AI readiness assessment for businesses
Readiness isn't about having a data science team. It's about having the data, the process clarity and the ownership that any AI system needs to work in production.
- 12 questions
- Free · no sign-up
- Runs in your browser
How to use · 4 steps
- 01Answer twelve questionsTwo questions each on data, process, systems, team, ownership and risk.
- 02Read the radarEach axis is one dimension, from 0 at the centre to 100 at the edge.
- 03Check your stageExploring, Ready to pilot or Ready to scale — based on your average score.
- 04Work on the weakest twoThe next steps target the dimensions holding you back most.
- Data1
Where does the data for your key processes live?
- 2
How consistent is that data?
- Process3
Are your core processes documented?
- 4
Could you name the first process you'd automate?
- Systems5
Do your main tools offer APIs or integrations?
- 6
How do your tools share information today?
- Team7
Does the team use AI tools in their daily work?
- 8
How does the team feel about automation?
- Ownership9
Is there someone who would own an AI project?
- 10
Is there budget for a first project?
- Risk & review11
How do you handle data privacy and access today?
- 12
Could someone review AI output before it reaches a customer?
The radar fills in as you answer each dimension.
Each axis runs from 0 at the centre to 100 at the edge.
No black box.Every step, in plain words.
Results are estimates for planning, based on the figures you enter. They aren't financial advice or a quote.
- 01
Two questions per dimension; each dimension is scored from 0 to 100.
- 02
The overall score is the average of the six dimensions.
- 03
Stage: under 40 is 'Exploring', 40–69 is 'Ready to pilot', 70 and above is 'Ready to scale'.
Good to know.
Not perfect data — but you need to know where it is and be able to access it. Many first projects start by fixing access to one data source rather than all of them.
A small, time-boxed version of a system running on real work for a limited scope — one team, one process — so you can measure results before committing to a full rollout.
Keep going.
Manual hours audit
Log the hours your team spends on eight common kinds of manual work and get a ranked list of what to automate first.
Lead response scorecard
Seven questions on how fast and consistently new enquiries are handled. Get a score out of 100 and see exactly where deals are leaking.
Agent or automation?
Describe a workflow in six questions and find out whether it needs an AI agent, rule-based automation, or should stay with a person for now.
Tell us the job thatkeeps coming back.
We'll tell you whether it's worth automating, and what it would take. A founder or senior engineer replies within one working day.
