Operationalizing ServiceNow AI Control Tower

Knowing AI is running in your environment is step one. Turning that visibility into a governance program that actually holds up, without burying teams in manual review or losing track of risk as usage scales, is the hard part.

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In this video on operationalizing ServiceNow AI Control Tower you'll learn how to:

• Design intake-to-retirement lifecycle workflows, including approvals, playbooks, and automation rules for AI assets
• Turn discovery and connector data into properly owned, reviewed, and governed records, not just inventory
• Use AICT Gateway and Security & Privacy signals to get ahead of shadow AI and ungoverned MCP servers
• Tie risk classification to control objectives, evidence requirements, and case/issue/remediation routing
• Define KPIs and dashboards that prove adoption and value with data that holds up to scrutiny