Integrating Artificial Intelligence with Digital Twin technologies fosters creating smart connected eco-friendly Intelligent manufacturing systems ecosystems in manufacturing positively. The use of self-learning algorithms to optimize systems in real-time marks a considerable advancement compared to older systems characterized by static control logic automation. This chapter discusses the convergence of AI and digital twins in the emerging frontiers of manufacturing such as additive manufacturing, microwave hybrid heating and precision machining, the foundational principles of the implementation architectures, systemic integration and the industrial impact. The use of closed control loops in convolutional processes with machine learning and reinforcing algorithms facilitates defect prediction, parameter fine-tuning and control, and quality assurance. Process monitoring with AI, as well as the virtual modeling of processes in Singh et al. (2024) and Zafar et al. (2022), provides enhanced efficiency, reduced waste, and sustainable manufacturing. As the manufacturing sector adopts Industry 5.0, a new and unique phase in the evolution of manufacturing technologies is the collaboration of the AI and the Ethical Human—the partner of social and environmental custodianship. This chapter outlines a vision in which manufacturing systems automate production processes, perceive and learn, and eventually develop cognitive control systems that achieve and maintain sustainable excellence.