This paper critically examines Peter Senge\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\'s learning organization theory and its relevance in today\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\'s complex, AI-driven world. Employing a mixed-methods approach to analyze the theory\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\'s core assumptions, concepts, and prescriptive elements. The research aims to assess the theory\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\'s strengths and limitations in the face of contemporary challenges, specifically the impact of rapid technological advancements, globalization, and increasing uncertainty. While the learning organization framework offers a valuable paradigm for organizational development, the research identifies gaps in addressing these modern realities. Specifically, the paper explores the theory\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\'s adaptability to the rise of artificial intelligence and its impact on organizational learning processes, revealing how AI integration both facilitates and challenges traditional learning dynamics. By highlighting these limitations and presenting empirical findings on AI\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\'s influence, the study proposes avenues for theoretical refinement, aiming to enhance the learning organization concept for both scholars and practitioners navigating the complexities of the modern organizational landscape. This contributes to a more nuanced understanding of how organizations can effectively learn and adapt in the 21st century.

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