AI READINESS CHECK
Find what needs attention before adopting AI
Choose one workflow you want to improve and answer 12 evidence-based questions. See your current readiness and up to three gaps to address first.
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How we assess the five dimensions
- A defined use case
What we look for
A recurring task, its volume and a way to compare results before and after a change.
What good looks like
The scope has clear boundaries, workload records exist and the team can define a useful outcome.
- Accessible data
What we look for
Where the data lives, who can authorize access and whether usable examples exist.
What good looks like
Access is authorized, formats and gaps have been checked and verified answers are available for testing.
- A repeatable process
What we look for
Documented steps and a person who can handle exceptions.
What good looks like
People can follow the process, handoffs are clear and failures have a route back to a human.
- Owners and users
What we look for
Who decides scope, who accepts the result and whether the people doing the work can participate.
What good looks like
An accountable owner can make decisions, and users have a way to test and report problems.
- Governance and risk
What we look for
Responsibility for sensitive data, access permissions and incorrect outputs.
What good looks like
Data rules are clear, risky outputs get human review and mistakes can be traced and stopped.
AI readiness questions
Is this AI readiness check suitable for small businesses?
Yes. Answer for one real workflow; a dedicated data team is not required. The result helps identify which foundation to clarify first, rather than asking your company to assemble every resource at once.
Does a high score mean we can deploy AI immediately?
No. This is planning guidance, and the score and tiers are not validated launch standards. You still need to test quality, cost and risk with real data and complete access, security and user acceptance reviews.
How is the score calculated?
Each of the 12 questions scores 0 to 3. The total is divided by the maximum of 36, converted to a percentage and rounded. Dimensions use their own maximum. Scores below 40 mean Exploring, 40–69 mean Piloting and 70 or above mean Ready to scale.
Should I answer for the whole company or one department?
Use the same workflow for all questions. Different departments and tasks can have very different data, ownership and risks. Separate checks make the next steps more specific.
Are answers and results stored or published?
Answers stay in this tab’s browser session so you can continue after a refresh. They may not persist after the session closes. Shared links contain only the total and tier. Tool usage events may record the total score and tier.
Can we start before our data is fully organized?
Start by mapping the workflow and inspecting samples rather than immediately automating it. Identify data owners, obtain authorization, check formats and establish verified answers to define a useful pilot.