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Rob was supposed to be finishing his book. Last chapter. Two days past deadline. Freedom was right there.
Instead, he hit pause and recorded this.
Because something from a few weeks ago wouldn't leave him alone.
A Microsoft exec had dropped "Microsoft IQ" into a conversation weeks ago. At the time, it didn't fully land. Not unusual. There's been a steady firehose of new terms, new features, new promises. Most of them sound important. Not all of them are.
Then he got deep into the data chapter. The one where you have to stop talking about what AI could do and deal with what it takes to make it work in a real company.
And that's where this thing stopped sounding like a label and started looking like a plan.
AI looks great right up until you ask it to do something that depends on your business. Your definitions. Your documents. Your people. That's where things usually start to wobble. Not because the model isn't capable, but because it doesn't have the context to land the answer.
What Microsoft is doing with IQ is trying to meet that problem head on.
· Fabric IQ is the structured side. Semantic models doing what they've always done, but now under a lot more pressure.
· Foundry IQ is all the documents and content you forgot you had.
· Work IQ is the human layer. Who's involved. Who needs to know. What you meant when you said "that thing."
And yeah… if you've been doing Power BI the right way, this is where it gets interesting. Because those semantic models everyone else treated like optional homework? That's now the thing everything else leans on.
We're not saying this episode is the key to your AI implementation, but it will make it clear why some of this is working and some of it isn't.
By P3 Adaptive5
5353 ratings
Rob was supposed to be finishing his book. Last chapter. Two days past deadline. Freedom was right there.
Instead, he hit pause and recorded this.
Because something from a few weeks ago wouldn't leave him alone.
A Microsoft exec had dropped "Microsoft IQ" into a conversation weeks ago. At the time, it didn't fully land. Not unusual. There's been a steady firehose of new terms, new features, new promises. Most of them sound important. Not all of them are.
Then he got deep into the data chapter. The one where you have to stop talking about what AI could do and deal with what it takes to make it work in a real company.
And that's where this thing stopped sounding like a label and started looking like a plan.
AI looks great right up until you ask it to do something that depends on your business. Your definitions. Your documents. Your people. That's where things usually start to wobble. Not because the model isn't capable, but because it doesn't have the context to land the answer.
What Microsoft is doing with IQ is trying to meet that problem head on.
· Fabric IQ is the structured side. Semantic models doing what they've always done, but now under a lot more pressure.
· Foundry IQ is all the documents and content you forgot you had.
· Work IQ is the human layer. Who's involved. Who needs to know. What you meant when you said "that thing."
And yeah… if you've been doing Power BI the right way, this is where it gets interesting. Because those semantic models everyone else treated like optional homework? That's now the thing everything else leans on.
We're not saying this episode is the key to your AI implementation, but it will make it clear why some of this is working and some of it isn't.

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