As organisations increasingly rely on data-driven systems, ensuring the quality of master data has become a critical concern. This research explores the application of Artificial Intelligence (AI) in Master Data Management (MDM) within Enterprise Resource Planning (ERP) environments, aiming to improve master data quality. MDM is essential in ERP systems, where accurate and consistent data is critical for effective business processes and decision-making. Despite advancements, challenges in handling data from multiple sources, which can lead to inconsistencies and errors, persist. By leveraging AI capabilities, the research examines ways to streamline MDM tasks and mitigate issues that negatively impact data integrity and, consequently, business operations. The core contribution is an AI-Enabled MDM Framework developed by conducting Systematic Literature Reviews (SLR) and utilising Design Science Research (DSR) methodology. The findings categorise MDM functions with corresponding AI capabilities, suggesting AI tools and methods identified from literature. The framework was refined through a survey completed by data management professionals. Survey responses, combined with literature references, were used to identify the most critical MDM functions and AI capabilities. This framework serves as a foundation for future research and a reference for industry professionals looking to integrate AI into MDM systems.