通过1500万条数据,揭示AI在职场与日常生活的实际使用情况。
Google's AI & Economy ATLAS v1.0: Mapping Gemini Usage in the Economy

- 基于隐私保护算法,将AI使用映射到800余职业与4000项任务。
- 美国超88%就业覆盖AI使用,但多数为协作式,端到端自动化有限。
- 非工作时间98%活动涉及AI,尤其在高摩擦任务中价值显著。
本文介绍人工智能与经济地图集(AI & Economy ATLAS),一项基于谷歌AI使用数据的持续性经济研究。首个版本基于1500万条去标识化交互数据,涵盖Gemini应用、Google AI模式及Gemini API。通过隐私保护算法与定制分类方法,将AI使用映射至800余职业、4000项任务、300项家庭活动、150个国家和140种语言。研究发现,美国超过88%的就业岗位涉及AI使用,但渗透率仍较浅,以协作为主,端到端自动化范围有限;非工作时间约98%的活动包含AI使用,尤其在与政府及专业服务互动等高摩擦任务中占比更高,可能带来被传统国民经济核算遗漏的经济价值。全球范围内,AI采用率随国家财富上升,语言分布广泛,英语查询仅占总量约三分之一。随着ATLAS持续扩展,将持续提供大规模实证数据,支持公众、政策与学术界对人工智能转型的探讨。
原文摘要 · Abstract (English)
This paper introduces the AI & Economy ATLAS (Activity, Task, Landscape, and Adoption Study), an ongoing economic research initiative using Google AI usage data. The first iteration of ATLAS is built on 15 million de-identified interactions across the Gemini App, Google AI Mode, and Gemini API. Using privacy-preserving algorithms as well as established and bespoke classification methods, we map AI usage to over 800 occupations, 4000 tasks, 300 household activities, 150 countries, and 140 languages. We then make a number of observations on what the data reveals about AI's diffusion, and its usage at work and in day-to-day life. In the workplace, we show that while AI adoption spans occupations covering just above 88% of US employment, penetration remains shallow and overwhelmingly collaborative in nature, with end-to-end task automation limited in scope. Outside of work, AI spans activities making up about 98% of Americans' non-sleep time, with disproportionately high use in high-friction tasks such as engaging with government and professional service providers, likely delivering economic value that standard national accounts may miss. Globally, adoption scales with national wealth and has broad linguistic distribution, with English queries representing only around a third of volume. As we build upon ATLAS and expand its scope and capabilities, we will continue to provide large-scale empirical evidence to inform the public, policy and academic questions about the ongoing AI transformation.
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