1. Pick a specific task
Begin with one repeatable task rather than a broad ambition to add AI everywhere. Describe its inputs, expected output and the person who will judge whether the result is useful.
2. Understand the existing workflow
Observe how the task is done today. An AI feature can create extra work if it does not fit the decisions, systems and hand-offs people already use.
3. Decide what good looks like
Prepare representative examples and a simple evaluation approach before the demonstration. Include awkward and incomplete inputs, not only cases where the tool is likely to work well.
4. Be deliberate about data
Understand what information the pilot needs and who is authorised to use it. Keep the pilot’s data needs narrow and agree the handling arrangements before implementation.
5. Keep review visible
Decide when a person needs to check an output or approve an action. Make uncertainty and failure recoverable within the workflow instead of relying on a polished demonstration.
6. Define the next decision
A pilot should help you choose what to do next: continue, change direction or stop. Record the evidence, remaining limitations and what production operation would require.
Make the pilot answer a real question
etech can help shape a focused discovery or proof-of-concept engagement. Bring a workflow and a question; we can work through the options together.
