Campo Labs

AI Readiness Checklist

A founder-and-operator diagnostic for deciding whether an AI build is ready to move now, needs sequencing first, or should wait.

Best For Teams evaluating workflow automation, document intelligence, or internal copilots.

Use It In A 10-minute founder review, ops meeting, or early discovery call.

Goal Clarify whether the problem, data, owner, and adoption path are actually ready.

1. Can you describe the problem without saying "AI"?

What manual process is slow, expensive, or inconsistent? What decision gets made poorly or not at all? If the answer is "we want to use AI" without a specific bottleneck, you're not ready.

Ready: "Our team spends 20 hours/week reviewing contracts for risk clauses and still misses things."

Not ready: "We should be doing something with AI."

2. Do you have the data, and can you access it?

AI needs inputs. Where does that data live today? Can you export it? Is it clean enough to use, or scattered across emails, PDFs, and legacy systems? Who owns it, and will they give you access?

"It's in the system somewhere" "We'd need to talk to IT" "It's in people's heads"

3. What does success look like in 90 days?

Not "transform the business" - what's the first win? A working prototype? One workflow automated? A decision that used to take a week now takes an hour? If you can't define a concrete milestone, scope will drift and the project will stall.

4. Who will own this internally?

AI projects fail without an internal champion who has:

Authority to make decisions Time to engage weekly (not monthly) Direct knowledge of the workflow being improved

If the answer is "we'll figure that out," figure it out first.

5. Are you ready for it to work?

If the AI does its job, what changes? Will your team trust the output? Will compliance sign off? Do downstream systems need to integrate? The build is often easier than the adoption.

Scoring

5/5: Ready to build

The problem is clear, the data is accessible, and there is a credible owner and adoption path.

3-4/5: Sequence the gaps

Worth pursuing, but fix the missing data, ownership, or rollout issue before expanding scope.

0-2/5: Do groundwork first

AI will not rescue an unclear workflow, absent data, or an unowned internal process.

What to do next If this surfaced a gap, solve the gap first. If it confirmed readiness, define the first 90-day deliverable and build against that, not against a vague “AI strategy” ambition.

Ready to talk? Book a 30-minute consult: calendly.com/mike-campolabs/30min