AI Readiness Assessment: 10 Questions to Ask Before You Start
An AI readiness assessment tells you whether your business can get real value from an AI project, and what to fix first if it can't. AI readiness means having a clear problem, usable data, connectable systems, people who will own the work and clear rules about risk.
You don't need a long consulting engagement to get started. Answer the 10 questions below for one specific process, because readiness varies from one part of a business to another.
How to score
Give each question 2 points for yes, 1 for partly and 0 for no.
Goal
1. Can you name the specific problem? "Reduce the time it takes to answer support tickets" is specific. "Use AI in customer service" isn't.
2. Do you know today's numbers? You need the current time, cost or error rate. Without a baseline, you can't prove any improvement.
Data
3. Does the data the AI needs exist in digital form? Knowledge that lives only in someone's head has to be written down first.
4. Is that data accurate and current? If your documents contradict each other, an AI system will repeat the contradictions with confidence.
5. Are you allowed to use it this way? Check privacy rules, customer contracts and what a model provider does with your data.
Systems
6. Can your systems connect? Look for APIs or reliable exports. Software that can only be used by hand makes integration slower and more expensive.
7. Can you control access? The AI should have its own identity with limited permissions, and you should be able to log what it does.
People
8. Is there one person who owns the outcome? This should be someone in the business with authority to make decisions, not only someone in IT.
9. Will the people doing the work help? They know the exceptions and they will use the result. Tell them honestly how it will affect their roles.
Risk
10. Do you know what a mistake would cost? Decide which errors are tolerable, which need human review and which are unacceptable.
What your score means
The bands below are a rule of thumb from this checklist, not a formal benchmark.
16 to 20: Ready to pilot. Choose your process and follow a first 90-day plan.
10 to 15: Ready with gaps. You can start, but fix the gaps first. Run a small, read-only pilot while you do.
0 to 9: Not ready yet. Don't buy anything yet. Start with the basics: a clear problem, a baseline and a named owner. These cost little and will improve the process anyway.
A low score on one area matters more than the total. Score 0 on question 5 and you must stop until it's resolved, however good everything else looks.
What to do with the gaps
- Vague goal. Spend an hour with the team that does the work and list where time goes.
- No baseline. Record the process for two weeks. A spreadsheet is enough.
- Messy data. Clean only what your one process needs, instead of launching a company-wide data project.
- Disconnected systems. Check for connectors and APIs, or start with data exports.
- No owner. Don't start until you have one.
Talk to us
Want a second opinion on your answers? DPR Software Labs can review one process with you and tell you what to fix before you spend money on building.