"Nothing in AI works without good data." Amen but also don't lack of data get into an 'action paralysis' either! Good data beats Lots of data that you'll never get to.
Enjoyed the sessions and these recaps - when's the next one?
Kyle's 70/20/10 model is one of the most honest things I've seen from a revenue leader on AI transformation. Most executives outsource the entire thing and wonder why nothing changes. The fact that he's spending 10+ hours a week personally tells his team something no memo ever could: this is real.
But what caught my attention was something he only recently added to his skill stack — change management for AI. And his fifth adoption principle: "Cultural transformation > technical implementation."
That's the part most organizations skip. Not because they disagree with it, but because they don't know how to execute it. They can map use cases, prioritize by expected value, fix CRM hygiene, all of that is structured and measurable. But when adoption stalls, the answer is usually upstream of the technology.
Kyle names it without naming it: "If the language makes them feel like you're trying to replace them, nothing will get traction." That's not a communication problem. That's an identity problem. And identity problems don't show up in a 5P prioritization framework.
The companies getting 3-4x productivity aren't just better at picking use cases. They've figured out the human layer, whether people feel safe experimenting, whether leadership has defined what "good" looks like at each role, whether the workflow actually changed or just got faster.
Owner.com clearly figured that out. The question for everyone else is: do you know which part of the human layer is actually blocking you? Because the answer is different for every organization, and most are guessing.
"Nothing in AI works without good data." Amen but also don't lack of data get into an 'action paralysis' either! Good data beats Lots of data that you'll never get to.
Enjoyed the sessions and these recaps - when's the next one?
amen! :)
people liked it! and things are moving so fast. maybe every 6 months? what do you think?
Well it depends on how much it takes for you to put them together 🙂 I think 3-6 months is a good cadence!
Kyle's 70/20/10 model is one of the most honest things I've seen from a revenue leader on AI transformation. Most executives outsource the entire thing and wonder why nothing changes. The fact that he's spending 10+ hours a week personally tells his team something no memo ever could: this is real.
But what caught my attention was something he only recently added to his skill stack — change management for AI. And his fifth adoption principle: "Cultural transformation > technical implementation."
That's the part most organizations skip. Not because they disagree with it, but because they don't know how to execute it. They can map use cases, prioritize by expected value, fix CRM hygiene, all of that is structured and measurable. But when adoption stalls, the answer is usually upstream of the technology.
Kyle names it without naming it: "If the language makes them feel like you're trying to replace them, nothing will get traction." That's not a communication problem. That's an identity problem. And identity problems don't show up in a 5P prioritization framework.
The companies getting 3-4x productivity aren't just better at picking use cases. They've figured out the human layer, whether people feel safe experimenting, whether leadership has defined what "good" looks like at each role, whether the workflow actually changed or just got faster.
Owner.com clearly figured that out. The question for everyone else is: do you know which part of the human layer is actually blocking you? Because the answer is different for every organization, and most are guessing.