Choosing an AI tool is a visible decision. Deciding who owns the work it changes deserves just as much attention.
Consider a team using AI to prepare a client proposal. Someone still needs to check the facts, assess the recommendations, protect confidential information, and approve what reaches the client. Those responsibilities should be clear before the pilot begins.
Start by describing the workflow. Where does the work begin? Which inputs matter? Who uses the output? What could go wrong, and who would notice?
Then agree the operating decisions:
- Who owns the business outcome?
- Who checks the output and makes the final decision?
- What information can the tool use?
- When should the team stop and escalate a problem?
- What evidence would justify expanding the pilot?
These questions give the pilot a useful shape. They also make it easier to assess value. Time saved matters, but so do the quality of the output, the review effort, and whether the team can repeat the result reliably.
Keep the first test focused. Choose a workflow with an accountable owner and a clear measure of improvement. Review the experience with the people doing the work, including the steps that became harder.
An AI pilot is an opportunity to learn about the operating model as well as the technology. Ownership helps turn that learning into a decision about what happens next.