This chapter traces the historical trajectory of artificial intelligence, from its symbolic beginnings and early optimism through the disillusionment of the AI Winter, to the current renaissance powered by deep learning and transformer-based models. It examines the factors that enabled AI’s resurgence—advances in computational power, data availability, and algorithmic innovation—and culminates in the rise of generative AI as a paradigm-shifting development. The chapter also critically assesses ongoing challenges, including environmental costs, infrastructure limitations, data scarcity, and equity concerns. By anchoring contemporary breakthroughs in historical perspective, it underscores the need for balanced, responsible innovation that avoids the overpromising that once stalled the field’s progress.