This research paper provides a comprehensive review of the emerging trends in AI-based stock market prediction. The paper highlights the key concepts, approaches, and techniques employed in AI-based stock market prediction, and discusses their strengths and limitations. Key topics covered include deep learning, natural language processing, sentiment analysis, and reinforcement learning. The paper also presents case studies and evaluates the performance of different AI-based models in predicting stock market trends. Overall, the research paper provides valuable insights into the latest advancements in AI-based stock market prediction and their potential implications for investors, financial analysts, and policy makers.