A support specialist already has a ticket open, a draft reply in progress and the relevant customer record on screen. An AI feature should help finish that work. Requiring a separate chat, repeated context entry and a copied answer may add a new task to the one it was meant to improve.
Choose a useful first feature
In this illustrative application, let the assistant prepare a reply draft from approved support material and the current ticket. Keep the specialist’s unsaved text intact. Show the proposed text in a place where it can be inspected and edited before the existing send action is used.
Define the contribution narrowly enough to judge. Does the draft answer the question? Does it preserve the necessary qualification? Does it reference material the specialist can inspect? A broad promise to make support intelligent is harder to implement and harder to evaluate.
Use existing access controls
The assistant should receive only the ticket and source material available for this user and task. OWASP’s RAG security guidance emphasizes carrying access decisions through retrieval and output. For this example, that means the AI feature follows the application’s existing data responsibilities.
A model does not need the entire customer history because the application can technically retrieve it. Select the context required for the proposed reply. Keep unrelated records and unnecessary private content out of the request.
Source: OWASP · RAG Security Cheat Sheet.
Handle delays and unavailability
A response may arrive after the specialist has edited the ticket or moved to another case. Associate the suggestion with the context that produced it, and avoid replacing current work with a stale result. Let the person request a new draft when relevant inputs change.
If the model is unavailable or the approved material cannot answer the question, preserve the existing reply flow. Explain the state within the application and let the specialist continue. The AI contribution should have a defined failure behavior, just like another dependency in the product.
Test the complete interaction
Test with synthetic tickets and representative tasks. Assess the proposed text, the source access, the placement in the interface and the final action. An accurate paragraph can still be unhelpful if it overwrites a draft or makes the user hunt for the original record.
- The suggestion belongs to the ticket and context currently being reviewed.
- The user can inspect, edit or discard it before sending.
- Restricted source material does not enter the draft.
- The ordinary task remains usable when the AI contribution fails.
Expand based on observed value
Begin with one task whose outcome can be inspected. Use feedback from that interaction to decide whether another suggestion, a new source or a more capable workflow is warranted. The application already has a place in the user’s day; earn the AI feature’s place within it.