Starting Up AI

Emin Dinlersoz, Can Dogan and Nikolas Zolas

Working Papers from U.S. Census Bureau, Center for Economic Studies

Abstract: Using comprehensive administrative data on business applications over the period 2004- 2023, we study business applications (ideas) and the resulting startups that aim to develop AI technologies or produce goods or services that use, integrate, or rely on AI. The annual number of new AI-related business applications is stable between 2004 and 2011, but begins to rise in 2012 with further increases from 2016 onward into the Covid-19 pandemic and beyond, with a large, discrete jump in 2023. The distribution of these applications is highly uneven across states and sectors. AI business applications have a higher likelihood of becoming employer startups compared to other applications. Moreover, businesses originating from these applications exhibit higher revenue, average wage, and labor share, but similar labor productivity and lower survival rate, compared to other businesses. While it is still early in the diffusion of AI, the rapid rise in AI business applications, combined with the better performance of resulting businesses in several key outcomes, suggests a growing contribution from AI-related business formation to business dynamism.

Pages: 49 pages
Date: 2024-03
New Economics Papers: this item is included in nep-ain, nep-ent, nep-lma and nep-sbm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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https://www2.census.gov/library/working-papers/2024/adrm/ces/CES-WP-24-09R.pdf Revised version, 2024 (application/pdf)
https://www2.census.gov/library/working-papers/2024/adrm/ces/CES-WP-24-09.pdf First version, 2024 (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:cen:wpaper:24-09

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