This paper explores the ongoing debate surrounding AI's capacity for genuine reasoning, questioning whether current systems truly think or merely exhibit advanced pattern recognition. It defines AI reasoning as simulating human cognitive processes like deduction and problem-solving, distinguishing it from generative AI and pattern matching. The document highlights the historical evolution of AI approaches, from symbolic systems to neural networks, and the emergence of hybrid models. Critically, it presents evidence from Apple's "Illusion of Thinking" research suggesting current AI models fail at high-complexity problems, pointing to fundamental limitations in their logical processing. Finally, it discusses future directions like Neural-Symbolic AI and underscores the crucial ethical, legal, and governance implications of developing increasingly capable AI.