This study explores the evolution of Artificial Intelligence (AI) from its mid-twentieth-century theoretical roots to modern advances in machine learning, deep learning, and natural language processing. It highlights milestones like early symbolic AI, expert systems, neural networks, and generative AI models. The study examines major constraints like computation limits, ethics, bias, and regulations. It also highlights growing patterns like explainable AI, human-centred AI, and merging AI with quantum computers. The study also discusses emerging trends and potential developments in AI research and applications.