人工智能时代的劳动力需求：来自美国招聘数据的早期证据（英）

Policy Research Working Paper11263Labor Demand in the Age of Generative AIEarly Evidence from the U.S. Job Posting DataYan LiuHe Wang Shu YuDigital Transformation Vertical &Prosperity VerticalNovember 2025 A verified reproducibility package for this paper is available at http://reproducibility.worldbank.org, click here for direct access. Public Disclosure AuthorizedPublic Disclosure AuthorizedPublic Disclosure AuthorizedPublic Disclosure AuthorizedProduced by the Research Support TeamAbstractThe Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.Policy Research Working Paper 11263This paper examines the causal impact of generative artificial intelligence on U.S. labor demand using online job posting data. Exploiting ChatGPT’s release in November 2022 as an exogenous shock, the paper applies difference-in-differences and event study designs to estimate the job displacement effects of generative artificial intelligence. The identification strategy compares labor demand for occupations with high versus low artificial intelligence substitution vulnerability following ChatGPT’s launch, conditioning on similar generative artificial intelligence exposure levels to isolate substitution effects from complementary uses. The anal-ysis uses 285 million job postings collected by Lightcast from the first quarter of 2018 to the second quarter of 2025Q2. The findings show that the number of postings for occupations with above-median artificial intelligence substitution scores fell by an average of 12 percent relative to those with below-median scores. The effect increased from 6 percent in the first year after the launch to 18 per-cent by the third year. Losses were particularly acute for entry-level positions that require neither advanced degrees (18 percent) nor extensive experience (20 percent), as well as those in administrative support (40 percent) and profes-sional services (30 percent). Although generative artificial intelligence generates new occupations and enhances pro-ductivity, which may increase labor demand, early evidence suggests that some occupations may be less likely to be com-plemented by generative artificial intelligence than others.This paper is a product of the Digital Transformation and the Office of the Chief Economist, Prosperity Vertical. It is part of a larger effort by the World Bank to provide open access to its