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搜索引擎请求酒店推荐时，哪些来源会被引用——查询措辞是否重要？我们对Google Gemini在东京156次酒店查询中的1,357条引用来源进行了审计，并记录了一种我们称之为意图-来源鸿沟的系统性模式。体验型查询从非OTA来源获得的引用占比为55.9%，而交易型查询仅为30.8%——两者相差25.1个百分点（$p < 5 \times 10^{-20}$）。在日语中，这一效应更为显著，体验型查询引用非OTA来源的比例达到62.1%，而英语仅为50.0%——这与日本更丰富的非OTA内容生态系统相一致。对于长期以来依赖OTA获取需求的酒店行业而言，这一模式意义重大，因为它表明AI搜索可能会使酒店被发现的过程不再完全受制于收取佣金的中间商。