Today we examine the profound societal impact of Artificial Intelligence, tracing its historical evolution and highlighting its pervasive influence across diverse sectors like economics, governance, education, and healthcare. It emphasizes AI's inherent reliance on vast amounts of data, exploring the various methods of collection, the different types of data (structured, unstructured, sensitive, biometric), and the complex algorithms and architectures used for processing and utilization. Crucially, the we identify and analyzes major privacy concerns arising from AI, including data breaches, re-identification risks, algorithmic bias, pervasive surveillance, deepfakes, and the “black box” problem, while also outlining the evolving legal and regulatory landscape and essential technical safeguards and best practices necessary to navigate these challenges responsibly.