Circular bioeconomy using artificial intelligence: valorizing agri‐food waste into sustainable bioplastics

Abstract This paper explores the current landscape of bioplastics, focusing on the utilization of agri‐food waste (AFW) as a valuable resource for their production using Artificial Intelligence (AI) and machine learning (ML) techniques. The processing methodology for converting such waste into bioplastics is elaborated, encompassing various innovative techniques and technologies enhanced by AI‐driven optimization. Specific examples of agri‐food waste utilized for bioplastic production, including bagasse, beer spent grain, tomato pomace, olive pomace, and rice husk, are included, showcasing the diverse range of feedstocks available for sustainable manufacturing practices. AI applications span multiple stages of the AFW‐to‐bioplastic value chain, including feedstock characterization via machine learning‐based composition analysis, fermentation process control using reinforcement learning and neural networks, property prediction through ensemble tree‐based models, and formulation design using genetic algorithms and generative adversarial networks. The potential applications of bioplastics across a multitude of sectors, including packaging, agriculture, textiles, 3D printing, medical, consumer goods, and electronics, are thoroughly examined. The industrial potential of utilizing agri‐food waste for bioplastic production is elucidated through techno‐economic assessments and digital twin technologies. From a circular bioeconomy perspective, it is essential to consider the importance of waste prevention, resource valorization, sustainable production practices, consumption patterns, and waste management strategies in the bioplastics industry, all of which are increasingly optimized using AI‐driven tools. Finally, this work addresses the challenges and future directions in the field of bioplastics, identifying areas for further research and development, including the standardization of AI models and the scaling of intelligent manufacturing systems. By highlighting the untapped potential of agri‐food waste for bioplastic production and the transformative role of artificial intelligence throughout the value chain, this review aims to contribute to the advancement of sustainable, data‐driven, and resource‐efficient solutions in the plastics industry. © 2026 Society of Chemical Industry (SCI).