In the rapidly evolving digital landscape, securing data access and automating data exchanges are paramount to safeguarding sensitive information and enhancing operational efficiency. This paper presents an AI-based system designed to address these challenges through advanced techniques in data security and automation. The proposed system leverages machine learning algorithms to dynamically manage and enforce access controls, predict potential security threats, and adapt to evolving security needs. Additionally, it utilizes intelligent automation to facilitate seamless and secure data exchanges across diverse platforms and environments. By integrating AI-driven decision-making and real-time monitoring, the system aims to reduce human error, streamline operations, and bolster overall data protection. The effectiveness of this approach is evaluated through a series of case studies and simulations, demonstrating its potential to revolutionize data security practices.