AI Control Tower release notes
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Summary of AI Control Tower Release Notes - Zurich Release
The ServiceNow AI Control Tower application offers a centralized workspace to manage and govern AI assets and workflows across an enterprise. The Zurich release introduces significant enhancements that improve AI governance, security, compliance, lifecycle management, and user experience. It supports integration with major cloud providers and features advanced analytics and automation to proactively manage AI risks and performance.
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Key Features
- Redesigned AI Control Tower Experience: A new interface enables natural language task completion, AI-generated recommendations, and focused governance work management through an Activity Center workspace.
- AI Quality and Safety Monitoring: Automated scoring and trend analysis detect quality and safety regressions in AI systems before they escalate.
- ServiceNow Otto Premium Chat Integration: Enhanced conversational AI with unified search, integrated web search, and file upload capabilities within AI Control Tower.
- AI Agent Management: Features include kill switch protocols to contain rogue AI agents, agent publishing to external registries (including Microsoft integration), and session token revocation via Okta.
- AI Asset Deduplication: Identifies duplicate AI assets to streamline governance and reduce redundancy.
- AI Service Graph Connectors: Integrations with hyperscalers and AI platforms such as Microsoft Azure, AWS, Google Cloud Vertex AI, Anthropic, and others facilitate discovery, tracking, and data usage monitoring of AI assets.
- Lifecycle and Compliance Management: Manage AI asset lifecycles including onboarding, change requests, and offboarding. Review risk classification, compliance posture, and regulatory adherence using enhanced risk heat maps and control attestations.
- Security and Privacy Enhancements: Monitor AI security metrics, detect potential policy violations, sensitive data exposure, and access issues, with default activation of system prompt leakage and threat monitoring metrics.
- AI Strategy and Value Tracking: Plan and track AI investments, goals, project costs, and productivity gains through integration with Strategic Planning and Goal Framework applications.
- User Interface Updates: Adoption of the Coral theme with dark mode, improved asset association workflows, editable asset details, and consolidated dashboards for value and adoption metrics.
Practical Benefits for ServiceNow Customers
- Centralized Governance: Enables enterprise-wide visibility and control over AI assets, simplifying compliance with internal policies and external regulations.
- Risk Mitigation: Proactively identifies and addresses security, privacy, and operational risks related to AI deployments, reducing potential negative impacts.
- Operational Efficiency: Streamlines management tasks with AI-driven insights, automation of lifecycle processes, and unified case management for AI-related issues.
- Integration and Extensibility: Supports discovery and governance of AI assets across multiple cloud platforms and AI frameworks, facilitating consistent enterprise-wide AI management.
- Enhanced User Experience: Improved interface and conversational AI capabilities support faster, more intuitive AI governance workflows for AI stewards and asset owners.
- Strategic Alignment: Links AI governance to business goals and investment tracking, helping organizations maximize AI value and ensure accountability.
Upgrade and Activation Notes
The new AI Control Tower experience is available alongside the legacy workspace in this release, with guidance provided for upgrading. The application can be installed via the ServiceNow Store. Customers should verify entitlements to access specific features and review the migration knowledge base article for upgrading to the redesigned experience.
Related Applications
- AI Risk and Compliance: Supports verification of regulatory compliance and risk management for AI systems.
- Strategic Planning: Facilitates AI strategy execution and investment prioritization with AI strategy tab integration.
- Goal Framework: Enables tracking and evaluation of AI-related organizational goals.
The ServiceNow® AI Control Tower application provides a centralized workspace to track and act on AI governance work across the enterprise. AI Control Tower was enhanced and updated in the Zurich release.
AI Control Tower highlights for the Zurich release
AI Control Tower highlights in Zurich Patch 11:
- Manage your AI governance work in a redesigned AI Control Tower experience that lets you find information and complete tasks using natural language.
- Resolve important issues using auto-generated recommendations and AI insights that direct your attention to the AI governance work that matters most.
- Detect quality and safety regressions in AI systems before they escalate, using automated scoring and trend analysis for AI interactions in production.
- Use ServiceNow Otto premium chat in AI Control Tower for a better conversational experience with unified search and chat capabilities, including integrated web search and file uploads.
- Contain rogue AI agents by using kill switch protocol to limit damage, preserve your security posture, and provide business continuity for your users.
- Make a managed AI agent discoverable to external systems by publishing it to the External Registry. The Microsoft integration provides two methods to publish an agent so that Microsoft can discover it.
- Publish agents from the AI asset record page.
