Explainable AI (XAI) refers to methods and techniques in artificial intelligence that make the decision-making processes of complex models more transparent and understandable to humans. Unlike traditional "black-box" models, XAI provides insights into how AI systems arrive at specific predictions or decisions, helping to build trust, ensure fairness, and meet ethical and regulatory standards. It aims to make AI more interpretable, enabling users to understand, validate, and challenge AI outcomes, especially in high-stakes domains like healthcare, finance, and autonomous vehicles