arXiv:2512.07828cs.LGecon.GN2025-12被引 14

首份大规模研究揭示普通人如何用AI助手查资料、办公、购物。

The Adoption and Usage of AI Agents: Early Evidence from Perplexity

  • 通过分析数亿次用户交互,构建三级任务分类体系
  • 57%查询用于工作学习,55%为个人使用,前10个任务占一半
  • 高收入高学历人群更早使用,长期转向深度思考类任务

本文基于Perplexity开发的Comet浏览器及其智能助手Comet Assistant,首次开展大规模实地研究,分析通用AI代理在开放网络环境中的采用情况、使用强度与应用场景。利用数亿条匿名用户交互数据,回答三类核心问题:谁在使用?使用强度如何?主要用于什么?研究发现,早期采纳者多为高GDP国家、高教育水平及数字/知识密集型行业从业者(如科技、学术、金融、营销、创业)。通过构建分层代理分类体系,将使用场景划分为主题、子主题与具体任务三级。其中,工作与学习两大主题占全部查询的57%,课程学习与商品购物两大子主题占22%;前10项任务占据55%的查询量。个人用途占55%,专业与教育用途分别占30%和16%。短期内使用模式稳定,但随时间推移,用户逐渐转向认知要求更高的主题。该研究对科研人员、企业、政策制定者和教育工作者具有重要启示,推动对新型人工智能能力的深入探索。

原文摘要 · Abstract (English)

This paper presents the first large-scale field study of the adoption, usage intensity, and use cases of general-purpose AI agents operating in open-world web environments. Our analysis centers on Comet, an AI-powered browser developed by Perplexity, and its integrated agent, Comet Assistant. Drawing on hundreds of millions of anonymized user interactions, we address three fundamental questions: Who is using AI agents? How intensively are they using them? And what are they using them for? Our findings reveal substantial heterogeneity in adoption and usage across user segments. Earlier adopters, users in countries with higher GDP per capita and educational attainment, and individuals working in digital or knowledge-intensive sectors -- such as digital technology, academia, finance, marketing, and entrepreneurship -- are more likely to adopt or actively use the agent. To systematically characterize the substance of agent usage, we introduce a hierarchical agentic taxonomy that organizes use cases across three levels: topic, subtopic, and task. The two largest topics, Productivity & Workflow and Learning & Research, account for 57% of all agentic queries, while the two largest subtopics, Courses and Shopping for Goods, make up 22%. The top 10 out of 90 tasks represent 55% of queries. Personal use constitutes 55% of queries, while professional and educational contexts comprise 30% and 16%, respectively. In the short term, use cases exhibit strong stickiness, but over time users tend to shift toward more cognitively oriented topics. The diffusion of increasingly capable AI agents carries important implications for researchers, businesses, policymakers, and educators, inviting new lines of inquiry into this rapidly emerging class of AI capabilities.

AI代理用户行为智能助手数据分析

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