If you're a process analyst or process owner working with ServiceNow workflows, you've probably had this experience: you surface a bottleneck or compliance gap in your process mining tool, write up a recommendation, and then...wait. For weeks. Maybe months. For someone else to act on it in an entirely different system.
That's the insight-to-action gap. And it's where a lot of process improvement initiatives go to die.
The problem with mining workflows somewhere else
Many of us work in organizations that have invested in standalone process mining tools. And look—there's real value there. These tools can absolutely help you see what's happening in your processes.
But if your workflows run on ServiceNow, mining them in a separate platform creates some friction that's hard to overcome - you're extracting data to analyze it elsewhere. That takes time, introduces complexity, and by the time you're done, the business has moved on.
The insights live in a separate interface that most of your stakeholders never see. Process mining stays siloed as a periodic exercise instead of becoming part of how people actually work.
Acting on those insights requires handoffs—connectors to push recommendations back into ServiceNow, alignment meetings, manual translation of "here's what we found" into "here's what we're going to do about it."
And here's the one that's becoming urgent: if you're deploying AI Agents on ServiceNow, those agents need to be grounded in real workflow execution data. Without that feedback loop, you're risking drift, hallucinations, and automating the wrong things at scale.
Why native process mining changes the equation
ServiceNow Process Mining runs on the same platform where your workflows and AI Agents execute. That means no data extraction. You're mining directly against the workflow data that's already there. Analysis in minutes instead of weeks.
Insights show up where people work. In Workspaces, in the Now Assist Panel, in List views. Your process owners and front-line managers see what's happening without needing to log into a separate tool or wait for a quarterly report.
Improvement opportunities connect directly to action. Through Automation Center, insights flow into AI Agent Studio, Workflow Studio, App Engine—whatever automation tool fits the job. No connectors. No handoffs. Insights into improvement in hours, not quarters.
We call this closed-loop process intelligence. It's a different model than "mine here, act over there."
Closed-Loop Process Intelligence
For those of you running external tools
If your organization has a centralized or federated process improvement CoE that uses an external tool, you're not alone. And you may have good reasons for that investment.
But if you're also responsible for ServiceNow workflow performance—or if you're the one who has to translate process mining findings into actual platform changes—it's worth understanding what native process mining can do for the workflows that run on ServiceNow.
You might find you have more control, faster cycles, and better access to insights that actually get acted on.
Go deeper
We've put together a short POV document attached below —Closed-Loop Process Intelligence for High-Performance Workflows and AI Agents—that lays out the case in more detail. It covers the limitations of standalone tools, what makes native process mining different, and why this matters even more as AI Agents become part of your workflow strategy.
Read the POV: Closed-Loop Process Intelligence
If you've been thinking about how to get more value from process mining for your ServiceNow workflows—or if you're trying to figure out how process intelligence fits into your AI Agent strategy—this is worth 5 minutes of your time.
Drop a comment if you have questions or want to compare notes on what's worked (or hasn't) in your organization.
