In the rapidly growing global markets, supply chains are facing issues like fluctuating demand, disruptions, and sustainability pressures, making the supply chains volatile and complex. Traditional supply chain management methods fail to address the dynamics behind these issues. This paper introduces a framework designed to enable traditional OR models with dynamic adaptability, resilience, and sustainability capabilities. This framework combines existing Enterprise Resource Planning (ERP) and Robotic Process Automation (RPA) systems with AI. By leveraging AI-enabled OR models and declarative modeling, the study introduces a framework for complex decision-making. The proposed framework will dynamically identify disruptions and inefficiencies based on various parameters, and with the help of Answer Set Programming (ASP), the model will be able to make decisions based on different scenarios and provide an optimized solution. This framework will overcome the lack of real-time responsiveness in supply chains. The proposed framework will enhance operational efficiency and make supply chains adaptive, resilient, and sustainable.