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Data Governance Circle

351 members • Free

1 contribution to Data Governance Circle
Intro
Hi everyone,I’m Alain. I work on data governance and AI compliance in regulated environments (GDPR, DORA, AI Act). My current focus is very operational: how organisations move from policies to traceable, auditable practices when AI is used in real workflows (contracts, vendor due diligence, compliance reviews, internal controls). I’m especially interested in practical patterns for logging, evidence, human oversight, and how people make this work without creating excessive overhead. Curious to learn from the community: what have you found most effective to make governance “stick” in day-to-day work, especially when AI enters the picture? Looking forward to learning and contributing. Alain
1 like • Dec '25
@Paul Mullon Absolutely, this is exactly the issue: every discipline is right in its own lane, but it’s hard to make the requirements “compose” in real operations. Records management ends up assumed rather than designed. One approach I’ve seen work is to stop trying to unify vocabularies, and instead agree on a small set of things we must be able to evidence in any case: what artefact was handled, what control was applied, what decision was taken, by whom, when, and why. Then privacy, security, records and audit can all read the same trail through their own lens. In Part 2, are you moving toward that kind of minimal evidence requirement, or keeping it mostly process guidance?
1 like • Dec '25
@Paul Mullon Thanks a lot for sharing. That distinction is exactly right. The inventory is essential because it defines intent and scope, but on its own it can’t show how controls were actually exercised over time. What I’ve seen work is when the inventory becomes a reference layer, and systems start emitting explicit decision events against it: validation, override, exception, remediation, closure. Not free text, but simple, typed actions linked back to the artefact and control. That way, when a question comes later, you’re no longer inferring behaviour from logs or emails, you can replay what happened. At that point, records management, audit and data governance finally line up operationally. Thanks again for sharing your approach and for the thoughtful exchange. Really appreciate the practical insight, and looking forward to more conversations on how this space evolves.
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Alain Augsburger
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@alain-augsburger-2873
AI governance & compliance, evidence-based controls for GDPR, DORA & EU AI Act. Building traceability and provability into data and AI systems.

Active 8d ago
Joined Dec 11, 2025