ServiceNow Podcasts

This is the takeaway episode with Patrick McGarry, Federal CDO at ServiceNow and author of The Adaptive Organization, who has spent years watching organizations accumulate data and tools but fail to convert them into decisions. Overhead grows. Outcomes don't. Hence “Intelligence Without Action Is Just Overhead.” See omnystudio.com/listener for privacy information.

This is the takeaway episode with Bethany Sehon, Enterprise Data Leader at Capital One where she share lessons learned of building data products and ontologies in production long before they became buzzwords: dedicated data product managers (not side-of-desk), ontologists treated as first-class citizens, a VP-accountable governance process, and much more. See omnystudio.com/listener for privacy information.

This is the start of our 7th year of doing the podcast. Juan and Tim kick off the 12th season sharing who are the upcoming guests and what's the latest on their mind about this crazy data and AI world: The new website (honestnobsdata.com) and discussed building a knowledge graph of the podcast itself  Two types of semantics: for AI context vs. for system interoperability  The vendor hype gap vs. practitioner reality AI agent proliferation and the governance surface area explosion AI cybersecurity: models escaping their sandboxes  The economics of AI: accuracy, latency, and token cost as the new CAP theorem The great convergence, "triangle of consolidation" and “postmodern data stack” OSI and Apache Nessie Work as the center of gravity Bridging the operational and analytics worlds See omnystudio.com/listener for privacy information.

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 #DontAutomateTheChaosSee omnystudio.com/listener for privacy information.