AI, Master Data & Data Governance: Why foundations matter more than ever?

Can AI replace Master Data Management and data governance?

No. AI makes MDM and DG them more critical than ever.

That was the core conclusion of the latest  Lights on Data Show, hosted by George Firican, featuring Bruno Billy, President North America at APGAR, and Ken Brown, Head of Customer Success at APGAR.

The discussion was wide-ranging and dynamic. For example, George, Bruno, and Ken discussed where AI can meaningfully support MDM programs. AI performs extremely well on public, standardized data. But enterprise data behaves differently. Domains such as product, supplier, and asset data are deeply business-specific and proprietary. Without that business context, AI can struggle to form a reliable view of reality. 

Another thread surfaced around why long-standing data issues persist even as new technologies, such as AI, emerge. The reason the team agreed is that most enterprise data challenges are not technical. They stem from issues found in the operating model, issues around ownership, governance, and the absence of shared business definitions. Without strong data foundations, adopting AI risks accelerating chaos rather than creating value. 

The session also touched on where AI is already delivering tangible benefits in MDM today. In addition to discussions around anomaly detection, automated classification, match and merge support, and user experience.  Bruno and Ken pointed out that conversational interfaces, in particular, have begun to simplify how business users engage with master data, and that is the addressing adoption and change-management challenges that we see in MDM programs.

You want to dive deeper ? Learn more in our ebook