In 2025 Food and Beverage Manufacturing sector is under growing pressure to implement practices of circular economy, which have made the demand for brilliant and sustainable waste management solutions much higher. The study focuses on the role of artificial intelligence in waste management through green digitalization in terms of both efficiency and sustainable business performance. A quantitative research design was adopted where primary data was collected from Food and Beverage manufacturing firms and analyzed using partial least squares structural equation modeling (SEM-PLS). The model indicated the relationships that exist between AI adoption, smart waste management efficiency, community attitude, and sustainable business performance. The findings indicate that the adoption of AI has a significant positive impact on the accuracy of waste sorting, efficiency of recycling, and overall environmental and technical performance (p <0.001). Smart waste management partially mediated the relationship between AI adoption and sustainable business performance, while community attitude moderates the effectiveness of AI enabled waste systems. The study concludes that AI-driven green digitalization is one of the major factors contributing to the success of circular economy and sustainable manufacturing practices. The findings also provide practical insights for managers and policymakers who want to set up intelligent and sustainable waste management ecosystems in the food and beverages sector.

Food and Beverage Manufacturing sector faces pressure to implement circular economy, increasing the need for sustainable waste management solutions. The study examines artificial intelligence in waste management efficiency and sustainable performance. A quantitative research design data was collected from firms and analyzed with (SEM-PLS). AI adoption, smart waste management efficiency, community attitude, and sustainable business performance. The findings indicate that the adoption of AI has a significant positive impact on the accuracy of waste sorting, recycling efficiency, and environmental performance (p <0.001). Smart waste management partially mediated the link between AI adoption and sustainable business performance, while community attitude moderates the effectiveness of AI-based waste systems. The study concludes that AI-driven green digitalization is a key factor supporting circular economy and sustainable manufacturing. The findings provide practical insights for managers and policymakers seeking to develop intelligent and sustainable waste management ecosystems in the food and beverage sector..