This chapter provides an overview of the multi-layered modern artificial intelligence (AI) ecosystem. The chapter answers the question of “Why AI now?” by examining the convergence of factors. The chapter traces the evolution from early symbolic systems to contemporary data-driven approaches. These include machine learning (ML), neural networks (NNs), deep learning (DL), transformers, mixture of experts (MoE), and large language models (LLMs). The chapter lists applications in natural language processing (NLP) and computer vision (CV). The discussion also covers the integration of rule-based and data-driven models, the emergence of AI agents and robotics, and the critical role of computing power, the Internet, and the Internet of Things (IoT). Finally, the chapter outlines the general development processes for AI models. It concludes with an introduction to the essential ethical guidelines and governance frameworks that guide responsible AI innovation.