Artificial intelligence (AI) is currently transforming the polymer lifecycle, from materials discovery and design to manufacturing and recycling processes. In this review, we will discuss the undergoing paradigm shift from conventional labor-intensive processes to machine learning and data driven automation, including the key machine learning models and techniques being applied across diverse polymer science application areas. Significant limitations and opportunities in AI-driven polymer manufacturing exist in data availability and model interpretability.