Artificial intelligence for agricultural supply chain risk management: Preliminary prioritizations and constraints for the deployment of AI in food chains assessed by CGIAR scientists
This paper seeks to propose priorities and support the integration of artificial intelligence (AI) in agricultural supply chains for the next ten years (2020-2030), with the aim of reducing supply chain vulnerabilities and contribute to global food security. Qualitative interviews with food chains a...
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| Format: | Informe técnico |
| Language: | Inglés |
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CGIAR Big Data Platform
2020
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| Online Access: | https://hdl.handle.net/10568/108402 |
| _version_ | 1855522375881195520 |
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| author | Tzachor, Asaf |
| author_browse | Tzachor, Asaf |
| author_facet | Tzachor, Asaf |
| author_sort | Tzachor, Asaf |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | This paper seeks to propose priorities and support the integration of artificial intelligence (AI) in agricultural supply chains for the next ten years (2020-2030), with the aim of reducing supply chain vulnerabilities and contribute to global food security. Qualitative interviews with food chains and food security specialists from the FAO, the World Bank, CGIAR, WFP and the University of Cambridge, and an exploratory quantitative survey of 72 CGIAR scientists and researchers are used to derive integrated assessments of the vulnerability of different phases of supply chains and the ease of AI adoption and deployment in these phases. The integrated assessments are structured across food chains in developed and developing regions. The research shows that respondents expect the vulnerability to risks of all but one supply chain phases to increase over the next ten years. Importantly, where the integration of AI will be most desirable, in highly vulnerable supply chain phases in developing countries, the potential for AI integration is estimate to be limited. |
| format | Informe técnico |
| id | CGSpace108402 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2020 |
| publishDateRange | 2020 |
| publishDateSort | 2020 |
| publisher | CGIAR Big Data Platform |
| publisherStr | CGIAR Big Data Platform |
| record_format | dspace |
| spelling | CGSpace1084022020-06-09T01:02:20Z Artificial intelligence for agricultural supply chain risk management: Preliminary prioritizations and constraints for the deployment of AI in food chains assessed by CGIAR scientists Tzachor, Asaf artificial intelligence agriculture supply chains supply change management risk factors food security This paper seeks to propose priorities and support the integration of artificial intelligence (AI) in agricultural supply chains for the next ten years (2020-2030), with the aim of reducing supply chain vulnerabilities and contribute to global food security. Qualitative interviews with food chains and food security specialists from the FAO, the World Bank, CGIAR, WFP and the University of Cambridge, and an exploratory quantitative survey of 72 CGIAR scientists and researchers are used to derive integrated assessments of the vulnerability of different phases of supply chains and the ease of AI adoption and deployment in these phases. The integrated assessments are structured across food chains in developed and developing regions. The research shows that respondents expect the vulnerability to risks of all but one supply chain phases to increase over the next ten years. Importantly, where the integration of AI will be most desirable, in highly vulnerable supply chain phases in developing countries, the potential for AI integration is estimate to be limited. 2020 2020-06-08T08:07:45Z 2020-06-08T08:07:45Z Report https://hdl.handle.net/10568/108402 en Open Access application/pdf CGIAR Big Data Platform Tzachor, Asaf (2020). Artificial intelligence for agricultural supply chain risk management: Preliminary prioritizations and constraints for the deployment of AI in food chains assessed by CGIAR Scientists. CGIAR Big Data Platform. 26 p. |
| spellingShingle | artificial intelligence agriculture supply chains supply change management risk factors food security Tzachor, Asaf Artificial intelligence for agricultural supply chain risk management: Preliminary prioritizations and constraints for the deployment of AI in food chains assessed by CGIAR scientists |
| title | Artificial intelligence for agricultural supply chain risk management: Preliminary prioritizations and constraints for the deployment of AI in food chains assessed by CGIAR scientists |
| title_full | Artificial intelligence for agricultural supply chain risk management: Preliminary prioritizations and constraints for the deployment of AI in food chains assessed by CGIAR scientists |
| title_fullStr | Artificial intelligence for agricultural supply chain risk management: Preliminary prioritizations and constraints for the deployment of AI in food chains assessed by CGIAR scientists |
| title_full_unstemmed | Artificial intelligence for agricultural supply chain risk management: Preliminary prioritizations and constraints for the deployment of AI in food chains assessed by CGIAR scientists |
| title_short | Artificial intelligence for agricultural supply chain risk management: Preliminary prioritizations and constraints for the deployment of AI in food chains assessed by CGIAR scientists |
| title_sort | artificial intelligence for agricultural supply chain risk management preliminary prioritizations and constraints for the deployment of ai in food chains assessed by cgiar scientists |
| topic | artificial intelligence agriculture supply chains supply change management risk factors food security |
| url | https://hdl.handle.net/10568/108402 |
| work_keys_str_mv | AT tzachorasaf artificialintelligenceforagriculturalsupplychainriskmanagementpreliminaryprioritizationsandconstraintsforthedeploymentofaiinfoodchainsassessedbycgiarscientists |