Demand Driven Material Requirements Planning (DDMRP) is an inventory management method that aims to optimize inventory levels in response to fluctuating demand. The performance of DDMRP relies on several key parameters that significantly influence its effectiveness. Integrating DDMRP with artificial intelligence (AI) can greatly enhance its performance. Artificial intelligence (AI) includes advanced technologies such as machine learning, which incorporates various tools like Reinforcement Learning (RL), Deep Learning (DL), and Deep Reinforcement Learning (DRL). These technologies enable AI to analyze data, automate tasks, and solve complex problems, transforming industries and driving innovation. DRL can dynamically adjust critical parameters such as the variability factor (FV) and lead time factor (FLT). Through a process of trial and error, a DRL agent learns to minimize on-hand inventory (OH) while maximizing on-time delivery (OTD). This approach allows for a more responsive and adaptive inventory management system, enabling companies to reduce inventory levels and better meet customer demand.