A simple way to identify which AI workflows to start with now, which to scale later, and which to deprioritize.
May 5, 2026 · Last updated on June 12, 2026
One of the easiest ways to lose momentum with AI adoption is to treat every workflow idea as equally urgent.
This simple Use Case Discovery & Prioritization Matrix is meant to help Champions step back and ask two practical questions:
1. How valuable would this workflow be if it worked well?
2. How much effort or complexity would it take to make it real?
A few things to consider as you place workflows on the matrix:
Impact / Value
Frequency, repeatability, and reach are often strong signals. A task that happens often, follows a recognizable pattern, and affects many people may be a better starting point than a more novel but less repeatable use case.
Complexity / Effort
Process complexity, readiness of inputs and outputs, governance requirements, and system dependencies all affect how hard a workflow will be to implement well.
Start by listing a few candidate workflows.
Score them loosely on value and effort.
Look first at quick wins to build visibility and momentum.
Treat strategic initiatives as important, but likely slower-moving.
Defer nice-to-haves, and deprioritize workflows that are costly but low value.
This can be especially helpful when you are trying to decide where to focus limited enablement time, what to pilot with a team, or which AI workflow to package for reuse.
