Brazil Patch 2, Brazil Patch 1, Brazil, Australia Patch 8, Australia Patch 7, Australia Patch 6, Australia Patch 4, Australia Patch 3, Australia Patch 2, Australia Patch 1, Australia, Zurich Patch 11, Zurich Patch 10, Zurich Patch 9, Zurich Patch 8, Zurich Patch 7, Zurich Patch 4, Zurich Patch 1, Yokohama Patch 11, Yokohama Patch 6
Standalone Application
AI Control Tower enables enterprises to actively manage, optimize, govern, secure & measure the value of their AI investments, ensuring performance, compliance, and workforce transformation while seamlessly embedding AI into enterprise strategy. AI Control Tower centralized enterprise AI asset inventory, boosts efficiency in the AI development with automated workflows and embeds risk and compliance management in the AI asset lifecycle.
- AI Control Tower: Single pane view of status of AI in the organization with actionable insights.
- Centralized AI asset inventory: Centralized information about AI systems, AI models, prompts and datasets, and their relationships. Supports automated discovery of Now Assist skills and ServiceNow deployed models.
- AI discovery: Discover and add enterprise AI assets in hyperscalers to the AI inventory
- AI asset lifecycle: Enables management of AI asset lifecycle from intake and to deployment, with review and governance tasks embedded in the appropriate phases of the lifecycle.
- AI risk and compliance management: Embeds risk and impact assessments, application of policies and controls in the AI asset lifecycle to manage and mitigate risk and measure compliance against organizational policies and regulatory needs.
- AI value and adoption: Enables value measurement and track adoption and usage of AI in the enterprise delivering continuous visibility into progress and tangible outcomes
- AI case management: Enables logging and management of AI cases and inquiries to address issues.
- AI security and privacy: Enables monitoring AI agents, their agent maps and usage to flag security vulnerabilities with elevated access and dormant assets.
Inventory and Discovery
New
- Connectors: Trace Collector discovers Tools. Hyperscaler connectors install automatically. Anthropic discovers Agents via Beta APIs and supports MID servers. GCP imports Gemini Enterprise App Agents with clearer errors. Microsoft adds attributes and tag-based discovery. Databricks adds Domain Separation. GitHub discovers organizations, repositories, and Copilot agents, with scheduled imports and Cloud and Enterprise support.
- AI Gateway: Client based access policies in AI Gateway to limit each MCP client to specific tools on an MCP server
Changed
- GCP Beta API usage UX updated.
Fixed
- AI Discovery Agentic Client support and staging domain fallback.
- Anthropic false success on Test Connection; LangGraph duplicates and standalone run usage; several GCP issues.
Govern
New
- AI Policy Framework v1.2: AI agent containment (kill switch) using policy-based automation.
Fixed
- Playbook and lifecycle fixes in AI Risk and Compliance, and AI Risk and Asset Management.
- Rejection comments display; rejected requests set to "Cancelled."
Secure
Changed
- In Settings, the Security tab has been restructured into these sub-tabs: Overview, Runtime, Post-runtime, and Security insights. These sub-tabs correspond to metrics they configure, except Security insights. Security insights shows the status of the AICT Security Analyzer agent.
- In Settings, in the Runtime sub-tab, the link to configure data patterns changed to go to Anonymization policies in Data Privacy.
- In Settings, in the Post-runtime and Security insights sub-tabs, the user is asked to consent to consumption of assists when enabling settings.
- In the Post-runtime tab, when you select Configure, you are now redirected to Settings to update your configuration instead of to a side panel.
- AICT correctness detection is renamed to Correctness detection.
- The Contained agents list is renamed Agent containment list and you can now filter the list by agent.
Fixed
- In Settings, the Data privacy tab shows anonymization disabled for a data pattern. (PRB2104868)
- Post-runtime tab heatmap is missing hover details and has an empty Provider column. (PRB2097211)
- In the Post-runtime tab, correctness detection events show JSON in the Description column instead of readable justification text. (PRB2098772)
- Agent map shows risk and owner data from the wrong instance's agent. (PRB2094174)
- Overview page load time regressed. (PRB2093094)
- Managed-asset filtering disabled when an instance doesn’t have governed assets, causing all assets to be analyzed. (PRB2100466)
Monitor
New
- Direct trace access for usage mismatches.
- Severity-based grouping of score drops.
- Agent activity chart filters by top or bottom five metrics.
- Metric scores and LLM judge reasoning on Session details.
- Input and output toggle in trace details.
Changed
- Arc traces evaluated at asset level for Agentic Client assets; Tools discovery and evaluation added.
- Reduced insight noise; widget customization across AICT pages.
Fixed
- Redundant session scores removed; Privileged Access Detector shows 0% in red.
- Custom date selection and duplicate insights.
Measure
Fixed
- Functional and non-functional IT defects.
- Creator metrics for managed and unmanaged AI systems.
Foundations
Changed
- AINPX UI: AI Gateway access management, runtime security configuration, a Security Insights tab, connector upgrades, and LLM-based deduplication.
Fixed
- EA for AICT domain separation on AI Portfolio widgets.
- AWH: correct Tool Groups count, MCP sync job errors, and catalog population on new instances.
- Otto: manufacturer, vendor, and owned_by details resolve correctly.
Full details: https://www.servicenow.com/docs/r/release-notes/ai-control-tower-rn.html
Not applicable for this application version. For more information, please see
Application Runtime Policy
Requires Brazil Patch 2 or Australia Patch 8