Agentic AI represents a transformative approach to data quality governance by autonomously managing data quality issues, shifting from reactive problem-solving to proactive prevention. Unlike traditional AI, agentic AI systems independently perceive, decide, and act, using reasoning and adaptation to manage data across various infrastructures in real-time. This approach addresses critical governance dimensions like accuracy, consistency, and compliance, significantly reducing financial risks and improving operational efficiency. Agentic AI automates repetitive tasks, scales effectively with growing data volumes, and continuously learns to enhance data accuracy, minimize compliance risks, and optimize data security. By integrating into existing systems, it offers tangible benefits across industries such as financial services, healthcare, retail, and manufacturing, enabling organizations to maintain stringent data governance standards. The future of data quality governance lies in the evolution of AI capabilities, promising fully autonomous systems that seamlessly integrate with blockchain technologies and continuously optimize data quality, positioning agentic AI as a cornerstone for competitive advantage in data management.