For every ServiceNow release, I like to learn a little about the place it is named after and draw some parallels to what we’ve built. When Australia came up, I felt confident. I’ve got this one.
Except it turns out approximately 100% of my knowledge of Australia comes from watching Crocodile Dundee as a kid.
So, I did what I always do. I went and actually learned something.
The concept that stopped me was the Walkabout, a rite of passage in Australian Aboriginal culture where a young person navigates the wilderness alone, reading the terrain as it actually is, not as someone described it. Mick Dundee didn’t need a map because he’d walked every inch of that Outback himself.
Most organizations are still navigating their operations from a map that was drawn when the workflow was designed. That map almost never matches the terrain.
Process Mining is your walkabout. It shows you what’s actually out there for your workflows and your AI agents. The Australia release takes that walkabout deeper than ever.
Let’s head out and explore the enhancements.
Intent and activity analysis
One of the hardest things to understand about a bottleneck is why it’s happening and what to do to address it. You can see on the process map that a certain transition is slow or that work is piling up at a particular group. But what are people actually doing to resolve those tickets? That answer lives in the work notes, unstructured, scattered across thousands of records, and historically very difficult to surface at scale.
The transition work notes analysis capability introduced Zurich allowed us to easily understand what is happening at certain transitions in the process, but Intent and activity analysis takes it to the next level.
Example of Intent and activity analysis dialogue launched from the Investigate menu in the Analyst Workbench
Intent and activity analysis automatically categorizes work by the type of customer request, VPN issues, credit card disputes, benefits inquiries, whatever your process handles, and then reconstructs a step-by-step view of the activities captured in work notes for each intent across the entire process not just a single transition in the process. This allows us to immediately see which resolution patterns are repeatable and consistent and which are strong candidates for automation, AI agent deployment or standardization.
It’s organized by intent and across the entire process, which is the key. You’re not just seeing what happened. You’re seeing what happened for each type of problem, which accelerates your ability to act on it.
And for organizations trying to identify where AI agents will have the biggest impact, this is exactly the kind of data-driven signal that separates a well-targeted deployment from a guess.
Process Mining for Playbooks
In Zurich we added the ability to generate a Playbook directly from a process map, turning the ideal path you identify in the Analyst Workbench into a guided, step-by-step workflow for your teams. In Australia we close the loop in the other direction. You can now mine Playbook execution data just like any other ServiceNow workflow.
That means you can see how your playbooks actually execute in the real world, not just how they were designed. Where are agents skipping steps? Where are delays accumulating by phase? Which execution paths produce the best outcomes? The same designed-path-vs-reality gap that Process Mining surfaces for Incidents and Cases now applies to your Playbooks too.
Sample output of a Process Mining project using Playbook as its data source
If you’ve invested in building guided workflows to improve consistency, you can now measure whether they’re actually doing that and continuously improve them with real data driving your improvement decisions.
Initiate Task Mining from the Process Mining Workspace
Task Mining, introduced in Zurich to give visibility into workstation-level tasks happening outside the ServiceNow platform, gets a significant usability upgrade in Australia. You can now launch a Task Mining project directly from a process step in the Analyst Workbench.
Example of creating a Task Mining project directly from the Analyst Workbench. You can also create from the Opportunity Details page.
Here’s why that matters. You’ve identified a bottleneck on the process map. You know which step is slow. But you suspect the root cause isn’t in ServiceNow. It’s in what people are doing in other applications on their workstations while they work that ticket. An Email. A spreadsheet. A supplier portal. Now directly from the process map you can create a pre-filled Task Mining project with context automatically carried over, and the status of that project, data approval, collection, mining, analysis, flows back into your Process Mining workspace.
Process bottleneck to workstation-level insight. The full analytical thread stays intact.
Closed-loop AI Agent Creation
This is the one that connects it all.
Process Mining identifies a workflow bottleneck caused by repetitive manual desktop tasks. Task Mining captures exactly how teams are performing those tasks, which applications, in what order, how long each step takes.
Example of the details being passed from Task Mining workspace to the Automation Center request
From the Task Mining workspace the "Generate Details" button invokes the User Task Step Summarization NowAssist skill to summarize those captured tasks into structured, actionable descriptions ready to be passed to Automation Center complete with contextual ROI data so the Automation team can accurately prioritize the opportunity.
Automation Center request ready to be sent to the AI Agent Studio
Then from Automation Center we pass all of the necessary information directly into AI Agent Studio, pre-populating the agent blueprint with the details from your Task Mining analysis.
AI agent populated by with details gathered from Task Mining exercise
The ROI is already quantified from the Process Mining analysis that kicked the whole sequence off. From bottleneck to AI agent blueprint, with the business case built in. That is a genuinely new capability and exactly what closed-loop process intelligence means in practice.
Process Mining for agentic workflows
This one is actually available as of Zurich Patch 5 but is too important not to cover it here.
As organizations deploy more AI agents (opportunities likely discovery via Process and Task Mining), a new and critical question emerges. How do you know if they're actually performing the way you designed them to? Your traditional analytics can tell you how many tasks your AI agents completed and what the outcomes were. But they can't tell you where agents are taking longer than expected, where they're looping back unnecessarily, where agent-to-agent handoffs are slowing things down, or where they're drifting from the intended process path.
