Most AI prioritization treats readiness as a fixed property of a workflow: either the data is clean and the rules are clear, or they aren't. That framing is wrong, and it's expensive.
Readiness moves. When you ship your first system, three things change for the workflows next to it. The integration you built is reusable. The data you cleaned is now clean for everyone. And the organization has watched one AI system run in production without breaking, so its tolerance for the next one rises.
Readiness is a byproduct of shipping
This is why sequencing matters more than selection. A workflow that scored a 2 on data availability in Discover can score a 3 once the first milestone has wired up the same source system. On the Leverage Map, that workflow visibly glides from Prove the Case into Automate First.
That's the difference between a roadmap and a flywheel. A roadmap is a list you work down. A flywheel is a list that gets shorter and easier every time you ship.
Written by Vurelio. Figures shown are illustrative and anonymized.
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