Five signals your organization is (actually) ready for AI

May 22, 20266 min read— Etienne Savard

Illustration of signal beacons representing organizational readiness

"Are we ready for AI?" is the wrong question. Every organization is ready for some AI. The right question is: which parts of the business are ready to absorb a change today, and which aren't?

Here are five practical signals I look for in a readiness assessment.

1. Someone owns the process end-to-end

If nobody can point to a single owner for the workflow you want to automate, the AI project will fail — not because of the model, but because there is no one to make the trade-offs.

2. The data exists, somewhere

You don't need a data lake. You need the source data to exist in a system a human can query today. If a human can't get the data, an AI can't either.

3. The team ships things

Look at the last three initiatives the owning team completed. If they took 18 months and got watered down, an AI workflow will follow the same fate. Start where delivery muscle already exists.

4. Leadership can define "good enough"

AI outputs are rarely 100% correct on day one. Teams that ship are the ones whose leadership can say "80% correct with a human review is a win." Teams that can't will chase perfection forever.

5. There's a real cost to the current state

If the pain is theoretical, the project will lose priority the moment something urgent lands. Look for workflows where the current cost — in time, errors, or missed revenue — is visible and quantifiable.

If you can check three of these five, you're ready to start. If you can't check any, the first engagement isn't AI — it's clarifying ownership, data, and delivery.