Automation has become one of the most talked-about levers in IT service management. Every tool demo promises it. Every roadmap includes it. Every improvement initiative seems to end with, “and then we’ll automate it.”
But here’s the uncomfortable truth:
Automation doesn’t fix broken processes. It accelerates them.
I’ve seen organizations automate chaos at scale; faster ticket misrouting, faster rework loops, faster escalation noise, all while proudly declaring progress because the tool is “doing more.”
The problem isn’t automation.
The problem is what we automate, and when.
Automation is a force multiplier — not a cure
Automation amplifies whatever already exists:
- Clear processes become faster and more consistent
- Unclear processes become faster and more confusing
- Poor behaviors become embedded and harder to unwind
When accountability, ownership, and intent aren’t understood, automation becomes a way to avoid hard conversations:
- “The workflow handles that.”
- “The tool decides priority.”
- “We don’t need training anymore.”
That’s not maturity. That’s offloading accountability.
You don’t end up with better ITSM.
You end up with very efficient dysfunction.
Where automation commonly fails
Automation struggles when it’s introduced:
- Before processes are clearly defined
- When data quality is inconsistent or optional
- When ownership is vague (“someone will pick it up”)
- As a headcount-reduction strategy rather than a flow-improvement strategy
In these environments, automation becomes a band-aid over immaturity.
Metrics might improve on paper, but outcomes don’t improve where it matters - experience, trust, and reliability.
Where automation actually makes a positive difference
When automation works, it works because the fundamentals are already in place.
Here’s where I consistently see real value.
1. Reducing cognitive load
Good automation removes thinking tax, not responsibility.
- Intelligent defaults based on agreed definitions
- Guided forms that help people do the right thing
- Auto-classification that reflects reality, not hope
This frees analysts to focus on solving problems instead of navigating tools.
2. Enforcing consistency without creating rigidity
Automation is excellent at creating guardrails:
- Required steps that shouldn’t be skipped
- Risk and compliance checks applied consistently
- Standard paths with intentional, visible exceptions
The goal isn’t bureaucracy - it’s reliable outcomes.
3. Accelerating repeatable, well-understood work
The best candidates for automation are boring and that’s a good thing:
- High-volume, low-variation requests
- Onboarding and offboarding activities with known outcomes
- Proven remediation steps that don’t require debate
If people are still arguing about what should happen, it’s not ready to be automated.
4. Enabling meaningful shift-left
Automation paired with strong knowledge management can:
- Answer questions before tickets are logged
- Resolve issues at the point of need
- Reduce demand instead of just processing it faster
This is where automation improves experience, not just throughput.
5. Making work visible instead of hiding it
The best automation exposes reality:
- Clear handoffs
- Visible wait states
- Measurable friction points
Visibility is what enables continuous improvement. Hidden work just creates blind spots.
The real question to ask before automating
Instead of asking “What can we automate?”, I encourage your teams to ask:
What decision are we intentionally removing?
What friction do we still need?
What behavior are we reinforcing?
What outcome should be measurably better?
Automation should support people, strengthen process, and clarify value.
If it doesn’t do those things, you’re not transforming ITSM - you’re just making bad work faster.
I’m curious:
Where has automation genuinely improved outcomes in your ITSM practice—not just speed or volume, but clarity, quality, or experience?
That’s the conversation worth having.