Find the work behind each answer
A short support reply can hide ten minutes of searching. Someone checks a payment, opens an account record, reads an earlier conversation and asks a colleague what happened.
When that request comes back every day, the cost grows with your customer base. Hiring more people is one response. Improving how the request gets resolved is another.
Start by identifying the repeated checks that take time, rather than counting messages alone.
Give the agent a complete, approved process
Consider a member who cannot access a paid community. An agent could check their verified account, confirm the membership status and investigate why the expected access is missing.
If a standard fix is authorized, it can apply it and verify the result. If approval is needed, it sends the relevant information to the right person. Either way, the customer should leave with a clear next step.
The saving comes from reducing repeated investigation and unnecessary back-and-forth. A quick reply that leaves the issue unresolved simply creates more work later.
Include the cost of running the system
AI also has costs: software, usage, setup, maintenance and quality checks. Compare those costs with the staff time saved on tickets that were actually resolved.
A study of AI assistance in customer support found productivity improvements, with results differing across workers. It studied assistance for human agents, so it does not establish the savings an autonomous agent would deliver for your business.
Your own ticket data is the best place to test the business case.
Measure the cost of a resolved issue
Track the time people spend on each request, how often customers reopen it and how often the agent needs intervention. Compare the same type of ticket before and after the change.
Review answers and account actions too. Lower costs only help if the customer receives correct support.
Begin with one high-volume request. Expand when the results show that the workflow saves work without creating extra follow-up.