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AI-handled tickets sit in the same data as everything else. Separating them is what stops your averages lying to you.
Why it matters
An AI agent resolves the easy cases in seconds. Left in the same average, resolution time falls sharply and your team appears to have become much faster, when what actually happened is that the quick work left the queue.
The remaining human tickets are harder and take longer, and that shows as a decline unless you separate them.
How to tell them apart
- By channel, where the AI agent covers a specific one.
- By tag, which is the most reliable if you set one deliberately.
- By whether the conversation was handed over, which distinguishes fully automated from assisted.
Set a tag on purpose
Rather than inferring it later. A tag applied when the AI agent handles or hands over a conversation makes every future report straightforward, and adding it costs one trigger.
Three groups, not two
Fully automated, started by AI and finished by a person, and purely human. The middle group behaves differently from both and is where most of the interesting change happens.
Report the split, then the averages
Lead with how work divided between those three, then give times within each. A single average across all of them answers no question anybody has.
Fix the baseline once
Agree how AI tickets are identified before anybody builds reports on them. Redefining it afterwards invalidates the comparison you were trying to make.
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