Five Questions Every Executive Should Ask Before Launching an AI Initiative

Start with the decision, not the technology

AI initiatives rarely fail because the technology underperforms. They fail because nobody agreed, in advance, on what decision or process the system was meant to improve. Before funding is approved, the sponsoring executive should be able to name the specific work the organization wants to do differently and describe what better looks like in operational terms.

The five questions below are the ones we use in the first working session with a leadership team. They take an afternoon to answer honestly and they save quarters of rework.

1. What business outcome are we buying?

State the outcome in the language the business already uses: cycle time, cost to serve, error rate, capacity released, revenue retained. If the answer is a capability rather than an outcome, the initiative is a research project and should be funded and governed as one.

2. Is the data fit for the decision we are automating?

Model quality is bounded by the data underneath it. Check lineage, completeness, refresh frequency, and access rights before committing to a delivery date. In regulated environments, also confirm that the intended use is consistent with the basis on which the data was collected.

3. Who is accountable when the system is wrong?

Every deployed model produces incorrect outputs at some rate. Name the accountable owner, define the review path, and decide in advance where a human must remain in the loop. This is a governance question, not a technical one, and it belongs to the business owner rather than the delivery team.

4. What changes in the operating model?

If roles, controls, and performance measures stay exactly as they were, the organization will keep working the old way alongside the new system. Identify the processes and job designs that must change, and plan that change with the same seriousness as the build.

5. How will we stop?

Set the criteria for scaling, pausing, and retiring the initiative before it begins. Programs without a defined exit tend to continue on momentum, absorbing budget that has better uses elsewhere in the portfolio.

Where this leads

Teams that can answer these five questions usually move faster afterwards, because the disagreements were resolved while they were still cheap. Teams that cannot answer them are not ready to build, and that is useful information on its own.