Beyond Trusted Data: 3 Key Insights from the 2026 Semarchy Summit
October 15th, 2026 WRITTEN BY FGadmin Tags: AI-native MDM, Intelligent Data Products, master data management modernization, Semarchy Data Platform (SDP)
Written by Suchi Agarwal, Sr. Manager, Data Management, Fresh Gravity
Master Data Management (MDM) has traditionally focused on establishing trusted, consistent data across the enterprise. But as organizations expand their analytics and AI initiatives, the conversation is shifting toward how that data can be made more accessible, actionable, and valuable to the business.
At the 2026 North American Semarchy Summit in Chicago, we had the opportunity to engage with customers, partners, and data leaders exploring the next phase of enterprise data management.
Across customer sessions, product demonstrations, and roadmap discussions, two themes stood out: the transition from xDM to the Semarchy Data Platform (SDP) and the growing focus on Intelligent Data Products.
A third perspective came from Fresh Gravity’s session, AI-Native MDM: When an Agent Talks to x360, where we explored how intelligent agents could support everyday MDM operations within established governance controls.
Together, these three areas highlight how enterprise data management is evolving, from modernizing data foundations to making trusted data more useful and exploring AI-assisted operations.
- Moving from xDM to SDP: Modernization with Purpose
A major focus of the Summit was the transition from xDM to the Semarchy Data Platform (SDP).
While this may initially appear to be a technology upgrade, the discussions highlighted a broader opportunity for organizations to modernize their data management environments.
The move to SDP is being considered as a way to simplify operations, improve scalability, and prepare for future analytics and AI initiatives.
However, successful migration involves more than transferring existing capabilities to a new platform. It also provides an opportunity to reassess processes, streamline governance, and align data management practices with changing business requirements.
For organizations planning this transition, the important question is what they want their data environment to support once the migration is complete.
- Intelligent Data Products: Making Trusted Data More Useful
Another prominent theme was the growing interest in Intelligent Data Products.
Organizations are looking beyond the creation and maintenance of trusted master data to consider how that information can be consumed across business functions, analytics platforms, and AI applications.
Intelligent Data Products bring together trusted data, business context, governance, quality insights, and metadata to create reusable, business-ready assets.
Rather than treating data simply as records maintained within individual systems, this approach emphasizes making governed information available for broader enterprise consumption.
As AI adoption grows, this becomes particularly relevant. Trusted data remains the foundation, but organizations also need to make that information accessible and usable in the appropriate business context.
The next consideration is how to make the operational processes surrounding that data more effective.
- AI-Native MDM: Bringing Intelligent Agents into Governed Data Operations
Even in mature MDM environments, activities such as diagnosing mapping failures, assessing the impact of codelist changes, and identifying differences across environments can require manual investigation and specialized technical knowledge.
During our session, we explored how intelligent agents could support these activities through the Model Context Protocol (MCP), while operating within established governance controls.
Three practical use cases were covered:
- Profiling new source data for data modeling & matching
- Making code changes
- Getting business answers by combining data from different applications
These examples highlight potential applications of AI-assisted investigation in MDM. However, approvals, auditability, and human decision-making remain essential when introducing intelligent agents into governed data environments.
The focus is on supporting MDM operations without compromising the controls that enterprise data management requires.
Suchi Agarwal, Sr. Manager, Data Management at Fresh Gravity, presenting at the 2026 North American Semarchy Summit in Chicago.
Looking Ahead: Connecting Data Modernization with AI
The three areas discussed above address different but connected aspects of enterprise data management.
Platform modernization provides an opportunity to strengthen data foundations. Intelligent Data Products focus on making trusted information more accessible and useful. AI-native MDM explores how intelligent agents could support the operational work involved in managing that information.
For data leaders, the priority is to evaluate these developments in the context of their existing environments, business requirements, and governance responsibilities.
Trusted data remains essential. Building on that foundation requires thoughtful decisions about how data is managed, consumed, and used to support emerging AI capabilities.
