
As artificial intelligence (AI) systems become increasingly integral to sectors like finance, healthcare, and autonomous vehicles, there is a growing imperative to ensure these systems are transparent, accountable, and trustworthy. Explainable Artificial Intelligence (XAI) has risen to prominence to address concerns about the opaque nature—or “black box”—of many AI models. This article discusses the need for explainability in AI, outlines