A ticket comes in. The AI classifies, categorizes, and routes it.

It searches historical tickets for similar issues. It finds a match from 2 months ago. It attaches that resolution as a suggestion.

It is a helpful feature and can help save time in ticket resolution.

It is a good early application of AI.

And just as with any technology in the early days, there are issues.

The problem? The historical ticket was about a different user. On a different system. With a different set of applications.

Imagine going to the doctor and being handed other patient's charts as the basis for your diagnosis. "Go home and try what the other patients did." But your vitals were never taken. You were never looked at.

That's what most AI Ticket Triage Agents do today.

They pattern-match on what worked before. They don't check what is happening now.

The issue then is historical tickets are static. Stale. Generic.

Yet your infrastructure is live. Dynamic. Relevant.

What we need is AI that checks your systems. Right now. In real-time.

Not what worked for someone else last month.

Question to Ask

"What live systems does your AI Agent investigate? What diagnostics does it run?"

If the answer is "None," then that's just pattern-matching on the past, not investigating what's happening now.