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 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.

Bibliographic Details

Main Author:	Tzachor, Asaf
Format:	Report biblioteca
Language:	English
Published:	CGIAR Big Data Platform 2020
Subjects:	artificial intelligence, agriculture, supply chains, supply change management, risk factors, food security,
Online Access:	https://hdl.handle.net/10568/108402
Tags:	Add Tag No Tags, Be the first to tag this record!