Generative AI has emerged as one of the most transformative areas in AI, enabling machines to not only analyze existing data but to produce entirely new content across a wide range of formats. This chapter introduces the foundational principles of generative modeling, explains how these models differ from traditional discriminative approaches, and explores their applications in text, vision, audio, and multimodal systems. It also provides an overview of the primary architectural families driving this field, including transformers, generative adversarial networks, variational autoencoders, and diffusion models. By the end of this chapter, readers will have a clear basic understanding of what generative AI is, how it works, and where it is being deployed in real-world environments.