Artificial intelligence, its diffusion and uses in manufacturing:
Using artificial intelligence (AI) and other digital technologies in manufacturing, and other areas of production, is essential for raising labour productivity growth in OECD countries. AI can increase productivity in manufacturing in many ways, from reducing machine downtime to managing supply-chai...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Paris
OECD Publishing
2021
|
| Schriftenreihe: | Going Digital Toolkit Notes
no.12 |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | Using artificial intelligence (AI) and other digital technologies in manufacturing, and other areas of production, is essential for raising labour productivity growth in OECD countries. AI can increase productivity in manufacturing in many ways, from reducing machine downtime to managing supply-chains. However, even in the most advanced economies, the use of AI in manufacturing is limited. This Going Digital Toolkit note discusses the challenges faced by manufacturers in adopting AI and what these imply for the design of policies, including for: skills; institutions for technology diffusion; connectivity; research and manufacturing linkages; computing infrastructure; and, programme evaluation. The Annex provides examples of policy initiatives in a variety of countries |
| Beschreibung: | 1 Online-Ressource (33 Seiten) |
| DOI: | 10.1787/249e2003-en |
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| spelling | Nolan, Alistair Verfasser aut Artificial intelligence, its diffusion and uses in manufacturing Alistair, Nolan Paris OECD Publishing 2021 1 Online-Ressource (33 Seiten) txt rdacontent c rdamedia cr rdacarrier Going Digital Toolkit Notes no.12 Using artificial intelligence (AI) and other digital technologies in manufacturing, and other areas of production, is essential for raising labour productivity growth in OECD countries. AI can increase productivity in manufacturing in many ways, from reducing machine downtime to managing supply-chains. However, even in the most advanced economies, the use of AI in manufacturing is limited. This Going Digital Toolkit note discusses the challenges faced by manufacturers in adopting AI and what these imply for the design of policies, including for: skills; institutions for technology diffusion; connectivity; research and manufacturing linkages; computing infrastructure; and, programme evaluation. The Annex provides examples of policy initiatives in a variety of countries Science and Technology Industry and Services https://doi.org/10.1787/249e2003-en Verlag kostenfrei Volltext |
| spellingShingle | Nolan, Alistair Artificial intelligence, its diffusion and uses in manufacturing Science and Technology Industry and Services |
| title | Artificial intelligence, its diffusion and uses in manufacturing |
| title_auth | Artificial intelligence, its diffusion and uses in manufacturing |
| title_exact_search | Artificial intelligence, its diffusion and uses in manufacturing |
| title_exact_search_txtP | Artificial intelligence, its diffusion and uses in manufacturing |
| title_full | Artificial intelligence, its diffusion and uses in manufacturing Alistair, Nolan |
| title_fullStr | Artificial intelligence, its diffusion and uses in manufacturing Alistair, Nolan |
| title_full_unstemmed | Artificial intelligence, its diffusion and uses in manufacturing Alistair, Nolan |
| title_short | Artificial intelligence, its diffusion and uses in manufacturing |
| title_sort | artificial intelligence its diffusion and uses in manufacturing |
| topic | Science and Technology Industry and Services |
| topic_facet | Science and Technology Industry and Services |
| url | https://doi.org/10.1787/249e2003-en |
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