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The food industry uses artificial intelligence (AI) to enhance food quality and security while proposing significant capital savings and resource optimization. Additionally, understanding machine learning (ML) techniques is essential for their effectiveness. Therefore, the gap lies in examining how industrial automation plays a crucial role in successfully implementing this new technology. To address this gap, this review explores AI’s potential to significantly enhance food safety by creating a more transparent supply chain management system. Therefore, the primary focus is exploring potential AI applications, such as artificial neural networks (ANN) and convolutional neural networks (CNN), for detecting food and agricultural product quality. The primary goal of utilizing these AI applications is to reduce human intervention and effort. These methodologies have advantages and disadvantages regarding theoretical knowledge and model interpretation.