Run the work yourself, identify one boring station, and let an agent draft into a queue you approve.
Map the work by doing it
Before automation, complete the process manually several times. Write down every step, especially the repetitive parts you dislike. That annoyance list is a better automation plan than a generic list of AI use cases.
Manual work gives you the ability to recognize a good result. If you cannot describe what right looks like, you cannot supervise an agent that produces a wrong result confidently.
Automate one station
Choose a bounded, reversible task: product metadata, caption drafts, research summaries, or a first-pass comparison. Keep customer promises, publishing, and spending behind approval until the workflow earns trust.
Verify the station for several cycles before adding the next one. A stack of checked layers is easier to debug than a complete automated business assembled in one request.
Measure behavior
Do not confuse compliments with evidence. Watch which product sold, which post was saved, which user returned, and which step repeatedly failed.
Small numbers are still directional. Use them to improve the one thing that showed life, then decide whether the next station deserves automation.
Continue the work
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