You bought the AI. Did you build the team?

Start with a workflow, not a purchase.

Choose a specific business task and describe the result you need. What is slow, inconsistent, or difficult to scale today? Record the current process and how the team judges a good output. This gives you a practical way to discuss whether AI belongs in the workflow and which parts should remain under direct human control.

Make ownership explicit.

Identify the process owner, the people who understand the source data, the technical contributors, and the reviewer accountable for the output. Depending on the use case, security, legal, compliance, or other internal teams may need to participate. One person may cover several responsibilities, but the responsibilities should not disappear because the project is small.

Protect capacity for implementation.

A finance team still has a close to finish while a new workflow is being built. Clarify which people can dedicate time to testing, exception handling, training, and documentation. Consider whether the requirement is a systems specialist, a process improvement professional, an experienced finance reviewer, or temporary coverage for day-to-day responsibilities.

Measure the work after the launch.

Track review effort, error handling, exceptions, adoption, and the quality of the final output alongside speed. Agree who can change the workflow and who will maintain it. A pilot is a starting point; an operating model gives the team a way to keep learning and to stop or revise a use case when the results do not meet expectations.

Turn the questions into a scope.

If this is on your desk, we can discuss the business need, the experience required, and the appropriate engagement model through Robert Half.