This paper presents an AI-powered Data Loss Prevention (DLP) approach for detecting and mitigating sensitive data leaks in cloud environments. It applies deep learning and NLP techniques for identifying sensitive data and machine learning–based behavioral analytics for anomaly detection. The study includes case analyses of AWS Macie and Google Cloud DLP and discusses scalability, compliance, and implementation challenges.