Before you spend money on AI, it helps to know whether your business is ready for it. Most stalled AI projects trace back to missing preparation. Use these seven questions as a quick check.
The seven questions
- What specific process are you trying to improve? A clear task, such as answering inquiries or preparing reports, works better than a vague goal like “use more AI.”
- Where does the data for that process live? List the systems involved, such as email, a CRM, spreadsheets, or accounting software.
- Is that data organized and current? Scattered or out-of-date data is the most common blocker.
- Who owns the process? Someone needs authority to change how the work is done and to judge the results.
- What happens if the AI is wrong? Low-risk tasks are the best place to start. High-risk tasks need human review.
- Can your systems connect? Tools that cannot share data with what you already use create extra manual work.
- How will you measure success? Decide in advance what you will track, such as hours saved, errors reduced, or faster response times.
How to read your answers
If you can answer most of these confidently, you are in a good position to run a small pilot. If several are unclear, that is useful to know before you buy anything. The fix is usually preparation: tidy the data, name an owner, and pick one narrow task.
What a readiness review adds
A readiness review goes deeper on the same areas: your business profile, data touchpoints, risk tolerance, technical readiness, and team adoption. You finish with a 90-day plan and measurable goals, so your first project has a clear target.
Common blockers and quick fixes
- Data is scattered. Pick the one system that should hold the source of truth for your pilot process and tidy that first.
- No clear owner. Name one person who can make decisions about the process and review the results.
- The goal is vague. Narrow it to one task with a measurable outcome.
- Security concerns. Write a short AI policy and approve tools before people start using them.
- Staff hesitation. Involve the team early, train them on real examples, and have leaders use the tools too.
A sample 90-day path
- Days 1 to 30: pick one process, prepare the data, name an owner, and set the policy.
- Days 31 to 60: run a pilot with a small group and track the numbers you chose.
- Days 61 to 90: review the results, document what worked, and decide whether to expand, adjust, or stop.
Want an outside view of where you stand?Our AI readiness assessment reviews your data, systems, risk, and team, then gives you a practical 90-day plan.
See the AI readiness assessment
