The Role of Artificial Intelligence in Preventing Data Leakage in the Digital Era: A Literature-Based Review

Artificial Intelligence (AI) is increasingly used to protect sensitive information in modern digital environments. As organizations adopt cloud services, SaaS applications, and AI tools, traditional rule-based Data Loss Prevention (DLP) mechanisms often struggle to detect complex and novel forms of data leakage. This paper provides a literature-based review of the role of AI in preventing data leakage in the digital era. It introduces key concepts related to data security, data leakage, and DLP, then explains how AI techniques are applied to enhance data classification, support user and entity behavior analytics, monitor data flows in real time, and safeguard data within AI systems. The review highlights several benefits of AI-driven DLP, including improved detection accuracy, better scalability, and more context-aware security policies, while also discussing important challenges and risks, such as potential leakage from AI models, limited explainability, and the need for strong governance and specialized skills. Finally, the paper outlines future directions for research on explainable AI, AI-specific safeguards, and integrated governance frameworks for AI-based data leakage prevention.