中文摘要
我们使用经授权取得的OpenRouter专有数据集,分析AI如何影响企业、市场和劳动者。该数据集涵盖四百多个大语言模型实际发生的AI消费,共计380万亿个词元,覆盖当前全球月度AI词元消费量的约2%。借助这一数据前所未有的规模、覆盖范围和细致程度,我们根据词元消费量、美元支出额和用户数量的增长构建AI因子,通过股票收益联动估计企业层面的AI贝塔,并刻画AI溢价。首先,我们构建一个高频AI因子,并将其分解为主要组成部分。其次,我们发现,股票收益与AI因子的正向协动程度更高的企业——即高AI贝塔企业——获得更高的后续收益,且AI溢价较大并具有异质性。市值加权多空策略每周获得64.1个基点的收益;对AI消费的集约型、前沿导向边际——闭源模型、付费用户和经验丰富的用户,以及长提示词——的因子载荷所对应的溢价较大,而对随意使用或开放权重模型使用的因子载荷所对应的溢价则并非如此。第三,该溢价超出科技企业的范围,延伸至经济中面向消费者和资本密集型的部门,但在包括中国在内的新兴市场中不存在。第四,AI暴露在非常规互动型工作中更为正向,而在分析、科学和运营控制技能方面更为负向——互动与沟通内容高出一个标准差的职业,其市场隐含的AI暴露高出0.36个标准差。此外,我们提供了智能体经济兴起的早期证据。
Abstract
Using 380 trillion tokens of realized AI consumption across more than four hundred large language models from the licensed proprietary OpenRouter dataset covering approximately 2 percent of current global monthly AI token consumption, we analyze how AI affects firms, markets, and workers. Leveraging the unprecedented size, scope and granularity of this data, we construct the AI Factor from growth in tokens, dollars, and users, estimate firm-level AI Betas from stock return comovement, and characterize the AI Premium. First, we build a high-frequency AI factor and decompose it into salient components. Second, we show that firms whose returns covary more positively with the AI factor—high AI beta firms—earn higher subsequent returns, and the AI premium is large and heterogeneous. A value-weighted longshort strategy earns 64.1 basis points per week, and the premium is large for loadings on the intensive, frontier-oriented margin of AI consumption—closed-source models, paying and seasoned users, and long prompts—but not on casual or open-weight use. Third, the premium reaches beyond technology firms into consumer-facing and capital-heavy parts of the economy, but is absent in emerging markets, including China. Fourth, the AI exposure is more positive in nonroutine interactive work and more negative in analytical, scientific, and operations-control skills—an occupation one standard deviation higher in interaction-and-communication content has 0.36-standard-deviation higher market-implied AI exposure. Additionally, we provide early evidence of the rise of the agentic economy.