When a traveler asks an AI search engine to recommend a hotel, which sources get cited -- and does query framing matter? We audit 1,357 grounding citations from Google Gemini across 156 hotel queries in Tokyo and document a systematic pattern we call the Intent-Source Divide. Experiential queries draw 55.9% of their citations from non-OTA sources, compared to 30.8% for transactional queries -- a 25.1 percentage-point gap ($p < 5 \times 10^{-20}$). The effect is amplified in Japanese, where experiential queries draw 62.1% non-OTA citations compared to 50.0% in English -- consistent with a more diverse Japanese non-OTA content ecosystem. For an industry in which hotels have long paid OTAs for demand acquisition, this pattern matters because it suggests that AI search may make hotel discovery less exclusively controlled by commission-based intermediaries.

翻译：当旅行者向AI搜索引擎请求推荐酒店时，哪些来源会被引用——查询框架是否产生影响？我们对Google Gemini在东京156个酒店查询中的1,357条溯源引用进行了审计，并记录了一个我们称之为"意图-来源鸿沟"的系统性模式。体验型查询的引用中有55.9%来自非OTA来源，而交易型查询的这一比例为30.8%——两者相差25.1个百分点（$p < 5 \times 10^{-20}$）。这一效应在日语中更为显著：体验型查询的非OTA引用占比达62.1%，而英语中为50.0%——这与日语中更加多元化的非OTA内容生态系统相吻合。对于一个长期依赖OTA获取需求的酒店行业而言，这一模式至关重要，因为它表明AI搜索可能使酒店发现过程不再被基于佣金的中介所独家控制。