Insights
Author: greenadmin
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From Data Governance to AI Governance: The Same Foundation, a Much Longer Checklist
My work is in data management and governance, the discipline that translates business and data strategy into data policy and standards, fixes accountability through owners and stewards, and holds both in place through continuous oversight and measurement. That is the vantage point…
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Why I built the Two Wings AI Framework
Enterprises are investing heavily in AI, yet relatively little of it reaches production. The published evidence is consistent on this point: a 2025 MIT study of more than 300 enterprise AI deployments found that roughly 95% of generative-AI pilots delivered no measurable…
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Govern the meaning, not just the data
Most AI teams I meet are convinced they have a retrieval problem. Their assistants and agents give inconsistent answers, so they reach for more — more context in the prompt, then RAG, then another connected system, then more documents, more metadata, more…
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Data governance operating models that stick
I have set up data governance in many large organisations. I know where it usually fails — and it is almost never the framework. Organisations write a competent policy, convene a council, publish the standards, and then underinvest in the one thing…
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Why trustworthy AI needs governed data
Every enterprise AI conversation I join eventually arrives at the same place: the model is the easy part. You can rent a capable model this week. What decides whether it earns trust — and survives contact with production — is the data…
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The importance of data management
Mastery of the Data Management discipline is an essential part of any organization’s digital transformation journey. It is part of being a data-driven organization and it is a pre-requisite for success in the exploitation and monetization of your data assets. Organizations with mature…