Agentic MDM Point-of-View
What Is Agentic Master Data Management and How Does It Work?
See how governed AI agents continuously improve, resolve and govern enterprise master data while people retain control over policy and critical decisions.
Video at a glance
Featuring:
Tim Ward
CEO and Co-Founder
CluedIn
Duration:
36 mins
Agentic video overview
Agentic Master Data Management is an operating model in which governed AI agents take ongoing responsibility for improving important enterprise data.
In this video, CluedIn explains what Agentic MDM means, how it differs from traditional MDM and why adding a copilot or chat interface does not make a platform genuinely agentic.
You will see how agents can continuously monitor data, investigate quality issues, identify duplicates, recommend corrections, enrich records, prepare matching and survivorship decisions and escalate uncertain cases for human review.
The session also explains why the foundations of MDM still matter. Golden records, entity resolution, survivorship, data quality, lineage, governance and stewardship remain essential. What changes is the operating loop around them.
A graph-native architecture gives agents the context needed to understand relationships, source trust, historical decisions, policies and downstream impact. Governance boundaries then determine what an agent may inspect, recommend or change, while attribution, audit trails, explanations and human-in-the-loop workflows keep the organisation in control.
Watch the video to understand:
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What Agentic Master Data Management is
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How Agentic MDM works in practice
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How it differs from traditional MDM and AI copilots
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Why knowledge graphs are important for agent decisions
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How agents support data quality, entity resolution and stewardship
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How organisations can introduce governed autonomy safely
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How CluedIn supports Agentic MDM across modern enterprise data estates
