AI Readiness Check

Are you ready to put AI into production?

Eight questions, about two minutes. You get a readiness level, the gaps that usually stall projects, and a recommended first step. Your answers stay in your browser.

01

How clearly is your first AI use case defined?

One use case with an owner and a success metric is what lets you tell, later, whether the system works.

Not yet A shortlist of ideas One use case with an owner and a success metric

02

Who owns the outcome?

Without a business owner, a project stalls at the first trade-off between cost, quality and scope.

Nobody yet An IT or innovation team A business owner with a budget

03

Can the system get to the data it needs?

An AI system can only be as good as the data it can reach and trust.

It is spread across tools, no access Mostly accessible, quality unknown Accessible and checked for quality

04

Do you have real examples to test the system against?

Real examples with known good answers are the baseline every later change is measured against.

No Some, without known good answers Yes, 50+ examples with known good answers

05

Where are you today?

Where you are now decides whether the next step is discovery, a pilot or scaling what already works.

An idea A demo or a pilot Live in production

06

Where would the system need to work?

An answer that never reaches the tools people use does not change the work.

Not clear yet Inside one tool Across several systems, with approvals

07

Have privacy, security and compliance been covered for this use case?

Privacy, security and compliance questions cost less to settle before the build than after it.

Not yet Partly Yes, with sign-off

08

Who will run the system after launch?

Someone has to watch quality, cost and failures after launch, or the system drifts.

Nobody identified Engineers new to AI A team with AI or ML experience

0 of 8 answered