Agentic AI Doesn’t Wait. Can ITIL Still Lead?

[Miguel Donayre]

Agentic AI Doesn’t Wait. Can ITIL Still Lead?

This Won’t Sit Comfortably—And That’s the Point.

ITIL brought order, language, and structure when enterprises needed it most.
It still matters—especially when people remain in the loop.
Even ITIL 4 made real progress toward flexibility and automation.
But it’s rooted in a world where humans drive execution—and structure exists to guide them.

Agentic AI doesn’t wait for handoffs. It doesn’t pause for categorization. It acts.
And if we force that kind of system into frameworks designed for people, we won’t gain control—we’ll create drag.

The frameworks we trusted weren’t built for systems that resolve faster than we can classify.
Unless we evolve, we’ll fall behind the very future we’re trying to lead.

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Part I – ITIL Was Built for a World With People in the Loop

ITIL brought structure to complexity. It gave us a shared language and a framework for scale.
It’s one of the most trusted operating models in the world.

And it didn’t hold us back—it enabled growth, discipline, and predictability.
But it’s still built around one assumption: people drive the process, and structure is needed to guide them.

That assumption still fits many environments today. But not all.

Autonomous systems now detect, interpret, and act in real time—without waiting for human approval.
That creates friction. Not because ITIL is broken, but because its control points were designed for slower cycles.

Example: A user logs something as an incident—but it’s actually a service request.
Under ITIL, that means reassignment, reclassification, and rerouting—before resolution.
Agentic AI resolves, logs, and classifies—before we even look.

Control hasn’t disappeared. It’s just moved—to the point of action.

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Part II – What Agentic AI Does Differently

Agentic AI doesn’t follow step-by-step instructions. It doesn’t route tickets, wait for approvals, or pause for classification.

It acts on live signals, governed by policy and boundaries—set by humans.

• Matches patterns, follows logic
• Stops if a signal doesn’t meet criteria
• Escalates with full context

This isn’t automation in disguise. It’s a system that evaluates conditions in real time and acts within codified trust.

Every action is logged—what happened, why, and under what policy. Oversight is embedded.

Policy logic doesn’t maintain itself. It’s authored, versioned, and governed like any other enterprise asset—with change control, ownership, and audits.

Agentic AI doesn’t eliminate structure. It repositions it—exactly where modern systems need it to be.

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Part III – From Process Obsession to Outcome Obsession

For years, operational performance has been judged by process adherence: SLAs, ticket volume, response time.

That made sense when people handled every step.

And yes, ITIL 4 has embraced outcome thinking and automation. It’s evolving.
But it still wasn’t designed for environments where systems act before tickets even exist.

Agentic AI resolves before an SLA clock starts. It doesn’t wait to be assigned.
It doesn’t ask permission. It just fixes the problem—within policy.

And if we keep measuring these systems by human-paced metrics, we’ll miss what really matters.

We need a new lens—new KPIs:

• Time to resolution from signal detection
• Recurrence suppression
• Policy-bound success rates

These aren’t abstract—they’re proof that autonomy can deliver real outcomes without sacrificing control.

Agentic AI shifts us from tracking compliance to proving value.

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Part IV – Where Agentic AI Is Already Working

Agentic AI demands more than intelligent recommendations or scripted automation.
It requires a system that can act—within policy, at scale, and without delay.

That only works when the platform already owns execution. ServiceNow does.

It runs the core of enterprise operations: service delivery, change control, incident response, compliance, and approvals.
It doesn’t just document decisions—it enforces them.

That’s why autonomous action isn’t a leap. It’s a continuation of what the platform already governs.

Whether it’s ITIL 4, something entirely new, or a hybrid—it needs policy logic to live and execute somewhere.
ServiceNow is built for that.

We’re not asking organizations to abandon control. We’re offering a way to embed it—at the point of action.

Without structure at the point of action, scale breaks.

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Part V – The Hybrid Reality

Most enterprises won’t replace ITIL overnight—and they shouldn’t.
They’ll live in a hybrid state, where human-in-the-loop, human-on-the-loop, and fully autonomous use cases all coexist.

That’s not a compromise. That’s reality.

Agentic AI doesn’t demand a rip-and-replace. It integrates. It complements.

It takes on what legacy systems can’t—while still honoring the structure that works.

Automation 1.0, 2.0, and 3.0 won’t compete. They’ll cohabitate—each handling the right type of work, based on trust, maturity, and risk.

Only one platform provides that kind of operational flexibility: ServiceNow.

This is the evolution. Not the end of frameworks like ITIL, but their transformation—repositioned to support outcomes at any speed.

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Part VI – So What?

“If it’s not broken, don’t fix it.”
That works—until what you’re working with no longer fits what you’re facing.

Agentic AI isn’t future-state—it’s already running in production.

It’s resolving issues, performing actions, and moving faster than the frameworks around it.

The blocker isn’t the tech. It’s the layers of control still optimized for human speed:

• Approval chains that stall decisions
• Escalations designed for human pace
• Risk models that assume slowness equals safety

And the cost is measurable:

• Revenue lost while requests bounce between teams
• Security exposure extended while policy waits for manual input
• SLAs missed—not from complexity, but unnecessary friction
• Customer trust eroded by hesitation—not failure
• Talent drained managing approvals instead of outcomes

Control that lags execution isn’t control—it’s drag.

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Part VII – The Way Forward

ITIL brought structure to human-led operations. It standardized language, guided coordination, and helped scale process across the enterprise.

But Agentic AI shifts the center of gravity.

It doesn’t ask for tickets. It doesn’t escalate by email.
It doesn’t need a human to approve what policy already allows.

If we try to hold it back with frameworks built for another speed, we’ll lose the advantage before we ever use it.

This isn’t about eliminating control. It’s about relocating it—to logic, to context, to the moment action is needed.

The platforms are ready. The shift is already underway.

What comes next isn’t a faster version of the old playbook.
It’s a new model—designed to operate where speed, policy, and trust converge.

The frameworks of the last two decades were built for service managers.
The next two will be built by platform owners, CIOs, and leaders willing to rethink control.

This future will be written by those who act—not those who wait.

[gobogo90]

• This is an excellent way to frame the transformative power of Agentic AI.  Frameworks can still play a part as the human interface if you will.  Connecting data securely at scale has never been more important.

[pbusch]

Great write-up on a critically important topic.

[Jyo2]

great article. All the more reason to make sure to not use technology for fixing process issues