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  • 1
    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.
    URL: Volltext  (lizenzpflichtig)
    URL: Volltext  (lizenzpflichtig)
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  • 2
    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.
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