Your Data Is Lying To You: Why Reconciliation Has To Come Before AI - E132

About this episode

The episode discusses the importance of data reconciliation before implementing AI in organizations.

Episode 132 - Most organizations are being pushed to adopt AI-powered workflows before their data is anywhere close to ready. In this episode of What Counts, Maura and Lee pick up where they left off — diving deep into the concept of data reconciliation and why it must happen before AI ever touches your records. Using a real-world example built across multiple systems — a customer database, a work order system, and a contract management platform — they break down what it means to have duplicate, overlapping, and contradictory counterparty data, and why humans, not algorithms, are the ones who can resolve it. Maura introduces the concept of the golden record, explains the role of metadata mapping and fuzzy matching, and walks through the governance framework — policy, process, and system-of-record designation — that prevents the mess from coming back. If your organization is facing an AI initiative, a system migration, or growing pressure around data privacy and right-to-be-forgotten compliance, this episode gives you the foundational framework you need to start doing it right. Episode length: 00:26:36 Learn more by visiting our website, or by sending TrailBlazer an email at…

People in this episode

Hosts: Maura, Lee

Topics covered

• data reconciliation
• AI workflows
• data governance
• metadata mapping
• data privacy
• right-to-be-forgotten

Keywords

• data reconciliation
• AI
• golden record
• metadata mapping
• data governance
• privacy compliance
• duplicate data

Mentioned in this episode

Organizations: TrailBlazer Consulting, LLC, customer database, work order system, contract management platform

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