The User Asks, Platforms Compete: How Agentic Recommendation Markets Take Shape
Online recommendation has traditionally taken place after a user enters a platform, which determines the candidate pool and the ranking shown to the user. LLM-based user agents enable a different recommendation process: a user specifies a need before choosing a platform, leaving platforms to compete for the user's attention, which we refer to as an agentic recommendation market. In our controlled LLM-based experiments across three product domains, we find this new setting of recommendation creat
Record details
Published: 28 July 2026
Source: arXiv
Category: Research
Topics: Agents & autonomy
Retrieved: 29 July 2026
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ethics.ai (28 July 2026), “The User Asks, Platforms Compete: How Agentic Recommendation Markets Take Shape,” evidence record 14161, https://ethics.ai/record/14161 (originally published by arXiv).
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