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Emerging trends in AI skill demand across 14 OECD countries (2023)

Borgonovi, Francesca [VerfasserIn] ; Calvino, Flavio [MitwirkendeR] ; Criscuolo, Chiara [MitwirkendeR] ; [et al.]

Paris : OECD Publishing

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Language: English

Pages: 1 Online-Ressource (64 p.) , 21 x 28cm.

Series Statement: OECD Artificial Intelligence Papers no.2

Keywords: Künstliche Intelligenz ; Qualifikation ; Arbeitsnachfrage ; OECD-Staaten ; Education ; Employment ; Science and Technology ; Industry and Services

Abstract: This report analyses the demand for positions that require skills needed to develop or work with AI systems across 14 OECD countries between 2019 and 2022. It finds that, despite rapid growth in the demand for AI skills, AI-related online vacancies comprised less than 1% of all job postings and were predominantly found in sectors such as ICT and Professional Services. Skills related to Machine Learning were the most sought after. The US-focused part of the study reveals a consistent demand for socio-emotional, foundational, and technical skills across all AI employers. However, leading firms – those who posted the most AI jobs – exhibited a higher demand for AI professionals combining technical expertise with leadership, innovation, and problem-solving skills, underscoring the importance of these competencies in the AI field.

DOI: 10.1787/7c691b9a-en

URL: lizenzpflichtig

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Is there a trade-off between productivity and employment? : A cross-country micro-to-macro study (2023)

Calligaris, Sara [VerfasserIn] ; Calvino, Flavio [MitwirkendeR] ; Verlhac, Rudy [MitwirkendeR] ; [et al.]

Paris : OECD Publishing

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Language: English

Pages: 1 Online-Ressource (63 p.) , 21 x 28cm.

Series Statement: OECD Science, Technology and Industry Policy Papers no.157

Keywords: Employment ; Science and Technology ; Industry and Services

Abstract: The impact of productivity on employment remains uncertain, particularly in light of growing concerns regarding potential negative effects of technological progress on labour demand. This report uses harmonised and comparable data from 13 countries spanning the last two decades to comprehensively analyse how productivity growth affects employment dynamics at various levels of aggregation. The study's findings highlight a positive correlation between productivity growth and employment as well as wage growth, both at the firm level and on a broader scale. This outcome arises from counteracting mechanisms and heterogeneous dynamics across different groups of firms. The findings have relevant policy implications: productivity is not just an isolated key economic objective, but well-designed and complementary policies can also help convert technological and organisational change into higher employment and wage growth.

DOI: 10.1787/99bede51-en

URL: lizenzpflichtig

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A portrait of AI adopters across countries : Firm characteristics, assets’ complementarities and productivity (2023)

Calvino, Flavio [VerfasserIn] ; Fontanelli, Luca [MitwirkendeR]

Paris : OECD Publishing

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Language: English

Pages: 1 Online-Ressource (85 p.) , 21 x 28cm.

Series Statement: OECD Science, Technology and Industry Working Papers no.2023/02

Keywords: Science and Technology ; Industry and Services

Abstract: This report analyses the use of artificial intelligence (AI) in firms across 11 countries. Based on harmonised statistical code (AI diffuse) applied to official firm-level surveys, it finds that the use of AI is prevalent in ICT and Professional Services and more widespread across large – and to some extent across young – firms. AI users tend to be more productive, especially the largest ones. Complementary assets, including ICT skills, high-speed digital infrastructure, and the use of other digital technologies, which are significantly related to the use of AI, appear to play a critical role in the productivity advantages of AI users.

DOI: 10.1787/0fb79bb9-en

URL: lizenzpflichtig

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Identifying artificial intelligence actors using online data (2023)

Dernis, Hélène [VerfasserIn] ; Calvino, Flavio [MitwirkendeR] ; Moussiegt, Laurent [MitwirkendeR] ; [et al.]

Paris : OECD Publishing

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Language: English

Pages: 1 Online-Ressource (50 p.) , 21 x 28cm.

Series Statement: OECD Science, Technology and Industry Working Papers no.2023/01

Keywords: Science and Technology ; Industry and Services

Abstract: This paper uses information collected and provided by GlassAI to analyse the characteristics and activities of companies and universities in Canada, Germany, the United Kingdom and the United States that mention keywords related to Artificial Intelligence (AI) on their websites. The analysis finds that those companies tend to be young and small, mainly operate in the information and communication sector, have AI at the core of their business, and aim to provide customer solutions. It is noteworthy that the types of AI-related activities reported by them vary across sectors. Additionally, although universities are concentrated in and around large cities, this is not necessarily reflected in the intensity of AI-related activities. Taken together, this novel and timely evidence informs the debate on the most recent stages of digital transformation of the economy.

DOI: 10.1787/1f5307e7-en

URL: lizenzpflichtig

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Identifying and characterising AI adopters : A novel approach based on big data (2022)

Calvino, Flavio [VerfasserIn] ; Samek, Lea [MitwirkendeR] ; Squicciarini, Mariagrazia [MitwirkendeR] ; [et al.]

Paris : OECD Publishing

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Language: English

Pages: 1 Online-Ressource (67 p.) , 21 x 28cm.

Series Statement: OECD Science, Technology and Industry Working Papers no.2022/06

Keywords: Science and Technology ; Industry and Services

Abstract: 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.

DOI: 10.1787/154981d7-en

URL: lizenzpflichtig

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A taxonomy of digital intensive sectors (2018)

Calvino, Flavio [VerfasserIn] ; Criscuolo, Chiara [VerfasserIn] ; Marcolin, Luca [VerfasserIn] ; [et al.]

Paris : OECD Publishing

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Language: English

Pages: 1 Online-Ressource (circa 48 Seiten) , Illustrationen

Series Statement: OECD science, technology and industry working papers 2018, 14

Series Statement: OECD science, technology and industry working papers

Keywords: Vereinte Nationen ; 2001 - 2015 ; Industrie ; Klassifikation ; Digitalisierung ; Industrie 4.0 ; Science and Technology ; Industry and Services ; Amtsdruckschrift ; Graue Literatur

Abstract: This study proposes a taxonomy of sectors according to the extent to which they have gone digital. The taxonomy accounts for some of the key facets of the digital transformation, and recognises that sectors differ in their development and adoption of the most advanced “digital” technologies, in the human capital needed to embed them in production and in the extent to which digital tools are used to deal with clients and suppliers. The indicators used to classify 36 ISIC revision 4 sectors over the period 2001-15 are: share of ICT tangible and intangible (i.e. software) investment; share of purchases of intermediate ICT goods and services; stock of robots per hundreds of employees; share of ICT specialists in total employment; and the share of turnover from online sales. The study further proposes an overall summary indicator of the digital transformation in sectors which encompasses all the considered dimensions.

DOI: 10.1787/f404736a-en

URL: Volltext (lizenzpflichtig)

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