A Supply Chain Approach Highlighting the Use of Artificial Intelligence and Computer Vision to Improve the Efficiency of Food Supply Chains in the United States

Advanced technological solutions have become necessary to manage the complicated food supply chains within the United States because they enhance operational efficiency while minimizing waste and optimizing logistical operations. The supply chain management industry benefits from artificial intelligence-based computer vision, which has become a revolutionary tool. This research investigates how computer vision algorithms specializing in fruit and garlic count and piece selection processes optimize supply chain efficiency in multiple ways. These algorithms achieve better inventory control, enhanced accuracy, and decreased human mistakes through their combination of machine-learning models and real-time object detection with automated quality assessment. The research discusses essential deployment methods, key barriers, and financial advantages of adopting computer vision technology in food supply systems. This paper presents quantitative evidence through case studies and experimental findings that validate the results of computer vision applications. Systematic research enables this study to offer both strategic knowledge about AI-driven supply chains of the future and an implementation model that industries can utilize.