- Publish agents while onboarding an asset.
- Detect AI assets in your inventory that perform the same function using deduplication. Deduplication enables AI stewards to review and consolidate redundant entries instead of governing them independently.
- ServiceNow Otto is the new AI experience brand. This change is reflected in AI Control Tower. Your product entitlements remain unchanged. Check your entitlements to determine your access to specific features.
- The AI Control Tower home page includes a Guided Setup widget that walks you through the initial configuration of AI Control Tower.
- AI Service Graph Connectors integrate with AI Control Tower to create AI connections for discovering AI assets and tracking data usage. For information about connectors, prerequisites, and the configuration process, see AI Control Tower- AI Discovery Connectors [KB2986990] article in the Now Support Knowledge Base.
- AI Service Graph Connectors and versions available for August 2026 release:
- AI Service Graph Connector for Microsoft (version 3.1.6)
- AI Service Graph Connector for GCP Vertex AI (version 1.2.3)
- AI Service Graph Connector for Anthropic (version 2.0.6)
AI Control Tower (legacy) highlights in Zurich Patch 8: Configure and create automation rules to set AI assets as managed assets.
AI Control Tower (legacy) highlights in Zurich Patch 7:
- Use new security metrics to monitor your LLM and AI agent output for potential security and content policy violations, potential PII, and other potential threats.
- Gain visibility into MCP client-server interactions routed through this instance’s AI Gateway.
- AI assets—Including AI models, AI systems, prompts, datasets, and MCP servers can be categorized as either managed or unmanaged. Managed assets benefit from AI Control Tower features such as governance, lifecycle management, value assessment, risk classification, security, and privacy. Unmanaged assets, on the other hand, don’t have access to these AI Control Tower capabilities.
- AI connections are introduced in AI Control Tower using Service Graph Connectors. AI connections are a combination of hyperscalars, AI apps, and agentic AI frameworks. The AI Service Graph Connectors available from March 2026:
- AWS
- Microsoft- Azure Foundry and Copilot
- Google Cloud Platform (GCP) Vertex AI
- n8n
- LangGraph
- Salesforce
- Manage the end-to-end life cycles of your agentic AI systems.
- Define the intended use and purpose of an AI system so that you can determine its benefits and risks.
- AI Gateway offers MCP Global Clients, which can be used across all servers.
- AI Gateway offers MCP Catalog to choose while adding MCP servers.
- MCP server can be added to an AI Asset inventory from AI Control Tower.
AI Control Tower (legacy) highlights in Zurich Patch 5: Review changes to Now Assist usage measurement.
AI Control Tower (legacy) highlights in Zurich Patch 4:
- Identify ServiceNow® AI assets that impact your security posture using the ServiceNow® AI security score and AI insights.
- Access and monitor security for AWS Bedrock agents running as privileged users, autonomous vs. Supervised tools, and dormant agents.
- Monitor sensitive data detection, prompt injection, and offensive content metrics to help identify and mitigate AI-driven security and compliance risks before they impact workflows or expose sensitive information.
- See more details in the access map about agent access issues to help you troubleshoot quickly.
- Audit logs capture configuration changes made on Data, Approvals, and AI model providers categories.
- Discover AI assets built and deployed in Google Cloud Platform (GCP) Vertex AI, Copilot Studio, and Azure AI Foundry.
- AI Gateway enables enterprises to actively manage, govern, and observe their MCP traffic, ensuring secure operation of agentic workflows across enterprise boundaries.
AI Control Tower (legacy) highlights in Zurich Patch 1:
- Monitor the performance of guardrails enabled through AI Guardian using the Health tab.
- Measure and improve the quality of interactions with virtual agents using the Evaluation tab.
- Display data based on the chosen allowed model providers and the status of the fallback in the Impact Summary table on the AI model providers section.
- Synchronize AI agents automatically when an AI asset is synchronized.
AI Control Tower (legacy) highlights in Zurich:
- Enhance the Product Owner experience with a personalized home page, value management tools to manage AI investments, and enhanced visibility into AI assets to simplify task management.
- Evaluate AI productivity and adoption across the enterprise using defined value metrics and performance indicators to drive data-informed decisions and maximize AI impact.
- Access and security monitoring for ServiceNow® AI agents, especially around access issues, agents running as privileged users and dormant agents.
- Discover AI assets built and deployed in AWS Bedrock and Azure Foundry.
- Enable choice for third-party model providers powering ServiceNow® skills and agents.
