Choosing a useful AI automation
Find a repeatable workflow, understand its data and decide where human review belongs.
Sample editorial content for preview. Review before publication.
Look for repeatable work
Begin with a task that happens often and has a recognizable input and output. Examples might include organizing incoming requests or preparing a first draft from approved material. Ask how the work is completed today and where delays occur. Automating an unclear process can make its problems harder to understand.
Check the available information
An AI workflow depends on the information it can access. Identify which sources are relevant, who owns them and whether they can be used for the proposed purpose. Consider incomplete, outdated and conflicting information. Decide what the system should do when the input does not provide enough context.
Keep human review intentional
Decide which outputs require a person to check them before an action is taken. Give reviewers useful context and a clear way to correct or reject the output. Higher-impact actions deserve more careful controls. An automation should have defined boundaries rather than unrestricted access to every system.
Evaluate before expanding
Test representative examples and include difficult cases, not only easy ones. Compare the output against criteria your team can explain, such as accuracy, completeness and handling of uncertainty. Start with a limited workflow, monitor its behavior and expand only when the evidence supports the next step.