AI automation becomes worth it when the task is repeated, stable enough to define clearly, and expensive enough that the savings survive human review. If any one of those is missing, the idea often collapses under real use.
Good signs
- the task happens often
- inputs are predictable enough to describe
- errors are visible and correctable
- the current manual process is slow or annoying in a repeated way
Bad signs
- the workflow changes every time
- quality depends on hidden judgment no one has documented
- review takes nearly as long as doing the task manually
- the team wants automation mostly because it sounds modern
The best automation opportunities are usually boring. They remove repeated drag from stable tasks, not from glamorous edge cases.