That's exactly what Process Mining for Agentic Workflows addresses. Using the same process intelligence that helps you understand how your human-driven workflows execute in the real world; you can now mine agentic workflows directly.
Example of a process map giving us visibility into agentic workflows
Every decision, every tool call, every agent-to-agent handoff creates traceable data that Process Mining turns into a visualized map of how your AI agents actually operated, not how you designed them to.
To go deeper on this capability, including a live demonstration, check out this Process Mining Academy session on Agentic Workflows.
Even more automated Improvement Opportunities
In Australia we've added four new automated Improvement Opportunities that put that data to work automatically.
In the Zurich release we introduced touchpoints as a metric, a way to see where high volumes of manual activity are happening in your process. Now we have two automated Improvement Opportunities tied to them, High Touchpoints (Node) flags process steps where one group of records consistently requires more updates than another to progress, a signal of high-effort work that's ripe for automation or standardization. Extreme Touchpoints (Node) catches steps where the update count is dramatically higher than the median, a more pronounced outlier that warrants immediate attention.
We've also added Slow Duration (Node) and Extreme Duration (Node). If those sound familiar, it's because we've had duration-based pattern detection at the transition level in prior releases. These new opportunities bring that same detection to the node level, surfacing steps where work is sitting significantly longer than it should.
Landing page for creating a new Improvement Opportunity
All four get surfaced and prioritized by size of opportunity on the Summary and Insights page alongside your existing Improvement Opportunities. This brings our total number of automated Improvement Opportunities to 11. That's a lot of opportunity surfaced with very little effort on your part.
Improvement Opportunities get surfaced on both the Insights panel within dashboards and the Summary and Insights page within every Process Mining project
You don't have to go looking for where manual effort or excess duration is concentrated. It gets surfaced for you, with the case for action already built in.
If you are interested in learning more about Improvement Opportunities check out this session.
Transition Filter Enhancements
The Transition Filter in the Analyst Workbench got a meaningful upgrade in Australia. You can now filter on touchpoints, idle time, time-based criteria, and use OR/AND logic, unlocking analysis combinations that weren’t possible before.
Example of the enhanced transition filter dialogue
And here’s the part worth highlighting. You can now save any transition filter set directly as a named Improvement Opportunity, tied to a category and the KPIs it impacts. That opportunity surfaces immediately on the Summary and Insights page and in stakeholder dashboards. A direct path from analyst insight to organizational visibility, with no extra steps required.
Example of the dialogue to create an Improvement Opportunity directly from transition filters
*Note – Since is the same dialogue used to create rule based Improvement Opportunities you could also consider this an Improvement Opportunities enhancement as well.
Transition work notes analysis on the Opportunity Details Page
The Improvement Opportunity Details page introduced in Zurich brought together metrics, trends, and variants for a given opportunity in one place. In Australia, Transition work notes analysis joins that page, so the AI-summarized human context behind an inefficiency pattern is right there alongside all the quantitative data.
Example of launching Transition work notes analysis directly from Opportunity Details page
Why did those 70 records take so long to move between groups? Now you don’t have to navigate anywhere to find out. The patterns from the work notes, the recurring themes, the root cause signals, are on the same page where you’re already making improvement decisions.
Example of Transition work notes analysis output
Understand the why, not just the what, right where it matters.
Learn more about the Opportunities Details page here.
Learn more about Transition work notes analysis here.
Just to throw a few more shrimps on the barbie
If those enhancements weren’t enough to get you excited there are even more.
The embedded process map widget on Platform Analytics dashboards now fully supports Views and Multidimensional Maps, so stakeholders get the complete end-to-end picture without leaving their operational dashboards.
Example of the a multidimensional map surfaced on a Platform Analytics dashboard using the Process Map visualization
Another enhancement for multidimensional maps is you can now apply breakdown filters on child tables within a multidimensional map directly from the Analyst Workbench without needing duplicate project configurations.
Example of filtering on a child table breakdown in a multidimensional map
Personally, I’m excited to use both of those enhancements when digging into Service Catalog inefficiencies.
A new Evaluation Project for Security Incidents is pre-configured and available on every instance out of the box, letting security teams mine up to 3,600 recent incidents in minutes with no setup required.
What you will see if you go to your production instance and open the Process Mining Workspace
If you aren’t familiar with Evaluation Projects, they are pre-configured Process Mining projects available for you TODAY in your production instance that allow you to try process mining with your own data. Go here to learn more.
This is the 11th release of ServiceNow Process Mining. From Quebec to Australia, each release has added depth, broadened reach, and accelerated the path from insight to action.
The Australia release moves both people and AI agents closer to the terrain they're actually operating in and that changes everything.
Going into this I knew two things about Australia. Crocodile Dundee had an impressive knife and that Foster’s was Australian for beer.
After writing this post, I’m confident in two things as well.
A cold Foster’s would go great with a long process mining walkabout through your own process data.
And that Process Mining is Australian for opportunity.
Register for our Process Mining Academy session on 3/19 where we’ll discuss these enhancements in more depth and do live demonstrations. Register here.
Related Process and Task Mining content
Guide to getting started with ServiceNow Process Mining
How to use the Process Mining Evaluation Projects
Process Mining for Agentic Workflows
Process Mining Use Case Series
