Show notes
Most organizations deploying AI agents can’t answer a basic question: is it actually working? Not whether the agent runs — whether the process actually got better.
In Episode 3 of our process mining and process intelligence series, Damian Pascale and Roz Parpia join host Bobby Brill to go deep on what it actually looks like to run process intelligence with AI in the mix — from the AI Visibility Gap, to a four-step framework for finding the right AI use cases, to what “closed loop intelligence” really means once agents are governing agents.
This episode’s answer to the recurring question: don’t automate the chaos. Find it, understand it, improve it — then, and only then, streamline it.
CHAPTERS
0:00 Introduction — Damian Pascale & Roz Parpia
0:56 “Don’t automate the chaos” — where the phrase comes from
2:25 Process mining vs. process intelligence — what actually changed
4:21 The linchpin: where AI fits across all three layers
5:36 The AI Visibility Gap — what most organizations are missing
6:56 A real example: when agent metrics look great, but quality doesn’t
8:13 The four-step framework: Find, Understand, Improve, Streamline
11:27 Where AI comes into streamlining — sizing the right use cases
13:19 Does the order of the four steps actually matter?
14:04 Task Mining — the human side process mining can’t see
15:19 A concrete example: the procurement approval bottleneck
16:31 The closed loop — six steps to continuous improvement
17:30 Why you can never skip the ‘detect’ step
18:05 Measuring real impact with the compare feature
19:25 Governance and AI Control Tower, explained simply
20:46 Mining the agents themselves — a third layer of visibility
21:36 Closed loop intelligence — the three layers, confirmed
22:48 Day one: what to do after deploying your first agent
23:38 Closing thoughts from both guests
24:26 Wrap-up
IN THIS EPISODE
• Why an AI agent doesn’t fix a broken process — it just runs the broken process faster
• The real difference between process mining and process intelligence: three layers in one
• The AI Visibility Gap: why almost every customer has deployed an agent, but few can prove it’s working
• A real customer example — an agent that improved response time but quietly increased the reopen rate
• The four-step framework for AI-ready process improvement: Find, Understand, Improve, Streamline
• The 2–15 minute rule (and the 3–9 minute sweet spot) for sizing the right AI agent use cases
• Why skipping straight to automation is exactly how you end up automating the chaos
• Task Mining and the procurement approval example — 45 minutes across four systems, invisible to process mining alone
• The six steps of the closed loop, and why the ‘detect’ step is the one everyone skips
• Using the compare feature to measure whether an AI agent actually helped — or just moved the problem
• AI Control Tower, explained simply — and how it becomes a third layer of process intelligence
• Closed loop intelligence: the agent, the governance, and the agent’s own behavior — all observable, all improving
GET STARTED
If you’re a ServiceNow customer, you already have access to free evaluation projects — no license needed.
https://www.servicenow.com/au/products/process-mining/get-started.html
https://www.servicenow.com/docs/r/now-intelligence/process-mining/process-mining.html
https://www.youtube.com/watch?v=TVrU0TQ7ldM
https://www.youtube.com/watch?v=GLKROYqnc10
#ServiceNow #ProcessMining #ProcessIntelligence #AIAgents #AgenticAI #TaskMining #AIGovernance #AIControlTower #WorkflowAutomation #DigitalTransformation #ContinuousImprovement #ClosedLoopIntelligence #ServiceNowPodcast #EnterpriseAI #DontAutomateTheChaos
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