# The End of Rented Discovery: How AI Search Redistributes Power Between Hotels and Intermediaries

arXiv: https://arxiv.org/abs/2603.20062 · HTML: https://mlsanity.com/paper/2603.20062/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 18 references that are in the map.
- First posted on arXiv 20 Mar 2026.

## Builds on (most cited first, 7 of 7)

- [GEO: Generative Engine Optimization](https://mlsanity.com/paper/2311.09735/) (2023)
- [Quantifying Search Bias: Investigating Sources of Bias for Political Searches in Social Media](https://mlsanity.com/paper/1704.01347/) (2017)
- [Generative Engine Optimization: How to Dominate AI Search](https://mlsanity.com/paper/2509.08919/) (2025)
- [Generative AI Search Engines as Arbiters of Public Knowledge: An Audit of Bias and Authority](https://mlsanity.com/paper/2405.14034/) (2024)
- [News Source Citing Patterns in AI Search Systems](https://mlsanity.com/paper/2507.05301/) (2025)
- [Role-Augmented Intent-Driven Generative Search Engine Optimization](https://mlsanity.com/paper/2508.11158/) (2025)
- [The Discovery Gap: How Product Hunt Startups Vanish in LLM Organic Discovery Queries](https://mlsanity.com/paper/2601.00912/) (2026)

## Built on by (most cited first, 1 of 1)

- [Measurement Risk in Supervised Financial NLP: Rubric and Metric Sensitivity on JF-ICR](https://mlsanity.com/paper/2604.27374/) (2026)

## Abstract (arXiv)

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 × 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.