- Access to aggregated risk scores to improve decision-making, manage risks, and help to promote ethical and transparent AI practices.
- Monitor performance, track progress, and make informed decisions related to your AI strategies, goals, targets, and the associated work from the AI strategy tab.
- Track costs of your AI projects, epics, demands, and track key project risks, issues, decisions, actions, and changes from the AI strategy tab.
For more information on the new AI Control Tower experience, see .
For more information on the legacy AI Control Tower experience, see AI Control Tower.
Important:
AI Control Tower is available in the ServiceNow Store. For details, see the "Activation information" section of these release notes.
Important information for upgrading AI Control Tower to Zurich
For details on upgrading to the redesigned AI Control Tower experience, see the AI Control Tower Migration [KB3144679] article in Now Support.
New in the Zurich release
- New in AI Control Tower in Zurich Patch 11:
- Activity Center
- Track and act on the governance work generated across AI Control Tower from a single workspace, including lifecycle tasks, security tasks, change and offboarding requests, and AI recommendations.
- Recommendations and AI insights
- Recommendations and AI insights direct your attention to the AI governance work that matters most, so you can resolve high-impact issues without searching for them. Act on recommendations from the Home page, an asset record, or Activity Center.
- Monitor quality and safety for AI systems
- Evaluate the quality and safety of AI interactions across your portfolio using automated scoring, configurable metrics, and trend analysis for both ServiceNow and external AI systems.
- Trace connections
- Collect trace data for discovery, security, and monitoring from hyperscalers including AWS, Azure, and Google Cloud by configuring trace connections.
- Plan AI strategy, prioritize, and execute
- Track your AI portfolio from strategy to delivery with the Plan menu. Plan connects goal alignment, intake management, and execution tracking in a single workspace, giving portfolio managers and AI COE leads a current view of AI investments.
- Use ServiceNow Otto premium chat in AI Control Tower for a better conversational experience with unified search and chat capabilities, including integrated web search and file uploads.
- Deactivate and reinstate AI agents running in AWS Bedrock, AWS Bedrock AgentCore, GCP Vertex AI (limited support), and ServiceNow agents. Revoke AI agent session tokens through Okta.
- See AI models, MCP servers, and providers in the agent map for complete resource visibility across your enterprise, along with agents, agentic workflows, and other AI assets.
- System prompt leakage, threat monitoring, and sensitive data disclosure post-runtime metrics are now configured and active by default.
- Specify the asset state during AI asset creation
- Specify the asset state when you create AI assets manually. By specifying the state during initial asset creation, you can track and manage your assets more accurately throughout their life cycles. You can specify the asset
state in the Asset state field of the following forms:
- Add AI system asset
- Add AI model asset
- Add prompt asset
- Add dataset asset
- Review AI risk and compliance posture
- See regulatory risk classification, compliance posture, and aggregated risk posture for AI assets across your portfolio from the Govern tab. Review related cases, issues, and governance actions associated with those assets.
- Track regulatory risk classification and compliance score
- See how AI systems, models, and datasets are categorized by regulatory risk, and track compliance scores against the priority frameworks configured in your environment.
- Review inherent and residual risk posture
- Compare inherent risk, residual risk, and control effectiveness for AI systems using the risk heat map, and identify concentrations of higher-risk assets across your portfolio.
- View governance records for AI assets
- Review assessments, risks, controls, attestations, issues, and policy exceptions for an AI asset directly from its Risk & Compliance tab, without leaving the asset record.
- AI Service Graph Connector for Anthropic connector
- Discover and import Anthropic AI Models and track usage data (per-user AI asset cost).
- AI Service Graph Connector for Amazon
-
- Admins can now configure all AWS AI discovery services using a single credential page.
- Admins can enable automatic rotation of AWS access keys for AI SGC connections.
- Admins can discover multiple explicit AWS accounts by specifying a comma-separated list of account IDs.
- AI Service Graph Connector for Microsoft
-
- Unified single-page connection for Azure ML and AI services.
- Resource group discovery and storage for Azure Foundry assets.
- Certificate-based authentication for Azure and Copilot.
- Knowledge Base integration in configuration review.
- New in AI Control Tower (legacy) in Zurich Patch 7:
- Security & privacy tab in AI Control Tower
-
- Measure whether your model's output or behavior potentially violates predefined LLM guardrail policies using the Data integrity incident detection chart.
- Review potential threats in AI agent output in Agent goal deviation, Output with PII detected, and Agentic output injection detection charts.
