International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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The Impact of Artificial Intelligence on the U.S. Grain Storage Chain

Author(s) Rafael Elias Venturini
Country United States
Abstract The application of artificial intelligence (AI) in the grain storage chain in the United States has led to significant changes in the operational and financial efficiency of the agricultural sector. AI-based solutions, such as machine learning algorithms for stock forecasting and transportation route optimization, have enabled managers to reduce costs and maximize profitability. Accurate grain demand forecasting and logistical optimization allow for more agile adaptation to market fluctuations, making companies more competitive globally. Furthermore, AI has proven essential in automating processes that prevent losses and improve the quality of stored grains. Intelligent monitoring of storage conditions, such as temperature and humidity, helps prevent deterioration and enhances product preservation. Technologies like computer vision and big data analysis have also contributed to improving both production and financial management by providing valuable insights into operational costs, profit margins, and opportunities to reduce expenses. AI not only optimizes operational processes but also shapes the business models of the agricultural sector. As more companies adopt these technologies, they become more resilient to external crises, such as the COVID-19 pandemic. Technological advancement, combined with the growing demand for more sustainable agricultural practices, opens up new possibilities for the future of farming. Emerging trends in AI promise to further expand the transformative potential, creating a smarter, safer, and more sustainable agricultural sector.
Keywords Artificial Intelligence (AI), Grain Storage, Machine Learning, Agricultural Efficiency, Supply Chain Optimization.
Field Business Administration
Published In Volume 7, Issue 1, January-February 2025
Published On 2025-02-28
DOI https://doi.org/10.36948/ijfmr.2025.v07i01.38037
Short DOI https://doi.org/g86w4j
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