This paper explores the transformative role of artificial intelligence (AI) in semiconductor manufacturing, focusing on its applications in enhancing yield, quality control, and process automation. As semiconductor manufacturing becomes increasingly capital-intensive and complex, the integration of AI technologies is essential for managing these challenges. This paper discusses how AI methodologies, including machine learning, computer vision, and neural networks, can significantly improve defect detection, predictive maintenance, and real-time process monitoring, leading to enhanced production efficiency and quality control Furthermore, the paper highlights the critical need for flexibility and adaptability in manufacturing processes, driven by the diversification of products and the demand for more autonomous operations. AI serves as a key leverage element for digitizing manufacturing processes and optimizing operations as technology advances toward nanometer-scale semiconductor nodes