AI is useful when it enters a clear and measurable process. Not when it is added on top of a workflow that is already confused.
Good signs
- the team repeats the same task many times every week
- there is data, examples or documentation to work with
- the output can be reviewed by a person
- an error does not stop the whole operation
- you can measure saved time, quality or fewer mistakes
Typical use cases
- classifying incoming requests
- preparing draft replies
- searching internal documents
- enriching data from different sources
- generating operational reports
- helping a team follow a checklist
When to avoid it
If the process is unclear, the data is messy or nobody knows how to verify the result, AI will usually make the problem more expensive.
First fix the workflow. Then, if it makes sense, automate it.