Category: AI Strategy Points
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AI Strategy Points: What, So What, and Now What — Applied to AI
The framework I built for operational dashboards turns out to be the clearest way I know to define what “value” actually means for an AI initiative.
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AI Strategy Points: Scaling AI Is About Successful Test Cases, Not Big Launches
Big-bang AI rollouts rarely earn the trust they need. Scaling looks a lot more like Kotter’s short-term wins than a company-wide launch event.
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AI Strategy Points: A Super-Intelligent, Hyper-Literal, Eager, Inexperienced Intern
The metaphor that’s helped me manage AI’s failure modes better than any other: it’s an intern who will produce exactly what you ask for, even when what you asked for was wrong.
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AI Strategy Points: Most Initiatives Start With Training. The Real Starting Point Is Data
Organizations rush to teach people how to prompt an AI before making sure the data underneath is trustworthy. That order is backwards.
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AI Strategy Points: AI Will Make Smart People Genius and Average People Smart
AI doesn’t flatten the gap between your strongest and weakest performers. It tends to widen it, in a specific and predictable direction.
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AI Strategy Points: People Won’t Lose Their Jobs to AI — Yet. They’ll Lose Them to People Who Adopt AI
The threat most people are worried about isn’t the one that’s actually coming for them right now.
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AI Strategy Points: A Realistic Assessment of AI End Users and AI Builders
Most organizations treat AI adoption as one population learning one skill. In practice, end users and builders need almost entirely different things from you.
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AI Strategy Points: AI Initiatives Have to Create Value to Stick — But Whose Value?
Everyone agrees AI initiatives need to create value. Almost nobody agrees on what value means, or who gets to decide.
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AI Strategy Points: If You’re Just Starting, You May Already Be Behind the Curve
I started with ChatGPT a few years before it went mainstream, trying to get ahead of what looked like a coming wave. I didn’t expect the wave to arrive this fast.