Artificial Intelligence for Sustainable Agribusiness: Innovations and Challenges

Abstract

The integration of artificial intelligence (AI) in sustainable agribusiness is examined in this research, with particular attention paid to robots, supply chain management, and precision agriculture. AI analyzes a variety of datasets, maximizes resource utilization, forecasts pest outbreaks and production changes, and allows for data-driven decision-making. AI improves supply chain management by lowering food loss, streamlining logistics, and guaranteeing on-time delivery. Robotics powered by AI revolutionize labor-intensive processes, increasing output while reducing the need for chemicals. Notwithstanding its revolutionary potential, issues like data privacy and skill shortages still need to be resolved. Developing AI solutions that are inclusive and appropriate to a given context requires interdisciplinary collaboration. Improved equity and transparency are anticipated from developments in federated learning and explainable AI. All things considered, artificial intelligence (AI) presents hitherto unseen chances to advance sustainability along the agriculture value chain, building food system resilience and equity.

Keywords: artificial intelligence, sustainability, efficiency, agribusiness, resilience, functionality

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