Identifying and characterising AI adopters: A novel approach based on big data
This work employs a novel approach to identify and characterise firms adopting Artificial Intelligence (AI), using different sources of large microdata. Focusing on the United Kingdom, the analysis combines data on Intellectual Property Rights, website information, online job postings, and firm-leve...
Gespeichert in:
| 1. Verfasser: | |
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| Weitere Verfasser: | , , |
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Paris
OECD Publishing
2022
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| Schriftenreihe: | OECD Science, Technology and Industry Working Papers
no.2022/06 |
| Schlagworte: | |
| Online-Zugang: | DE-862 DE-863 |
| Zusammenfassung: | This work employs a novel approach to identify and characterise firms adopting Artificial Intelligence (AI), using different sources of large microdata. Focusing on the United Kingdom, the analysis combines data on Intellectual Property Rights, website information, online job postings, and firm-level financials for the first time. It shows that a significant share of AI adopters is active in Information and Communication Technologies and professional services, and is located in the South of the United Kingdom, particularly around London. Adopters tend to be highly productive and larger than other firms, while young adopters tend to hire AI workers more intensively. Human capital appears to play an important role, not only for AI adoption but also for firms' productivity returns. Significant differences in the characteristics of AI adopters emerge when distinguishing between firms carrying out AI innovation, those with an AI core business, and those searching for AI talent. |
| Beschreibung: | 1 Online-Ressource (67 Seiten) 21 x 28cm. |
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| spelling | Calvino, Flavio VerfasserIn aut Identifying and characterising AI adopters A novel approach based on big data Flavio, Calvino ... [et al] Paris OECD Publishing 2022 1 Online-Ressource (67 Seiten) 21 x 28cm. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier OECD Science, Technology and Industry Working Papers no.2022/06 This work employs a novel approach to identify and characterise firms adopting Artificial Intelligence (AI), using different sources of large microdata. Focusing on the United Kingdom, the analysis combines data on Intellectual Property Rights, website information, online job postings, and firm-level financials for the first time. It shows that a significant share of AI adopters is active in Information and Communication Technologies and professional services, and is located in the South of the United Kingdom, particularly around London. Adopters tend to be highly productive and larger than other firms, while young adopters tend to hire AI workers more intensively. Human capital appears to play an important role, not only for AI adoption but also for firms' productivity returns. Significant differences in the characteristics of AI adopters emerge when distinguishing between firms carrying out AI innovation, those with an AI core business, and those searching for AI talent. Science and Technology Industry and Services Samek, Lea MitwirkendeR ctb Squicciarini, Mariagrazia MitwirkendeR ctb Morris, Cody MitwirkendeR ctb |
| spellingShingle | Calvino, Flavio Identifying and characterising AI adopters A novel approach based on big data Science and Technology Industry and Services |
| title | Identifying and characterising AI adopters A novel approach based on big data |
| title_auth | Identifying and characterising AI adopters A novel approach based on big data |
| title_exact_search | Identifying and characterising AI adopters A novel approach based on big data |
| title_full | Identifying and characterising AI adopters A novel approach based on big data Flavio, Calvino ... [et al] |
| title_fullStr | Identifying and characterising AI adopters A novel approach based on big data Flavio, Calvino ... [et al] |
| title_full_unstemmed | Identifying and characterising AI adopters A novel approach based on big data Flavio, Calvino ... [et al] |
| title_short | Identifying and characterising AI adopters |
| title_sort | identifying and characterising ai adopters a novel approach based on big data |
| title_sub | A novel approach based on big data |
| topic | Science and Technology Industry and Services |
| topic_facet | Science and Technology Industry and Services |
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