Challenges Facing Artificial Intelligence Adoption during COVID-19 Pandemic: An Investigation into the Agriculture and Agri-Food Supply Chain in India

Abstract

The coronavirus (COVID-19) pandemic has witnessed a significant loss for farming in India due to restrictions on movement, limited social interactions and labor shortage. In this scenario, Artificial Intelligence (AI) could act as a catalyst for helping the farmers to continue with their farming. This study undertakes an analysis of the applications and benefits of AI in agri-food supply chain, while highlights the challenges facing the adoption of AI. Data were obtained from 543 farmers in Odisha (India) through a survey, and then interpreted using “Interpretive Structural Modelling (ISM)”; MICMAC; and “Step-Wise-Assessment and Ratio-Analysis (SWARA)”. Response time and accuracy level; lack of standardization; availability of support for big data; big data support; implementation costs; flexibility; lack of contextual awareness; job-losses; affordability issues; shortage of infrastructure; unwillingness of farmers; and AI safety-related issues are some challenges facing the AI adoption in agri-food supply chain. Implications were drawn for farmers and policy makers.

Turn‐key research in food processing and manufacturing for reducing the impact of climate change

“…Machine Learning (ML) tools, utilising data from Sentinel satellites download over 20 petaBytes of openaccess data daily (Brown et al, 2022;Muduli et al, 2023).…”

“…The FSC is facing immense pressure to improve sustainability, food security, and resilience due to climate change, a growing global population, and various disasters such as floods, droughts, earthquake, conflicts, and pandemics (Jagtap et al, 2022;Mishra et al, 2023). Consequently, all stakeholders within the FSC, including producers, distributors, manufacturers, retailers, consumers, and policymakers, are actively seeking novel solutions to enhance the sustainability, resilience and security of the food system.…”