AI readiness checklist for small and mid-size businesses

Most failed AI projects fail before any code is written. They start without a clear problem, without owners, or without a plan for the data. This checklist helps you avoid that.

Is there a specific problem to solve?

“We should use AI” is not a problem. “Our estimators spend eight hours a week re-keying supplier quotes” is. Write the problem in one sentence, including who has it and how often.

Can you measure success?

Choose one number before you start: hours saved per week, response time, error rate, or cost per task. Without a baseline, you cannot prove the project worked.

Do you know where the data lives?

AI needs inputs: documents, emails, records, spreadsheets. List where they are, who owns them, and whether they contain personal or confidential information. You do not need perfect data, but you do need to know what you have.

Who owns the outcome?

Every project needs one person on the business side who cares about the result and can make decisions. Without an owner, projects drift.

What are the privacy and security limits?

Decide what data may be sent to outside AI services and what must stay inside your environment. If you handle personal information, review your obligations under PIPEDA, Alberta PIPA or applicable US state laws with your advisors.

Will people actually use it?

The best solution fits into existing work. Involve the people who will use it early, and plan a short pilot with a small group before rolling out widely.

What if you answered “not yet” to some?

That is normal. A short readiness assessment can turn those gaps into a plan. Talk to us if you want help.