AI Recommendation Systems Supporting the Circular Economy and Zero-Waste Practices

The growing integration of artificial intelligence (AI) recommendation systems into sustainable development initiatives offers new avenues for promoting circular economy and zero-waste practices. The objective of this study is to identify and analyse the key motivational factors that influence consumers’ engagement with AI-driven sustainability tools. By employing the Kano model, the study categorises user expectations and satisfaction with various AI features supporting sustainable consumption. A large-scale, cross-cultural survey was conducted among 11,294 participants from Poland, Norway, and Italy to examine the roles of environmental awareness, perceived transparency, economic incentives, and trust in AI technology. The findings reveal that features such as real-time waste tracking, lifecycle-based product recommendations, and integration with sustainability certifications are perceived as essential by consumers. Moreover, hybrid recommendation systems that combine AI with human advisory support significantly enhance trust and reduce resistance. Despite growing acceptance, concerns related to algorithmic opacity and data privacy remain barriers to widespread adoption. The study contributes to our understanding of how AI can effectively support consumer transitions towards circular economy behaviours and highlights the need for ethical, transparent, and user-centred AI design. Future research should incorporate objective impact metrics, expand to other geographic regions, and further explore the social and ethical dimensions of AI in sustainability.