Hey y'all, I'm a data governance advocate and practitioner, a bit of a data quality nerd, and have been working in healthcare for many years. Glad to be here because nobody knows everything about data governance and it is different at each and every company, so we all have things to share to make our data governance community stronger. I welcome all connections on LinkedIn (https://www.linkedin.com/in/billwoodmba/) and can talk data governance all day. I'm avidly learning about AI governance and how it differs from data governance. Pleased to meet you all!

Interested to know how much MDG tooling drives governance frameworks and practices?

Where Do They Intersect? Share your thought? 👇

From this article. On August 2, 2026, the EU AI Act's high-risk provisions become enforceable. While boards are obsessing over model compliance, they are missing the real operational threat: Article 10. It mandates that training, validation, and testing datasets must be relevant, representative, error-free, and complete. Regulators are no longer just auditing your AI; they are auditing the underlying data architecture. The brutal reality from a recent Cloudera/HBR report is clear: only 7% of enterprises believe their data foundation is completely ready for AI. The other 93% are accelerating blindly into a regulatory wall. The Verdict: You cannot bolt compliance onto a messy data swamp. If your data governance practices—like lineage tracking, bias detection, and data preparation—aren't systematically documented and enforced "by design," your high-risk AI systems will become immediate legal liabilities by August. The fix isn't deploying more AI tools; it's enforcing rigorous, unglamorous data architecture. Let's Discuss: 💬 The Readiness Gap: Are your AI initiatives building on a governed data foundation that can withstand a rigorous regulatory audit, or is your organization part of the 93% crossing their fingers for a grace period? 💬 The Article 10 Challenge: When the auditor knocks, who in your C-Suite is actually on the hook for proving your datasets are "free of errors and complete"—the CDO, the Legal team, or the AI engineers left holding the bag?

Huge milestone today—we just welcomed our 500th member to the Data Governance Hub! Data Governance is no longer a "nice-to-have"; it’s the backbone of the AI era. I’m honored to lead such a talented group of professionals dedicated to making data better. If you're new here, welcome home. Head over to the Classroom to grab your starter templates and join the conversation in the community feed. Onward to 1,000! 📈