Reliability
Human in the loop
Designing the workflow so a person reviews or approves at the points where being wrong is expensive.
Full automation is not always the goal. The useful question is not "can AI do this?" but "what does it cost when it gets this wrong?"
Where the cost is high — regulatory filings, money movement, anything a customer receives — the productive pattern is AI doing the tedious 90% and a person applying judgement to the last 10%. The person stays accountable; the work still gets much faster.
This usually beats either extreme: full automation carries risk nobody signed off on, and full manual work wastes the capability entirely.
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