The demo always looks the same: someone types a sentence and a complete deliverable appears. Real workflows are less theatrical. The value shows up in narrow places where the task is repetitive, the input is messy, and a near-right answer reviewed by a human beats a perfect answer that takes three days.
Where agents genuinely help
- Turning unstructured input — call notes, emails, forms — into structured records
- Drafting the first version of routine replies for a human to approve
- Summarising long threads so whoever picks up the account has context
- Flagging records that look wrong, rather than deciding what to do about them
Where they cost you
Any step where being confidently wrong is expensive. Pricing, contractual commitments, compliance answers, and anything a customer will treat as a promise. In those places an agent should prepare the work, never publish it.
Use AI where review is cheap and error is recoverable. Keep humans where being wrong has a cost you cannot claw back.
The practical shape
The systems that work in production tend to look boring: an agent that reads incoming enquiries, extracts the fields, writes a CRM record, drafts a reply, and stops. A person spends fifteen seconds approving rather than four minutes typing. Multiply that across a week and the return is obvious — without betting the customer relationship on a model's confidence.