- Monitor MCP server access by AI Gateway with these new charts: Clients connecting to MCP servers, authorized access attempts, and failed access attempts.
- Data section on Configurations page
- Set up data integrity incident detection, agent goal deviation, and output screening metrics to measure the integrity of your data model and potential threats in LLM output.
- Manage agentic AI system life cycles
- Create AI system assets to track and manage the complete life cycles of your agentic AI systems, from onboarding to deployment. Gain comprehensive insight into each agentic AI system and take any necessary actions to successfully complete each life-cycle stage. By managing the life cycles of your agentic AI systems, you can extend their lifespans, reduce downtime, and optimize licensing costs.
- Define the use and purpose of an AI system
- Specify the intended use and purpose of an AI system. Provide insight into who is using the AI system, what the AI system is being used for, and how the AI system works and provides value. This information can help you determine the benefits and risks that are associated with the AI system. For more information on classifying AI systems based on regulatory risk at intake by applying a configured Risk Assessment Methodology (RAM), see Assessment templates and risk assessment methodologies and Request an AI use case.
- Associate additional related AI asset types with AI systems
- Associate the following additional related AI asset types with your AI systems:
- If an AI system has an Asset type of Generative AI or Agentic AI, you can associate it with any of its supported components or subsystems.
- If an AI system has an Asset type of Agentic AI, you can associate it with any of its integrated AI tools.
- Create change and offboarding requests for additional AI asset types
-
Create change requests for the following additional AI asset types:
- AI systems with an Asset type of Agentic AI
- Datasets
In addition, create offboarding requests for the following additional AI asset types:- AI systems with an Asset type of Agentic AI
- AI models
- Datasets
- MCP servers
- New in AI Control Tower (legacy) in Zurich Patch 4:
- Security & privacy tab in AI Control Tower
-
- Identify ServiceNow® AI assets that impact your security posture using the ServiceNow® AI security score and AI insights. AI insights highlight key metric changes, recommend next steps, enabling you to quickly understand the impacts and take action.
- Access and monitor security for AWS Bedrock agents running as privileged users, autonomous vs. supervised tools, and dormant agents.
- Monitor sensitive data detection, prompt injection, and offensive content metrics to help identify and mitigate AI-driven security and compliance risks before they impact workflows or expose sensitive information. AI security tasks are created automatically from Dormant AI systems metrics to streamline your workflow and quickly resolve issues. You can also create AI security tasks directly from more areas, such as access issues and privileged AI agents metrics.
- Review Autonomous vs. supervised systems metrics based on AI tools. Previously, the metrics were based on workflows.
- Show Access issues metrics for only those agents with issues. Previously, agents with issues and no issues were shown.
- See more details about agent access issues in the access map to help you troubleshoot quickly. For example, you can see the user ID of the user who executed the agent and the workflow and tool associated with the access issue, if applicable.
- AI Gateway tab in AI Control Tower
-
View metrics at the MCP server level, including all connected MCP servers along with the total number of transactions for each server and its success rate.
- Data section on Configurations page
- See a read-only view of your data privacy configuration for sensitive data patterns in the Data privacy page. Use this page as a quick reference when troubleshooting sensitive data charts.
- AI Task section on AI assets page
- Review all AI security tasks for your instance in the All Security Tasks page. You can also create an AI task on this page.
- Enhance control of AI asset life cycle through change and offboarding requests
- Manage deployment of AI assets using the change request workflow to update AI assets that have undergone review and onboarding. Facilitate the retirement of AI assets by submitting an offboarding request, ensuring a structured and controlled process for removing assets that aren't needed or have been superseded.
- New in AI Control Tower (legacy) in Zurich Patch 1:
- Health tab in AI Control Tower
- Monitor and evaluate the effectiveness of offensive content and prompt injection guardrails active on your AI assets.
- New in AI Control Tower (legacy) in Zurich Early Availability:
- AI strategy with Strategic Planning(Requires SPM)
-
- Monitor and track your AI strategies and associated goals and targets.
- Track the costs of your AI projects, epics, and demands.
- Monitor key project risks, issues, decisions, actions, and changes.
- AI strategy with Goal Framework (Requires SPM)
- Monitor and track your AI strategies and associated goals and targets.
- AI connections
-
- Discover and add AI agents and related models and tools to the AI inventory through integration with AWS Bedrock.
- Discover and add AI agents and related models and tools to the AI inventory through integration with Azure AI Foundry.
- Configure AI discovery setup and visibility of connections.
