The integration of Artificial Intelligence (AI) and Machine Learning (ML) into semiconductor manufacturing has revolutionized defect detection and yield improvement processes. AI and ML algorithms analyze vast amounts of data generated during fabrication to enhance quality control, reduce defects, and optimize production yields. This paper provides an overview of AI and ML applications in semiconductor manufacturing, focusing on their roles in defect detection methodologies, process optimization, and yield enhancement strategies. Case studies and current advancements illustrate the transformative impact of AI and ML technologies on semiconductor fabrication, highlighting their potential to drive future advancements in microelectronics.