‘These Five Apps Aren’t Managed’: How Agentic AI Talks Like a Teammate

COMMENTARY: Imagine your system sending you this:

“These five applications are not under management. Based on a review of other devices in the environments, three appear to be standard applications for this environment. Would you like me to bring those under management? The other two aren’t common anywhere else. Should I remove them or manage them as well?”

That’s not a ticket. That’s not a script. That’s an informed, opinionated assistant. And for MSPs already stretched thin, it’s a glimpse of a future where your tools don’t just observe, they help you decide and act.

Goodbye Reactive Loops, Hello Smart Partners

Most MSP “automation” today is still rules and scripts, useful but rigid. Something breaks, it gets logged, queued, reviewed, approved, then fixed. That’s a reactive treadmill.

The next wave is proactive and context-aware. It’s about knowing what’s broken, why it matters, and what should happen next. It’s about a fix you can approve in seconds instead of hours.

One MSP prospect put it bluntly to me recently:

“My team is spending all of our time firefighting. Agentic AI will help you figure out the hot spots.”

That’s the real value. It is not about replacing human judgment, but making sure your judgment is applied where it counts.

Why Agentic AI Has to Happen Now

Scale kills manual workflows. A few tenants can be handled with elbow grease. Dozens or hundreds turn into dashboard chaos. The mental overhead of context switching is where MSP teams burn out.

Agentic systems give you leverage. They catch drift early, surface the right next step, and make approval frictionless. They learn your preferences and keep improving. The payoff is consistency, fewer errors, and a team that has room to breathe.

When AI Feels Like a Peer, not a Pager

The best agentic AI behaves like a trusted peer. It can guide you in technical situations where the “right” choice isn’t obvious, using insights from your environment and others like it.

It’s the difference between “policy XYZ failed to apply” and “policy XYZ failed to apply on 15% of devices. Here’s the fix that worked in similar environments last week.”

That’s informed. That’s opinionated. And that’s a long way from another noisy alert feed.

Make Every Action a Ticket

Here’s a philosophy worth adopting: every action, whether manual, semi-automated, or fully automated, should exist as a trackable ticket or task.

Why? Because that’s how you capture decision-making for the future. It’s how one-off hero work turns into repeatable workflows. It’s how institutional knowledge survives when a key tech leaves.

Over time, this fuels the AI itself, letting it offer your preferred actions proactively. You’re not removing the human. You’re multiplying their impact.

Think MDR for Intune

If you need a mental model, think about managed detection and response (MDR) in security. MDR doesn’t just throw alerts at you; it investigates, recommends, and remediates with a human in the loop.

Now apply that thinking to Intune and endpoint management. MSPs want confidence that:

When something’s off, the system should not only tell you but also recommend or take action and then log it. That’s the endpoint equivalent of MDR.

From Firefighting to Fire Prevention

Agentic AI isn’t about replacing techs or removing oversight. It’s about moving from constant firefighting to true fire prevention. It’s about giving your team an informed, opinionated copilot that can scan the chaos, pinpoint hot spots, and guide the next move before they turn into full-blown incidents.

And if that copilot occasionally tells you, “These five apps aren’t managed. Want me to fix that?” you’ll know you’ve made the leap from tools that watch to agents that work alongside you.

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