Prove the use case before expanding the commitment.

Discuss the use case

Start with what needs proving

A demonstration can show that a model performs a task. A useful pilot must also show how the output enters the workflow, who checks it, what happens when it is wrong and whether the economics hold.

Agree the business baseline and the decision the evidence will support before a build begins. “See what AI can do” is not an acceptance criterion.

Define the boundary

Specify the users, data, systems, volumes and actions included. Identify exclusions and the conditions under which the test must pause.

A controlled environment, shadow evaluation or assisted workflow may be more appropriate than live autonomous deployment. Production exposure is a separate decision, not a requirement for calling the work a pilot.

What the work includes

Pilot definition: the problem, accountable owner, intended result and evidence requirements.

Measurement: representative cases, baseline, quality criteria, complete costs and the treatment of exceptions.

Operating controls: approval boundaries, monitoring, issue handling and fallback appropriate to the scope.

Review points: decisions to continue, narrow, change or stop, with reasons recorded.

A scale recommendation: what is supported, what remains unproven and what needs changing before wider use.

Detailed engineering, specialist assurance and integration responsibilities are defined in the scope, not assumed to be included in a generic package.

Measure the complete result

Count time to an accepted outcome, including preparation, checking, rework and coordination. Track quality and service consequences alongside productivity.

If a pilot releases capacity, name its destination. If it forecasts avoided hiring, identify the funded demand and operating conditions that make the avoidance realistic.

A stop decision can be a valuable result

The evidence may show that the data is unsuitable, the process unstable or the checking burden removes the expected gain. Stopping can limit a larger mistake.

A positive result also has limits. Success with a small team or selected sample is not proof that performance will hold across sites, seasons or customer groups.

Ramon leads the commercial and advisory framing. Applied AI Australia is part of Acquire Intelligence; delivery responsibilities are separately defined.