What the term really means
A system based on an AI model that plans tasks and uses tools to achieve a defined goal.
How it works in practice
An agent may read a customer request, check an order in an approved system and draft a response while leaving refunds to a person.
The decision to make before implementation
The decisive boundary is permission scope: the agent should see and perform only the operations required by that workflow.
How to verify that it works
Track correctly completed cases, escalations, cost per task and every tool call that can affect a customer. Compare results with an agreed baseline and review routine cases, difficult exceptions and human hand-offs separately. A practical AI Agent test should have an owner, a review date and a recorded example of an outcome the team will not accept.
The PAR HOUSE Agency approach
We approach AI Agent from the workflow rather than a tool demonstration. The decisive boundary is permission scope: the agent should see and perform only the operations required by that workflow. We then build a small measurable scope, record assumptions and expand only after quality review.
