The need for improved and environmentally friendly sustainable packaging materials with exceptional physical, mechanical, and barrier qualities is growing. The existing industrial packaging materials primarily use non-biodegradable plastics and other raw materials with limited recyclability and has serious consequences toward raised carbon footprints. Therefore, the integration of artificial intelligence (AI) in the sustainable packaging industry is fundamentally changing how things are packaged and distributed, with emerging materials and technologies that promote safety, quality, and sustainability. Many AI-based tools are being used or evaluated for packaging systems, including (but not limited to) machine learning (ML), deep learning (DL), sensors for monitoring, predictive analytics, and generative models for accurate predictions of shelf life, automated identification of defects or contamination, traceability or authentication of a product’s origins, optimal material selection for barrier and environmental properties, and more sustainable packaging designs. This article investigates various applications of AI for sustainable packaging for various applications. Moreover, various challenges in practice data heterogeneity, model generalizability, and scalability showing the importance strong and well-designed AI framework are necessary to implement effectively are also discussed. Overall, the sustainable-packaging sector can expect that AI innovations will improve productivity, food safety and waste management.
Mann et al. (2026) studied this question.