Food safety is essential to our survival and well-being. The intricacy and sophistication of today's food systems necessitate upholding the strictest food safety regulations and employing state-of-the-art technologies to shield consumers from foodborne illness while lowering the possibility that food companies will suffer millions of dollars in recall expenses and potential harm to their brand. This review paper explores the burgeoning integration of artificial intelligence (AI) in the food industry, focusing on its applications in various domains. The study encompasses the utilization of machine learning (ML), deep learning (DL), computer vision, and image processing techniques. The review provides a holistic overview of AI's transformative impact on the food sector's production and quality control processes. The paper searches through the specific applications of AI in dairy products, meat products, fruits, vegetables, and bakery items. Each category examines the role of ML and DL algorithms, highlighting their efficacy in optimizing production efficiency, quality assurance, and supply chain management. Computer vision and image processing techniques are explored for their ability to enhance product inspection and quality control, ensuring compliance with industry standards.