Optimizing Sustainable Supply Chains: Integrating Environmental Concerns and Carbon Footprint Reduction through AI-Enhanced Decision-Making in the USA

Abstract

In today's dynamic business environment, sustainable supply chain management (SSCM) is emerging as a critical factor for organizations aiming to balance profitability with environmental responsibility. This study delves into integrating artificial intelligence (AI) technologies to optimize sustainable supply chains and foster environmentally conscious decision-making processes. The research demonstrates their capability to accurately predict supplier and consumer categories by applying advanced machine learning techniques, specifically Random Forest and Neural Networks. The AI-driven models exhibited superior performance compared to conventional methods, emphasizing their potential to enhance supply chain efficiency while minimizing environmental impact. The findings indicate that AI can be pivotal in revolutionizing supply chain operations by providing actionable insights, optimizing resource allocation, and reducing carbon footprint. As businesses worldwide face increasing pressure to adopt sustainable practices, integrating AI in supply chain management offers a promising pathway to drive eco-friendly initiatives, improve operational efficiency, and meet stakeholder expectations for environmental stewardship.