01Define the problem before choosing the tool
A useful AI agenda starts with the work the organisation needs to improve. Which decision is too slow? Which task consumes disproportionate effort? Which service could become more useful to its users?
These questions give the technology a purpose. They also make it possible to compare an AI approach with process redesign, automation or a simpler change to the existing workflow.
02Test the full operating requirement
A promising demonstration does not establish readiness for deployment. Consider the data required, the quality standard, the controls, the user experience and the cost of operating the solution.
Define where human judgement remains essential and how errors or exceptions will be handled. Assign responsibility for the process—not just the model.
Assign responsibility for the process—not just the model.
03Make value and safeguards explicit
The business case should define what success looks like and how it will be measured. Faster completion matters only if the result remains useful, reliable and appropriate to the task.
Governance should be proportionate to the risk of the use case. Decisions about access, review, data use and monitoring belong in the design rather than being left until launch.
04Design the path beyond the pilot
A pilot should answer a defined set of questions about performance, usability, risk and economics. Its next step should not depend on enthusiasm alone.
Plan for the organisational changes required to scale: process ownership, user capability, integration, support and ongoing measurement. AI transformation becomes meaningful when the new capability improves the way work is done.
