Motivated by agentic markets -- two-sided markets in which consumers and businesses are assisted by AI tools that facilitate consumers' search -- we study the impact of improved search technology on learning and welfare in markets. We put forth a model where consumers engage in costly search to acquire signals of product fit prior to purchase. The market tracks indications of fit for searched products and indications of quality for chosen products, thereby guiding searches. We characterize the long-run steady-state of the resulting dynamics as well as the impact of improving search technology. We find cheaper search improves learning and consumer surplus, whereas more informative search can degrade both unless the market learns as much as consumers about the products by, for example, ``reading the transcripts'' of agentic conversations. Finally, we consider the impact of search improvements on how businesses set prices. At equilibrium prices in symmetric markets, consumer surplus is improved by cheaper search but may be decreased by more informative search, due to weakened inter-business competition.

翻译：受代理人市场（即消费者和企业借助人工智能工具促进搜索的双边市场）的启发，我们研究了搜索技术改进对市场学习与福利的影响。我们提出一个模型：消费者在购买前通过成本较高的搜索获取产品匹配信号。市场追踪已搜索产品的匹配指标及已购买产品的质量指标，从而引导后续搜索。我们刻画了该动态过程的长期稳态，以及搜索技术改进的影响。研究发现：降低搜索成本可改善学习效果和消费者剩余；而提升搜索信息量反而可能同时损害两者，除非市场能通过例如"读取"代理人对话记录等方式，与消费者同步掌握产品信息。最后，我们探讨了搜索改进对企业定价策略的影响。在对称市场的均衡价格下，降低搜索成本能提升消费者剩余，但提升搜索信息量可能因弱化企业间竞争而减少消费者剩余。