Before investing in AI: the questions your board should ask

AI investment should begin with a business decision. A promising demonstration is a reason to investigate further; a decision to scale needs a clear purpose, ownership and evidence.

What problem are we trying to solve?

Describe the current task and who experiences the problem. Identify the improvement you want to see, how you will measure it, and the baseline you will compare it with. Time saved, quality and service outcomes need to be assessed in the context of the whole process.

What does the full business case include?

Look beyond the tool price. Consider data preparation, integration, review time, training, support and the effort needed to change the way people work. Agree which benefits are assumptions and which have been demonstrated.

Who remains accountable?

Name the business owner and decide where human review is needed. Define what the system may do, how exceptions will be handled and when it should stop or escalate. Match the controls to the consequences of an incorrect output.

What evidence will support the next decision?

A focused pilot should have a clear scope, realistic examples and agreed success criteria. Examine errors and difficult cases as well as the successful demonstrations. Agree what would justify proceeding, changing direction or stopping.

How will this operate after the pilot?

Consider ongoing monitoring, changes to the tool, staff adoption and ownership of support. Scaling creates an operating responsibility as well as a technology decision.

Digitley AI Strategy & Governance helps leaders assess worthwhile opportunities and put practical ownership and oversight in place. Advisory and implementation scopes are agreed separately.