Weaving Intelligence
AI for Data Governance & Stewardship
MDM + AI
Same Work, New Tools: What the Rules Engines Already Taught Stewardship About AI
Rules engines, rule-proposing profilers, auto-approve thresholds, automatic classification and routing were the smart governance of the pre-AI era. They mostly kept their promise. What struggled was adoption, the steward's loop never changed, and today's AI pitch repeats the list.
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Heads Up: The Data Steward's Job After the Routine Work Goes
When the master data system first automates a steward's routine work, the tricky residue takes over the week and time opens up for problems nobody could chase before. AI should repeat that pattern. What it means for skills, for headcount, and for the experience it frees.
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The Primrose Path: Where AI Is Taking Policy Enforcement, Exceptions and Routing in Master Data
Budget pressure will hand policy enforcement, routing and, last and in pieces, exception handling to AI, often because it is good enough rather than better. What full automation does to an error, and what to keep doing while it happens.
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Another Set of Eyes: How a Data Steward Should Work With What the AI Proposes
An AI model's output belongs in the data steward's queue as a suggestion, with the evidence it used, approved before anything is written. The research on decision fatigue is contested, but the case for spending a steward's attention carefully, and for introducing the model as another set of eyes…
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