Customer Support: When to Use an AI Agent

In billing support, not all issues require an AI agent. The distinction between understanding, action, evidence needs, and step flexibility allows for the choice between scripts, information retrieval, or a limited agent. Safeguards and an incremental method are recommended for implementation.

Separate Inquiry from Execution and Frame the Stops

It is advisable to clearly distinguish inquiry from execution, especially for high-risk operations like refunds. Adding explicit stop conditions helps limit uncontrolled actions. Before deploying a solution, the accuracy of the cited policies and authorization rules must be verified. The evaluation should rely on realistic test cases and a clear reference. Finally, it is recommended to implement the smallest possible change to address the identified issue.

Scripts, Retrieval, or Limited Agent Based on Need

Standardized requests are well-handled by simple scripts or fixed workflows. When the response involves providing documents, information retrieval is appropriate. A limited-behavior agent becomes relevant if the inquiry requires using different tools based on evidence discovered throughout the process. The use of an agent depends on the separation between understanding the message and the action to be taken, as well as the need for evidence and the degree of flexibility required to choose the next steps.

Start with a Case the System Cannot Handle

Four typical cases of billing-related requests are examined: obtaining an invoice, querying the refund policy, addressing a double billing case, and analyzing an account migration. It is recommended to start with a request that the existing system is unable to manage, and then determine whether the difficulty lies in understanding, evidence administration, or the adaptive choice of subsequent steps. This approach helps target the solution to be developed.