A sectoral taxonomy of AI intensity

Flavio Calvino, Hélène Dernis, Lea Samek and Antonio Ughi

No 30, OECD Artificial Intelligence Papers from OECD Publishing

Abstract: This work proposes a sectoral taxonomy of AI intensity, outlining different dimensions that characterise the extent to which AI relates to the activity of economic sectors. Focusing on AI human capital, AI innovation, exposure to and use of AI, the taxonomy provides a novel multifaceted perspective and reveals significant heterogeneity across sectors and indicators. While some sectors, such as IT services, score high along all the dimensions considered, others, such as Pharmaceuticals, exhibit more considerable heterogeneity (high AI human capital but low AI innovation). The taxonomy can be a useful tool for future policy-relevant analyses aimed at exploring empirically the role of AI and the implications of its diffusion.

Keywords: Artificial Intelligence; Human Capital; Innovation (search for similar items in EconPapers)
JEL-codes: C81 J24 O33 O34 (search for similar items in EconPapers)
Date: 2024-12-12
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Persistent link: https://EconPapers.repec.org/RePEc:oec:comaaa:30-en

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