Free tool · 10 questions · About 3 minutes
AI Automation Readiness Assessment
AI automation readiness is how prepared a business is to hand repetitive work to software and AI without creating new problems. It comes down to four things: how clear and consistent your processes are, how clean and reachable your data is, how well your tools connect, and whether there is a real business case with an owner and a budget.
Answer 10 multiple-choice questions. The assessment scores each of the four areas from 0 to 100, combines them into one readiness score with fixed, published weights, ranks the three workflows to automate first, and lists the prep work and guardrails your answers call for. No AI guesswork, and no email needed to see your results.
01 / 10
About 3 minutes
Methodology
How the score is calculated
The score is deterministic: the same answers always give the same result. Each answer maps to a point value from 0 to 100, those points roll up into four sub-scores, and the sub-scores are combined with the weights below.
- 01
Process clarity
75% how standardized the work is (written down and consistent scores 100, changes case by case scores 10), 25% whether you know how many hours the repetitive work takes.
25% weight
- 02
Data readiness
65% data quality (clean and exportable scores 100, locked away or on paper scores 15), 35% how structured the places it lives are, averaged: CRM or accounting software 100, industry software 85, spreadsheets 70, email 45, paper 15.
30% weight
- 03
Integration readiness
70% how well your tools already connect (linked cloud tools 100, desktop software 35), 30% whether a system of record exists, such as a CRM, accounting or industry system.
20% weight
- 04
Business case
35% hours of repetitive work at stake, 35% whether a decision-maker owns it and how soon, 30% budget readiness.
25% weight
Bands
- Ready to automate now: overall score of 70 or more, with no single area below 40.
- Ready with prep: overall score from 45 to 69, or 70 and above with any area below 40.
- Foundations first: overall score below 45.
The weakest-link rule exists because one weak area, such as data that cannot be exported, tends to stall a project no matter how strong the rest is. Data readiness carries the most weight because an automation can only be as reliable as the records it reads, and fixing data is usually the slowest prep step.
What to automate first
Each workflow starts from our estimate of how well it usually suits automation, based on how rule based and easy to check it is: data entry and intake 85, documents and follow-ups 80, scheduling and reporting 75, customer support 70. It gains 5 to 10 points when your data already lives in a system that suits it, and customer support loses 10 when the data is regulated. Workflows you flag as pain points always rank first, ordered by that fit; any open slots go to the best-fit workflows you did not flag. The top three are your shortlist.
Business size and data sensitivity do not change the score. Size shapes the recommended approach, and sensitivity decides which guardrails you need, such as human review, access controls and audit logs.
The score is a guide, not a guarantee. It reflects your answers, not an inspection of your systems, and it cannot promise a time saving or a return. Use it to decide where to look first.
Questions
Common questions about AI automation readiness
What should a small business automate first with AI?
Start with work that is high volume, rule based and easy to check: data entry between systems, lead and client intake, invoice and document processing, and customer follow-ups. Pick one workflow, measure how long it takes today, automate it with a person reviewing the output, and expand only after it works. Avoid starting with anything that moves money or gives customers advice without human review.
How do I know if my business is ready for AI automation?
You are ready when four things are true: the process is done the same way each time, the data it needs is clean and reachable, your tools can connect through APIs or integrations, and a decision-maker wants it done and has budget for it. If one of the four is missing, fix that first. This assessment scores each of the four from 0 to 100 and tells you which one is holding you back.
Is it safe to use AI automation with sensitive customer data?
It can be, with the right guardrails: least-privilege access so each automation sees only the fields it needs, human review before anything customer-facing or financial goes out, audit logs of every automated action, and vendor agreements that cover where data is processed (for example a BAA for health data). Sensitive data does not rule automation out; it makes the design more careful.
Should I use off-the-shelf tools or custom AI automation?
Use off-the-shelf tools when they cover the workflow and your volume is modest, because they are cheaper and faster to start. Custom automation earns its cost when a workflow runs many times a day, spans several systems, or needs rules no product supports. Many businesses end up with both.
How accurate is the readiness score?
It is a structured guide, not a prediction or a promise. The model is fixed and published on this page, so the same answers always produce the same score. It cannot see your actual data or processes, so treat it as a starting point for planning rather than a verdict.
Do I need to give my email to see results?
No. Results appear as soon as you answer the last question. Your answers are kept in the page link, so you can copy it to revisit or share your result. Asking for a free automation plan afterwards is optional.