What if IT fixed issues before you noticed?

IT teams today have more data about the digital employee experience than ever before. They can see which devices are struggling, which applications are underperforming, and which users are most affected. What they often can't do is act on it fast enough.

The gap between knowing something is wrong and actually fixing it is where IT time goes. And as environments grow more complex, with more endpoints, more SaaS applications, and more employees working in more ways, that gap widens.

This is the problem we're focused on with agentic digital employee experiences (DEX).

Seeing the problem is half the battle

When DEX platforms emerged, giving IT teams a structured, data-driven view of employee experience was transformative. Before that, most organizations were relying on helpdesk ticket volume as a lagging indicator of how well things were working. Real-time telemetry across devices, applications, and networks changed what was possible.

But visibility creates a new problem: more signal than IT teams can act on. Our State of Digital Workspace 2026 report shows that enterprise environments generate millions of events daily across endpoints and applications. Most of those signals never translate into resolved issues because triaging, diagnosing, and remediating at scale is a human-speed process in a machine-speed environment.

The question is no longer whether IT can see the problem. It's whether the platform can help them do something about it.

What agentic means in the context of DEX

We use the word "agentic" deliberately, and it's worth being precise about what we mean.

An agentic DEX system goes beyond surfacing insights. It can analyze what it observes, recommend or initiate remediation actions, and operate within the guardrails defined by IT and security teams. It doesn't replace IT judgment—it applies that judgment at a scale that wasn't previously possible. We’re already delivering pieces of this today: DEX Playbooks give IT teams dynamic, data-based investigations with remediation access built directly into the workflow.

This is a natural next step in the autonomous workspace journey. Self-configuring, self-healing, and self-securing endpoints have been our north star at Omnissa. Agentic DEX extends that logic to the experience layer: When an employee's experience degrades, the platform identifies the root cause and takes action instead of simply raising an alert.

For example, a patch rollout introduces a driver conflict on a specific hardware model. The platform detects the resulting experience degradation, correlates it to the patch and affected devices, identifies impacted users, and either proposes a targeted remediation or, where policy permits, automatically executes it. Instead of piecing together what happened across multiple consoles, the IT engineer can review a complete audit trail.

Trust and control are foundational, not optional

Every time we talk about agentic capabilities with customers, the first question is some version of, "What does IT still control?"

The answer is: everything that matters.

Administrators define what actions the system can take, under what conditions, and how much human review is required. The system doesn't earn new permissions on its own. IT teams decide how much autonomy to extend, and they can change that at any time.

We also believe auditability isn't just a compliance checkbox. When AI takes or recommends an action, IT teams need to understand why. Every recommendation and automated action should come with a plain-language explanation of the reasoning behind it. This transparency builds trust over time.

This also fits naturally with how enterprise organizations are approaching AI governance more broadly. Most large IT shops are actively developing policies around where AI should act autonomously, and where it shouldn’t. Agentic DEX should work within those frameworks from day one.

How agentic DEX changes IT operations

The practical impact of agentic DEX isn't subtle. When remediation can begin automatically—or with a single approval click instead of a 30-minute investigation—mean time to resolution drops significantly. IT engineers spend less time on the routine, repetitive work of triaging known issue patterns and more time on problems that actually require their expertise.

There's also a proactive dimension that matters. An agentic system can anticipate issues before employees experience them by:

• Correlating upcoming patch schedules with known device compatibility data.
• Flagging the potential blast radius before a deployment.
• Identifying application performance trends that indicate a problem is developing.

That's a meaningful shift from reactive IT operations to something closer to continuous assurance.

For employees, the change is simpler: Their tools work, and when something goes wrong, it's often resolved before they open a ticket.

How we're bringing agentic DEX to market

We're not building toward a state where Agentic DEX replaces IT decision-making. We're building toward a state where the platform handles the predictable problems automatically, so IT teams can focus on the ones that truly require their judgment.

That means the rollout is gradual by design. We start with high-confidence recommendations: The system tells you what it would do and why, and you decide. As accuracy and trust are established in specific domains, more of that workflow can be automated, with IT retaining the ability to step in at any point.

It also means close collaboration with customers as we develop these capabilities. Execution boundaries, approval workflows, escalation paths all vary by organization, industry, and IT team maturity. We're building this with that variability in mind.

The future of autonomous work starts here

Agentic DEX is the next chapter in the autonomous workspace story. We've spent years getting observability right. Now, we're working on what happens after you see the problem.

We’ll be sharing more in the DEX keynote at Omnissa ONE. And if you're thinking about where automation makes sense in your environment, and where human judgment should stay in the loop, we'd like to be part of that conversation.