AI agent feedback loops are revolutionizing data management in Master Data Management (MDM) by actively correcting data inconsistencies, reducing errors caused by human oversight, and improving data quality. These loops involve AI agents that not only interpret data but also contribute to its improvement, making them applicable across various industries such as healthcare and finance. Agent feedback loops can continuously monitor data inputs, identify anomalies, and correct them in real-time, leading to a more robust and reliable data infrastructure. By leveraging these technologies, companies can ensure accurate and up-to-date master data, improving operational efficiency and strategic decision-making. The key advantage of agent feedback loops is their ability to adapt to the ever-changing digital world, setting the stage for truly autonomous systems that can self-correct and optimize without human intervention.