Extending AI Control Tower with Process Mining How Process Mining diagnoses AICT KPI root cause, surfaces improvement opportunities, and drives lifecycle management and governance workflow velocity © 202 6 ServiceNow, Inc. All rights reserved. . ServiceNow, the ServiceNow logo, and other ServiceNow marks are trademarks and/or registered trademarks of ServiceNow, Inc. in the United States and/or other countries. Other company names, product names, and logos may be trademarks of the respective compa nies with which they are associated. 2 Overview AI Control Tower gives you complete visibility into your AI asset inventory —what's deployed, what's in queue, and where risk classifications stand. But visibility alone doesn't tell you why your mean time to onboarding is 46 days when business expects 14, or why low -risk AI assets sit in the same review queue as high -risk ones. And when it's time to offboard deprecated or underperforming AI assets, you need the same clarity into what's stall ing retirement workflows and creating compliance exposure. Process Mining closes that gap —across both AI asset lifecycle management and AI governance workflows . Built on the same platform where your AI Control Tower workflows execute, it connects the dots between AICT metrics and the actual process behavior driving them. You're not looking at dashboards in isolation —you're diagnosing the root cause behind risk a ssessment cycle times, quantifying where governance effort exceeds (or falls short of) risk levels, and identifying exactly which bottlenecks are slowing on boarding or leaving offboarding tasks incomplete. More importantly, Process Mining moves you from diagnosis to action. Improvement Opportunity detectors surface where your governance and lifecycle processes deviate from design —flagging the manual reviews that shouldn't exist, the workarounds teams create when standard processes don't fit deployment timelines, and the approval or retirement handoffs where work stalls. These aren't generic recommendations; they're prescriptive, evidence -based opportunities tied directly to your AICT workflows. And because ev erything runs on ServiceNow, acting on those opportunities happens in the same environment —no data export, no translation, no lag between insight and improvement. Beyond optimizing existing governance and lifecycle operations, Process Mining also extends AICT's value upstream and downstream. Upstream: mining operational workflows across your ServiceNow environment surfaces high -value AI use cases —feeding your demand pipeline with candidates grounded in actual process pain, not wishful thinking. Downstream: before -and -after process comparisons let you measure the real impact of AI Agent deployment on cycle times, throughput, and process conformance. You're not just go verning AI assets through their lifecycle — you're proving their value with the same rigor you apply to risk management. The following use cases show how Process Mining delivers this value across two critical AI Control Tower workflows: AI Asset Onboarding , where you surface the governance and assessment friction slowing time -to-production; and AI Asset Approval , where you diagnose the bottlenecks and handoff breakdowns that stall decisions. Each demonstrates how Process Mining turns AICT metrics into root cause evidence —and root cause evidence into faster, governed AI deployment. © 202 6 ServiceNow, Inc. All rights reserved. . ServiceNow, the ServiceNow logo, and other ServiceNow marks are trademarks and/or registered trademarks of ServiceNow, Inc. in the United States and/or other countries. Other company names, product names, and logos may be trademarks of the respective compa nies with which they are associated. 3 Use Case: AI Asset Onboarding The Challenge As organizations scale AI adoption, they face a critical challenge: balancing governance rigor with business velocity. Without visibility into the actual onboarding process, risk assessments become inconsistent, governance steps get bypassed, and AI assets either enter production with gaps or get stuck in review cycles that delay business value.