Artificial intelligence (AI) is playing a transformative role in the development of sustainable manufacturing systems by optimizing processes, reducing waste, and increasing efficiency. AI-based predictive analytics helps monitor and manage resources in real time, ensuring minimal energy consumption and efficient use of materials. Machine learning models analyze large data sets to predict equipment failures, thus enabling proactive maintenance and extending machine life. Autonomous systems, including robotics, streamline manufacturing processes, reduce human error, and support precision manufacturing. AI increases supply chain sustainability by optimizing logistics, reducing carbon footprint, and supporting circular economy practices through waste minimization and resource recycling. Additionally, in the energy sector, AI optimizes grid operations and integrates renewable energy sources such as wind and solar, anticipating fluctuations in energy supply and demand. This article illustrates how AI is significantly contributing to the development of environmentally friendly, resilient, and efficient manufacturing systems aligned with sustainable development goals. This allows for more precise determination of directions for further development of research and economic practice in this area.