The semiconductor industry plays a vital role in driving technological advancements, and the incorporation of AI (Artificial Intelligence) can greatly enhance its efficiency and productivity. Through optimizing material usage and reducing defects, AI can significantly reduce costs and enhance production efficiency and product quality. However, despite the increasing interest in AI applications in the semiconductor industry, comprehensive reviews are lacking to systematically analyze existing research and identify the challenges and opportunities in this field. This review aims to bridge this gap by providing a thorough overview of AI-driven techniques in optimizing semiconductor manufacturing and offering valuable insights for future research directions. Initially, the review intends to explore and analyze the diverse applications of AI in optimizing semiconductor manufacturing processes. By examining existing research and real-world case studies, this review will provide insights into the specific AI techniques utilized and their impact on different stages of semiconductor manufacturing. By pinpointing these challenges, the review will contribute to a better understanding of the current limitations and areas that require improvement. Additionally, suitable suggestions and recommendations will be provided to address these challenges, ultimately assisting future researchers in advancing the field. Overall, this review paper will contribute to the existing body of knowledge by comprehensively evaluating how AI-driven techniques can revolutionize semiconductor manufacturing. By uncovering the various applications of AI, identifying existing drawbacks, and providing appropriate suggestions, this review aims to guide future researchers and shed light on research conducted in this area. Ultimately, these efforts will foster advancements in semiconductor manufacturing processes.