Room Check Found a Problem. Now what?

By Sam Kennedy

Part 2 of our series Inside Room Check

Finding a problem isn't the same as solving it.

For years, AV and UC monitoring systems have gotten better and better at telling us when something is wrong. A device goes offline. A configuration changes. A system throws an error. An alert fires.

And then what?

Someone has to figure out what actually happened, decide whether it matters, work out what to do about it, make the change, and hope the room is really working again.

We got very good at detecting problems. We never quite got good at solving them.

In Part 1 of Inside Room Check, I walked through how Lena compares a room's actual state with the target state we've defined for it. That raises a more interesting question, though: what happens when she finds something wrong?

That's where Room Check starts to move past monitoring and into actual operations.

An Alert Isn't a Resolution

Think back to the Zoom Room from Part 1.

Someone had changed the display input, turned the volume down, and muted the system before leaving. The technology was still online. The room just wasn't ready for whoever walked in next.

Even if a traditional monitoring platform had caught every one of those changes, an administrator would still have work ahead of them. They would need to read the alerts, figure out what the room was supposed to look like, log into the right systems, make the changes, and then check whether the room was actually ready.

At a small scale, that's manageable. Across hundreds or thousands of rooms, it becomes an operating model that depends entirely on people showing up.

Room Check takes a different approach. Instead of stopping at “something is wrong,” Lena can ask a better question: can I do something about it?

Detect, Diagnose, Act

When Lena runs a Room Check, she compares the room's real-time state against the target state defined for that room and its intended use.

If the two don't match, she has something a simple alert never gives you: context. She knows the actual state, she knows the target state, and she knows exactly where the two diverge. That's what creates room to act.

In our Zoom Room example, Lena found a handful of issues. The system was muted. The volume wasn't where it should be. The display was on the wrong input.

None of that required someone to grab a tool bag and walk across the building. These were configuration problems, so Lena fixed them. She took the system off mute, brought the volume back to the target level, and switched the display to the correct input. Then she tested the conferencing experience herself by placing a Zoom call.

The goal was never just to clear the alert. It was to actually get the room ready again.

Some Problems Need Software. Others Need People.

This distinction matters.

Not every room problem can be solved automatically, and not every one should be.

Picture two scenarios. In the first, a display is set to the wrong input. In the second, someone has physically unplugged a cable. Both leave the room unready, but they call for very different responses. The first is something software can likely handle on its own. The second needs a person.

That points to a simple operating principle: let software handle the problems software can solve, and let people focus on the ones that actually need them.

This isn't about replacing the AV technician or administrator. It's about clearing unnecessary work off their plate. If Lena can correct ten configuration issues on her own, the administrator doesn't need ten more tasks that day. They need to know about the one room where someone genuinely has to show up.

Rethinking the Morning Room Check

This becomes especially powerful once you think about how most organizations prepare rooms today.

Someone comes in before meetings or classes start and walks the building room by room. Turning things on, checking displays, verifying settings, testing the conferencing system, fixing whatever looks off, then moving on to the next room.

Most of those rooms are probably fine. But someone still has to check every one of them, because there's no way to know ahead of time which ones actually need attention.

The technician isn't spending most of that time fixing problems. They're spending it looking for problems. That's the part of the workflow worth questioning.

What if software checked the rooms first? What if it corrected what it found and tested the room afterward? What if the administrator could start the day already knowing which rooms actually need a person?

At that point, you're not just automating a room check. You're changing how the team works.

From Alert Fatigue to Exception-Based Operations

This matters even more at scale.

A large environment generates a constant stream of operational noise: warnings, status changes, tickets, alerts, configuration differences. Some need immediate attention. Some can wait. Some can be fixed remotely. Some may not need a person at all.

If every one of those still lands on an administrator's desk, automation hasn't actually reduced the workload. It has just found a faster way to create more of it.

The better model is exception-based operations. Lena handles what she can, flags what she can't, and the administrator focuses on the exceptions.

Instead of asking “what do I need to check today,” the question becomes “what actually needs me today.”

That's a genuinely different way to start a morning.

Fixing Something Isn't the Same as Confirming It's Fixed

There's one more piece worth calling out.

Taking an action doesn't automatically mean the problem is solved. If Lena changes a setting, the job isn't done the moment the command goes through. What matters is whether the room is actually back in the state it needs to be in, and the only way to know that is to check.

In the demonstration from Part 1, Lena didn't stop at restoring the configuration. She placed a Zoom call to test the conferencing experience, then ended it once the test was complete.

That's the difference between a workflow that goes detect, correct, test, verify, and one that goes detect, alert, and hope someone handles it. It sounds like a subtle difference on paper. In practice, it's enormous.

People Still Need to See What Happened

If AI is going to take action inside an enterprise environment, the people responsible for that environment need to know what it did.

Room Check isn't meant to be a black box. Once a check is complete, Lena puts together a report showing what she found, what she changed, and what the outcome was. That information lives inside Lena and can also go out by email to whoever needs to see it.

That's an important balance to strike: automation without losing accountability. The administrator doesn't have to perform every action by hand, but they can always see what was done and why. As we give software more responsibility inside these environments, that kind of visibility only becomes more important.

This Isn't About Fewer People. It's About Using Them Better.

There's a tendency to frame AI and automation as being about replacing people. I think that's the wrong lens for this problem.

AV and UC teams already manage more technology than ever: more rooms, more device types, more platforms, more integrations, more expectations from the people using all of it. None of that is getting simpler.

The question was never whether we still need skilled people. We do.

The real question is whether those people should spend their mornings walking into fifty rooms just to find out that forty seven of them were already fine, or manually fixing a display input that software could have corrected in seconds.

The scarce resource here was never the alert. It's human attention. Room Check exists to protect that attention for the problems where it actually matters.

From Monitoring to Operations

This is really the larger shift happening across enterprise technology.

Monitoring tells you what happened. Operations does something about it. Autonomous operations takes that one step further: understand what the room is supposed to look like, observe what it actually looks like, spot the difference, fix what can be fixed, confirm it worked, escalate what genuinely needs a person, and report back on all of it.

That's the workflow we're building toward with Room Check. Catching a broken room five minutes before a meeting is useful. Catching it, fixing it, testing it, and having it ready before anyone even knows there was a problem is a much better outcome.

Next in the Inside Room Check Series
Part 3: How Do You Know a Meeting Room Is Actually Ready?
A room can be online and still not be ready. In Part 3, we'll look at why room health needs context, how target states change what “working” even means, and why the next stage of AV and UC operations may be less about measuring uptime and more about measuring readiness.

To learn more or to schedule a demo:
Visit: www.netspeek.ai
Contact: lena@netspeek.com
Demo: Book a live walkthrough