AI governance and data governance are related, but they are not interchangeable. We talk about data ownership, quality, accountability, institutional knowledge, shadow AI, hallucinations and regulatory exposure.
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Clip · Aug 15, 2026
Why replace the engine?
Why do organizations settle for replacing the engine when preventative maintenance is 10x less costly?
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Clip · Aug 14, 2026
Sanctioned AI vs. shadow AI
“Sanctioned” AI, even if procurement approved it, may still lack proper governance.
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Clip · Aug 13, 2026
Hallucinations inside your organization
An AI headshot with an extra limb is a reminder of the silent “hallucinations” happening inside organizations.
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Clip · Aug 12, 2026
AI can’t govern without defined ownership
If you can’t define who owns the data, how can you expect AI to make reliable decisions?
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Clip · Aug 11, 2026
Start your AI journey right
An AI journey hinges on robust data governance and effective organizational change management.
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Clip · Aug 10, 2026
Data governance is non-negotiable
Data integrity and high data quality are ongoing necessities, not one-time projects.
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Clip · Aug 9, 2026
Data governance: not a restriction, but trust
Its true purpose is to build trust, so you can make high-value decisions with confidence.
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Clip · Aug 7, 2026
AI’s Wild West: setting the standards
Without clear standards and ethical frameworks, we risk unchecked growth and unintended consequences.
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Clip · Aug 7, 2026
What do enterprise execs really want from AI?
The AI era demands clear standards and a deep executive understanding of the implications.
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Clip · Aug 6, 2026
How many top-1000 companies have good governance?
Fortune 1000 companies with a truly robust governance program? A resounding none.
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Clip · Aug 5, 2026
Data governance vs. AI governance
Two distinct disciplines: data governance is about ownership, stewardship and trusted data foundations.
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Clip · Aug 4, 2026
AI prompts left in client decks
Leaving AI prompts visible and skipping the fact-check can turn a client presentation into an embarrassment.
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This is a follow-up to my earlier piece, Who’s Minding the Farm? I want to look more closely at one part of that question: what happens when the people who know the farm best are the ones being let go.
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Post · Oct 15, 2026
Leaders should ask themselves: Do people trust us enough to tell us what they’re using? Can they ask a question without getting a lecture? Have we given them a workable option?
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Post · Oct 11, 2026
Experience in machine learning, predictive analytics and automation matters. But lumping all of that together with generative AI and AI agents makes it harder to understand what someone has actually delivered.
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Post · Aug 18, 2026
To a lot of people AI is this magical beast that is supposed to make everything better, easier, faster, but most people can’t even articulate what it actually means to deploy AI in their organizations.
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Post · Aug 4, 2026
Data Governance ensures the information AI consumes is accurate, trusted, secure, and fit for purpose. The problem often is, organizations put all the effort into making sure the data is clean once and then forget about it.
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Series: Who’s Minding the…
Post · Jul 30, 2026
Say companies do everything right. They keep experienced people, capture the knowledge and govern the data properly… There’s still something sitting underneath it…
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Series: Who’s Minding the…
Post · Jul 27, 2026
If you hired a firm because of its expertise, would you expect them to tell you if much of the work was now being performed by less experienced resources augmented by AI?
Read on LinkedIn →“Efficiency without that foundation isn’t transformation. It’s cost reduction with a knowledge deficit.”
From Who’s Minding the Farm?
Post · Jul 23, 2026
People aren’t trying to cause a breach, they’re just being told to be more efficient. But chasing efficiency without foundations leads to shadow AI creeping in.
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Post · Jul 15, 2026
If you’ve been impacted by AI, laid off, displaced (as my friends now call it, Hartwell’d)… Sometimes you don’t need someone to solve your problems, you just need someone who gets it.
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