从产品搜索到偏好表达：智能体商业的经济学

中文摘要 AI 辅助

生成式AI正将数字商业从浏览转向智能体搜索，在此模式下消费者将产品发现任务委托给AI智能体。我们对比手动搜索与智能体搜索：手动搜索能准确评估有限的产品集合，智能体搜索则通过偏好与产品的有噪表征筛选广泛的产品目录。偏好复杂性是指与满意度相关的维度数量，这些维度在搜索前难以清晰表达，但在产品检视时易于评估。消费者注意力有限，会选择搜索强度：要么手动检视产品，要么用智能体优化偏好的深度。我们得到三项发现：第一，手动搜索在有限的复杂性阈值之外会崩溃，即检视停止、错配达到无搜索基准、平台收入降至零；智能体搜索可避免这种崩溃，一旦优化变得有价值，其价值会随复杂性上升而保持，错配仍低于无搜索基准且收入为正，尽管表达努力和错配可能增加。第二，平台按转化收入对两种模式排序，而消费者还需承担搜索支出；当手动检视足够便宜时，智能体搜索在消费者自愿采用前就成为收入更优选项，产生采用滞后，此时消费者理性地继续使用手动搜索。第三，在智能体参与的条件下，平台可能为注意力预算更大的消费者分配更低的保真度，因为他们可通过额外优化抵消更嘈杂的表征，形成倒转的保真度分配。因此，智能体商业将稀缺性从产品检视转向偏好表达，使消费者的互动意愿与能力成为自愿使用和平台保真度设计的核心。

英文摘要

Generative AI is shifting digital commerce from browsing toward agentic search, in which consumers delegate product discovery to AI agents. We compare manual search, which accurately evaluates a limited product set, with agentic search, which screens a broad catalog through noisy representations of preferences and products. Preference complexity is the number of satisfaction-relevant dimensions that are difficult to articulate before search but readily evaluated upon inspection. Consumers have finite attention and choose search intensity: products inspected manually or preference-refinement depth with an agent. We obtain three findings. First, manual search collapses beyond a finite complexity threshold: inspection ceases, mismatch reaches the no-search benchmark, and platform revenue falls to zero. Agentic search avoids this collapse. Once refinement becomes worthwhile, it remains worthwhile as complexity rises; mismatch stays below the no-search benchmark and revenue remains positive, although articulation effort and mismatch may increase. Second, platforms rank the regimes by conversion revenue, whereas consumers also bear search expenditure. When manual inspection is sufficiently inexpensive, agentic search becomes revenue-superior before consumers voluntarily adopt it, creating an adoption lag in which consumers rationally continue manual search. Third, conditional on agentic participation, platforms may assign lower fidelity to consumers with larger attention budgets because they can offset noisier representations through additional refinement, yielding an inverted fidelity allocation. Agentic commerce thus shifts scarcity from product inspection to preference articulation, making consumers' willingness and ability to interact central to voluntary use and platform fidelity design.

发表机构

• Olin Business School, Washington University in St. Louis（圣路易斯华盛顿大学奥林商学院）
• School of Business, University of Connecticut（康涅狄格大学商学院）

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