This conceptual study reviews and synthesizes the existing literature to explore the impact of agentic artificial intelligence (AI) on market efficiency. The existing studies have well established the benefits of AI in improving information processing, price discovery, and liquidity. The transition from AI to autonomously driven agentic systems has additional benefits, along with introducing new challenges and risks such as volatility and systemic instability. This study examines two key dimensions: (1) how agentic AI contributes to the broader market efficiency; (2) the risks agentic systems pose to stability and volatility in the market. Our discussion posits that while agentic AI holds significant promise, structured governance frameworks, including human in the loop oversight, would be critical to its success. The study’s originality lies in framing a comprehensive conceptual understanding of how agentic AI simultaneously drives efficiency and presents challenges within financial markets. As a conceptual paper, the study is limited by the absence of empirical analysis, relying instead on secondary sources. However, the study identifies critical gaps, particularly in exploring how agentic AI influences cross market spill overs, governance mechanisms, and investor behaviour. This paper provides a valuable foundation for academicians and policymakers navigating the evolving intersection of AI and financial systems.