Practical guide · AI adoption
AI readiness checklist: 10 questions to answer before a business pilot
A successful AI pilot begins with a defined business problem, appropriate information, clear safeguards, and a way to evaluate whether it helped. This checklist can help leaders, operations teams, and project owners ask the important questions before selecting a tool.
Start with the problem, not the product
You may discover that the best next step is a process redesign, clearer knowledge ownership, better reporting, or a smaller technology change rather than AI.
1. What business problem are we trying to solve?
Describe the current workflow, who experiences the problem, how often it happens, and why it matters. Avoid beginning with a tool or model name.
2. What happens today without AI?
Map the current process, time, handoffs, exceptions, workarounds, and existing tools. A simpler process change may solve the issue more reliably.
3. How will we recognize a useful outcome?
Choose a small set of measures tied to the problem, then capture a baseline before the pilot. Depending on the use case, this may include quality, time, error rates, customer effort, or cost.
4. Is the right information available?
Check whether the data and knowledge are accurate, current, sufficiently complete, permissioned, and usable for this purpose. Missing or outdated knowledge will affect output quality.
5. Is AI suitable for the task?
Consider how often the task occurs, how predictable it is, whether the output can be checked, and how harmful a mistake could be. Do not automate a task simply because it is repetitive.
6. What are the privacy and security requirements?
Identify sensitive information, access controls, retention needs, vendor data practices, and applicable organizational or legal requirements before sharing data with a tool.
7. Where is human judgement required?
Define who reviews outputs, what needs approval, what confidence or quality threshold is acceptable, and when a case must be escalated to a person.
8. How will we test accuracy and edge cases?
Use representative examples, including difficult and unusual cases. Track incorrect, incomplete, biased, or unsafe output and decide how those failures will be handled.
9. What does the pilot require to operate?
Account for integration, maintenance, training, monitoring, usage costs, process ownership, and the people who will support the workflow after initial testing.
10. What decision will we make at the end?
Agree in advance whether the pilot will stop, change, continue, or expand, based on evidence. A pilot is valuable even when it shows an idea should not be scaled.
Turn the checklist into a decision
Capture your answers in a short brief: the problem, current process, candidate use case, required data, risks, human checkpoints, baseline, and pilot decision criteria. If important answers are unknown, resolve those gaps before increasing the scope.
The right level of review depends on the sensitivity of the data, the impact of an incorrect result, and the scale of the proposed use. This checklist is a planning aid, not a substitute for your organization's legal, privacy, security, or compliance review.
Need help prioritizing AI use cases?
Explore a structured readiness review covering business value, workflow fit, data, risk, human oversight, and practical next steps.
Explore AI readiness consultingWritten by Abhishek Shukla, who works across customer experience, operations, practical AI adoption, and human-centred leadership.