Year: 2025
Type: article
Abstract: Master Data Management (MDM) serves as a critical foundation for successful Artificial Intelligence implementation by ensuring data quality, consistency, and proper governance across the enterprise. As organizations increasingly adopt AI technologies, they face significant challenges with fragmented data infrastructures, inconsistent information, and compliance requirements that directly impact AI performance. MDM addresses these obstacles through entity resolution, standardization, data integration, and comprehensive governance frameworks. The symbiotic relationship between MDM and AI creates tangible benefits including enhanced decision-making, increased operational efficiency, improved customer experiences, and greater organizational agility. Financial services case studies demonstrate how MDM transforms fragmented customer data into strategic assets, significantly reducing duplication while improving model accuracy and regulatory compliance. Implementing MDM with clear governance policies, quality management tools, cross-departmental collaboration, and cloud-based architectures provides organizations with the essential data foundation needed to fully realize AI's transformative potential.
Author: Sumit Prakash Singh
Language: English
Topic: Data Quality and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4409670094