There’s a story Jeff Bezos tells about the early days of Amazon that every leader running an AI transformation right now needs to hear.
He was at a whiteboard, doing what he does — generating ideas. A hundred in half an hour, by his own admission. One of his senior executives, Jeff Wilke, who’d been at Amazon for about a year at that point, pulled him aside.
“Jeff,” he said, “you have enough ideas to destroy Amazon.”
Bezos was floored. Destroy Amazon? With ideas?
Wilke came from a manufacturing background, and he explained it the way a manufacturing engineer would. Every idea Bezos released into the organization without it being ready was work-in-process. Inventory. A queue. It sat there, added zero value, and actively created distraction by competing for attention with everything else in the queue.
The problem wasn’t Bezos’s creativity. The problem was release rate.
Bezos’s reaction, in his own words: “This sounds so obvious, but it was not obvious to me at the time. It was a profound insight.”
He changed three things:
- He started prioritizing ideas instead of releasing them as they came.
- He started holding ideas back until the organization was ready to receive them.
- He started building an organization that could absorb more ideas per unit time — through better senior leadership, more executive bandwidth, and the right team structure.
That’s the part most people miss. Bezos didn’t slow down his inventiveness. He sped up his organization’s ability to absorb invention.
Why this matters right now, in 2026, in every Canadian boardroom
I’m watching a pattern repeat itself in almost every enterprise I walk into.
The CEO came back from a conference. The CIO read a McKinsey report. Someone on the board asked about agents. Marketing wants to pilot something. Finance wants to pilot something else. HR is “exploring options.” A Copilot rollout is half-done. Three different teams are evaluating three different LLM platforms.
Twelve workstreams. Six pilots. Two strategy decks. One steering committee that meets monthly.
And nothing — nothing — is actually shipping at scale.
Leaders look at this and conclude they have an AI strategy problem. They don’t. They have a Bezos problem. They’re releasing ideas faster than the organization can absorb them.
The release-rate diagnostic
Ask yourself, honestly, five questions:
- How many AI initiatives are currently in flight in your organization?
- How many of them have a named executive owner with the bandwidth to actually drive them?
- How many of your senior leaders could explain, in plain language, the difference between a Copilot, an agent, and a fine-tuned model?
- How many people in your org have been trained to lead change — not just announce it?
- If you stopped generating new AI ideas for 90 days, would the organization catch up, or fall further behind?
If your answer to #1 is high and your answers to #2 through #5 are uncomfortable, you don’t have an ideas problem. You have an absorption problem.
What “increasing absorption rate” actually looks like
This is where the AI-Native lens helps, because it names the three layers that have to move together.
Executive fluency. Your top team has to understand AI well enough to make release-rate decisions. Not prompt engineering — prioritization. What gets released this quarter, what waits, and why.
Change capacity. You need a critical mass of people inside the organization who can actually land AI change — not run a pilot, but embed new ways of working. These are your change agents, and most organizations have nowhere near enough of them.
Shared language. Everyone — exec, manager, individual contributor — needs the same vocabulary for what AI is, what it isn’t, what’s risky, and what’s table-stakes. Without shared language, every conversation restarts from zero, and release rate collapses.
Foundations, Change Agents, and Leading the AI-Native Organization map directly onto these three layers. That’s not a coincidence. It’s what an absorptive organization actually looks like.
The closing thought
Bezos finishes the story with a line that’s easy to miss. The interviewer asks whether forcing himself to release ideas at the right rate made him a better inventor. His answer: probably yes, because it forces you to prioritize, which sharpens the ideas.
In other words: the discipline of release rate didn’t kill his creativity. It improved it.
If your AI transformation is stuck, the answer is almost never “more ideas.” It’s an organization that’s ready for the ideas you already have.
Build the absorption rate first. The inventiveness will keep.
