ABSTRACT The following paper attempts to research the utilization of Artificial Intelligence (AI) and Machine Learning (ML) in the scalability and dependability improvement of enterprise applications by solving pooled database connection problems. Along with intelligent monitoring with anomaly detection and forecasting models, factors such as self-healing systems and automated failover mechanisms significantly increased database system connection stability and efficiency. The research shows employing simulations and live precise case studies for foreseeing and fixing possible problems, thereby minimizing time losses and improving the system's dependability. Furthermore, the research identifies technical and operational issues related to implementing these solutions and the best practices for their solutions, making readers or users see the possibility of using AI and ML to enhance enterprise applications' performance and reliability. The findings help to expand the knowledge base in managing and building advanced technologies as flexible enterprise applications.