Planning an AI Pilot That Can Reach Production

An AI pilot can produce encouraging results without showing whether the solution will work in everyday operations. Plan for the conditions it will encounter after the trial, including system access, exceptions, support, and user adoption.

Decide what the pilot must establish

Write a specific question the trial should answer. For a document-processing workflow, that might be whether the system can prepare accurate drafts while reducing total review time. A successful demonstration alone does not answer that question.

Use representative cases and users

Include incomplete, inconsistent, and unusual inputs as well as straightforward examples. Involve people who will use the workflow after launch, including those who did not select the tool.

Measure the whole task. A quick extraction step may still require substantial manual checking or data transfer. Keep track of that work so the trial does not overstate the expected savings.

Identify the work needed for deployment

List the systems the solution will touch, the access it needs, and the reviews required before release. Confirm who will answer questions, monitor performance, and handle failures. These details may change the feasibility or cost of the proposal.

Agree on four decisions before testing

Set the acceptance criteria, name the production owner, outline the integration plan, and estimate operating costs at the expected volume. Put a review date on the calendar.

Acceptance criteria should cover important failure cases as well as average performance. A workflow that usually produces a good answer may still be unsuitable if a rare error has serious consequences. Include human review where needed.

Make a documented decision

At the review date, decide whether to proceed, address a specific gap and retest, or stop. If you extend the pilot, define the remaining question, responsible person, and next decision date.

Keep the test results and reasons for the decision. They can help another team avoid repeating an unsuitable approach. When a deployment proceeds, use a limited rollout and compare actual performance with the pilot assumptions.