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This study leverages 15 million de-identified Gemini interactions to empirically map the diffusion of AI across occupations, tasks, and global regions, revealing currently shallow but widespread adoption patterns rather than end-to-end automation. The findings highlight significant economic value generated in high-friction daily activities that may be undercounted by standard national accounts while noting a correlation between national wealth and AI uptake levels.
Surse care acoperăarXiv, Fortune
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Google's AI & Economy ATLAS v1.0: Mapping Gemini Usage in the Economy

arXiv3 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2608.00038v1 Announce Type: cross Abstract: 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.

Title:Google's AI & Economy ATLAS v1.0: Mapping Gemini Usage in the Economy

Abstract: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.

General Economics (econ.GN); Artificial Intelligence (cs.AI)

arXiv:2608.00038 [econ.GN]

(or arXiv:2608.00038v1 [econ.GN] for this version)

https://doi.org/10.48550/arXiv.2608.00038 Focus to learn more arXiv-issued DOI via DataCite

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