AI-Driven Environmental, Social, and Governance (ESG) and Economic Optimization for Circular Economy and Sustainable Waste Reduction
DOI:
https://doi.org/10.70670/sra.v4i1.2272Keywords:
Artificial Intelligence, Circular Economy, Environmental, Social, and Governance (ESG); Sustainability, Waste ReductionAbstract
Innovative solutions are needed for a successful transition to a circular economy and new frameworks for sustainable waste management. These solutions must balance environmental, social, and governance responsibilities with sustainable profitability. This research examines the possibility of introducing an AI-based ESG and economic optimization framework further to advance circular economy principles and sustainable waste management practices. The framework was developed on the basis of a quantitative research methodology that utilized sustainability and operational datasets from manufacturing, energy, retail, and waste management. Several Machine Learning techniques, including Random Forest, XGBoost, and Artificial Neural Networks (ANN), were used to forecast waste and measure the potential for improvement in the recovery of value from resources. Of the models developed, ANN produced results with the greatest accuracy in prediction (R² = 0.95). Correlation analysis indicated a positive relationship between ESG, circularity, economic and recycling outcomes. Substantial AI-related improvements to sustainability were noted through the application of multi-objective optimization, which included a 32.4% reduction in waste, a 29.8% increase in recycling, a 29.0% increase in the efficiency of resource utilization, and a 27.9% reduction in carbon footprint, along with a 27.0% increase in annual profit. This research, therefore, demonstrates that the integration of AI, ESG, and circular economy principles simultaneously improves the environmental bottom line, the efficient use of resources, and the economy’s buffer capacity and resilience. This research aims to further the scope of sustainability-related research and offer a comprehensive framework for intelligent waste management and the sustainable development of organizations.
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