Xingsi Xue, Himanshu Dhumras, Garima Thakur, Varun Shukla
The growing connection between AI and eco-friendly materials has made it possible to completely change the way things are made today so that they are smart, resourceful, and safe. The research investigates the potential of AI optimization in advancing the utilization of sustainable materials to enhance energy efficiency and diminish waste production, operational costs, and carbon footprint, in response to the imperative to alleviate climate change effects, lower production expenses, and preserve natural resources. This paper proposes a new concept that intertwines AI predictive analytics and sustainability material selection based on the extensive use of case studies and synthetic datasets to test the use scenario. The results show a significant increase in efficiency based on performance indicators and the future possibilities of waste and zero manufacturing and the circular economy. The findings provide actionable insights for policymakers, industry leaders, and researchers seeking to integrate advanced digital intelligence with eco-innovative production strategies, thereby paving the way for scalable, adaptable, and future-ready manufacturing ecosystems.