HARNESSING ARTIFICIAL INTELLIGENCE IN AGRICULTURE: IN-DEPTH CASE STUDIES AND STRATEGIC INSIGHTS
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Abstract
Agriculture, which employs over 25% of the global workforce and feeds a growing population, faces increasing challenges due to climate change, resource constraints, and declining productivity. In response, Artificial Intelligence (AI) has emerged as a powerful tool to modernize farming practices, offering data-driven solutions for more efficient and sustainable agriculture. This paper explores the application of AI in agriculture through five real-world case studies from India, Israel, the United States, Japan, and the Netherlands. These studies demonstrate how technologies like machine learning, computer vision, drones, and IoT are being used for pest detection, precision irrigation, yield prediction, crop monitoring, and livestock health management. The paper highlights key outcomes, identifies common challenges, and offers recommendations to enhance AI adoption and impact in global agriculture
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