketing to AI is therefore a broader problem than "show up in search" -- positioning, content, and product fit matter as much as discoverability. We audit ~37,000 production runs across four model configurations and 215 commercially-framed prompts spanning 19 sectors, evaluated against a 533-brand reference catalog stratified into five prominence tiers (L1 category leaders to L5 regional players) sourced from external authority lists. The ladder proxies a brand's awareness footprint within its sector, not revenue or market share. The failure mode differs sharply by tier. L1 brands appear in nearly every relevant retrieval but win only 25-41% of the recommendation slots they reach -- the leverage is differentiation, not visibility. L2 challengers carry the highest conversion rates of any tier (37-52%) but lose to persona-mediated substitution on the Anthropic models. L3 mid-market brands are the inflection level: aggregate coverage drops to 88%, conversion to 34-40%, and persona effects peak. L4 specialists and L5 regional players face catastrophic invisibility -- 48-52% never surface in any of the 37,000 runs. No uniform optimization recipe wins; the right marketing investment depends on where the brand sits on the prominence ladder.

翻译：像ChatGPT和Claude这样的AI助手本质上是推荐引擎而非搜索引擎：它们通过直接推荐品牌而非返回链接列表来回答商业查询。因此，面向AI的营销已超越"出现在搜索结果中"这一传统问题——品牌定位、内容策略与产品适配度与可发现性同等重要。我们针对四种模型配置、涵盖19个行业的215个商业导向提示，进行了约37,000次实际运行审计。评估基准为包含533个品牌的参考目录，该目录依据外部权威榜单被划分为五个显著性层级（从L1品类领导者到L5区域品牌）。该层级模型衡量的是品牌在其行业内的知名度辐射范围，而非收入或市场份额。失败模式随层级呈现显著差异：L1品牌几乎出现在所有相关检索结果中，但在其触及的推荐位中仅获得25-41%的胜率——关键在于差异化而非可见性；L2挑战者品牌在所有层级中拥有最高转化率（37-52%），但在Anthropic模型上会因角色中介替代效应而失利；L3中端市场品牌为转折层级：整体覆盖率降至88%，转化率降至34-40%，角色效应达到峰值；L4专家型品牌与L5区域品牌面临灾难性不可见性——48-52%的品牌从未在37,000次运行中出现。不存在统一的优化方案，正确的营销投入取决于品牌所处的显著性层级位置。