Master Data Management (MDM) is a critical foundation for enterprise systems, yet many organizations struggle with data inconsistency, duplication, and governance challenges within ERP environments. This session presents practical insights into how AI and machine learning can transform MDM processes to improve data quality and operational efficiency.

Based on research and real-world implementations, the session explores how AI techniques such as machine learning, natural language processing, and predictive analytics can be applied to automate data validation, cleansing, and enrichment within ERP systems. It highlights how AI-driven MDM frameworks enable real-time data synchronization, reduce redundancy, and improve decision-making across business processes.

The session also introduces a modular architecture for integrating AI into existing ERP landscapes, focusing on scalability and adaptability. Findings demonstrate measurable improvements in data accuracy, reduced manual effort.