All learning
Practical advice
Set a stopping rule for every AI trial
Decide in advance what success, revision and cancellation look like so a weak experiment does not become permanent overhead.
The practical answer
Start with this principle
A trial needs an end date and a decision rule. Agree the minimum useful result before starting, then keep, change or stop the workflow using evidence.
Do this in order
Three steps you can use today
Choose one outcome measure
Use a measure connected to the task, such as minutes per item, correction rate or response time. Avoid vague goals such as improving productivity.
Set the review point
Pick a date or sample size that gives the trial a fair chance without letting it drift. Name the person who will make the decision.
Define all three decisions
Write the threshold for keeping the workflow, the change that earns another trial and the condition that means stopping it.
Copy and adapt
Trial stopping rule
We are trialling: ............................................
Started: .......... Decision date: ..........
We will keep it if, by the decision date:
- It has been used at least ....... times on real work
- It saved at least ....... minutes a week
- It produced fewer than ....... results we had to reject
We will stop if none of the above are true.
Write the decision date before you start. A trial with no end date becomes a
subscription nobody reviews.