Watch Why Master Data Management Is the Foundation for AI in Retail
Video Summary
In this webinar highlight from Breaking Down Retail Silos: Building the AI-Ready Enterprise, Gary Hawkins asks Digital Wave Technology CEO Lori Schafer why Master Data Management (MDM) is critical in the age of AI. Lori explains why AI is only as powerful as the data it runs on, and why messy, inconsistent records undermine automation, personalization, and compliance.
She introduces the concept of AI-native MDM, where intelligence is built directly into the foundation to deliver a single source of truth across the enterprise. With clean, governed data, retailers can reduce costly errors, streamline operations, and maximize AI’s impact.
Key Takeaways
AI is only as effective as the quality of the data it runs on
Traditional MDM is outdated; modern MDM must be AI-native and dynamic
A single “golden record” creates trusted consistency across product, customer, and pricing data
Starting with an AI-powered master data foundation ensures every AI initiative scales successfully
Clean, de-duplicated, and governed data prevents errors that can cost 15–25% of revenue
Video Transcript
Gary Hawkins: We’ve talked about Master Data Management and why it’s so important today, especially when powered by AI. Could you share your perspective on what you’re seeing?
Lori Schafer: At Digital Wave, I feel very strongly that AI has to be built on a rock-solid foundation. AI is only as good as the data it runs on. When data sits in silos, you often end up with duplication, inconsistencies, or errors across different systems.
That’s where Master Data Management comes in — and it’s where companies need to start. MDM provides clean, consistent data across the entire enterprise.
Traditional MDM used to be passive, sitting in IT, but today we’re seeing MDM that is AI-native. This means intelligence is embedded directly into the foundation, creating a single source of truth — one golden record — for all data, from customer and product to pricing and descriptions.
AI-native MDM automatically de-duplicates, cleans, and validates data before it’s used in merchandising, marketing, or supply chain execution. Without this, organizations risk applying AI on top of messy, fragmented information.
Gartner has found that data errors can cost 15–25% of revenue. By automating with a clean master data foundation at the start, retailers can avoid these costs and set the stage for AI to deliver real, scalable impact.