- Value tab in AI Control Tower
-
- Gain insights into the value realized from AI skills and features. The Value insights dashboard page gives you insights into the estimated productivity gains as a result of using AI systems.
- Define and measure value relevant to your AI systems using customizable value templates.
- Perform calculations and approximations for the read and write time saved by users using AI systems by using data points and timestamps from the invoking records.
- Understand the key usage and performance indicators that help you evaluate the adoption of Now Assist in your organization.
- Provide insights on success rate visualization by department, country, and AI assets along with the indicators for task closure efficiency.
- Value templates
-
- Create, manage, and use templates from a Global Template Repository to apply consistent settings across AI assets and track usage more effectively.
- Enable users to edit, view, and create customized value templates by enabling a value template assignment experience in inventory records.
- Provide transparency to value calculations of each AI system through value templates.
- Perform calculations and approximations for the read and write time saved by users using AI systems by using data point and timestamps from the invoking records.
- Risk and compliance tab
- Display the risk classification of AI assets and the compliance posture for selected authority documents and policies through the Risk and compliance tab. This tab provides visibility into AI systems, models, and datasets. The Risk overview section uses visual charts to categorize AI assets.
- AI cases tab in AI Control Tower
- Gain a centralized overview of all your AI asset cases and inquiries by using the AI cases. On the AI cases tab, you see a list of records that include the case details such as the status, priority,
owner, and timeline of your AI cases. You can monitor the progression of a case, stay informed about ongoing investigations, follow up on pending actions, and help to ensure timely resolutions. On this tab, you can also find
filtering and sorting options that help you to prioritize cases that require immediate attention.
- Use the enhanced home page to access a single, unified view of all AI-related cases and inquiries.
- Track, manage, and respond to AI-related cases more efficiently through centralized case visibility.
- Security & privacy tab in AI Control Tower
- Review your AI security health metrics in the Security and Privacy tab. Use the access map for a comprehensive overview of agentic workflows, tools, and agent details. The map helps to show how AI agents interface with workflows and tools to accomplish a task. Additionally, you can analyze current AI access, investigate ongoing access issues, and review your AI usage metrics.
- Specify additional details during AI asset creation
- Use the following fields to specify additional details about your AI systems, AI models, prompts, and datasets when you create AI assets:
- AI systems:
- Managed by
- License details
- Supported locations
- AI models:
- Managed by
- License details
- Supported locations
- Prompts: Managed by
- Datasets:
- Managed by
- Creation type
- Department
- Dataset creation date
- AI systems:
UI changes
- AI Control Tower (legacy) UI changes in Zurich Patch 7:
- Coral theme
- Coral is now the default theme for new portal, web, and mobile experiences with Next Experience or Core UI enabled. This theme provides a fresh look and feel, featuring brand-neutral illustrations to enhance your user experience. A dark theme option is available for web and mobile experiences.
- Drop-down menu for associating AI assets with related assets
- The Add new button in AI asset creation forms and records is now the Add from inventory drop-down menu. Select Add from inventory to associate an AI asset with a related asset that already exists in your inventory. Select Create to associate it with a related asset that doesn't exist in your inventory yet.
- Editable asset details fields on the Details tab of AI asset records
- You can now modify asset details fields directly on the Details tab of your AI asset records.
- Related asset lists in AI asset records
- The lists of related assets in each AI asset record has moved from the Related assets tab to the Details tab.
- AI Control Tower (legacy) UI changes in Zurich Patch 4:
- Product Owner portal
-
- Widgets from both the Value and Adoption tabs are now combined and accessible within the updated Value tab.
- The Create AI Asset button is added on the AI Control Tower home page.
- A new Quick link option is added to the employee center to help navigate AI asset owners and AI stewards to the AI Control Tower workspace home page.
Changed in this release
- AI Control Tower changed in Zurich Patch 11:
- New AI Control Tower experience
- The new AI Control Tower provides a more efficient, streamlined way for you to work. For information about how to upgrade, see the AI Control Tower Migration [KB3144679] article in Now Support. Note that the legacy AI Control Tower workspace is still supported in this release.
- Now Assist > ServiceNow Otto® announcement
- Now Assist introduced AI on the platform. As that experience has evolved, there's a new name for the experience. ServiceNow Otto® is the conversational AI platform integrated into ServiceNow workflows. It provides agentic capabilities, supports multimodal interactions across web, mobile, and messaging channels, and enables autonomous orchestration for cross-system workflows.
- The access map is renamed to agent map and shows Veza access intelligence and node details for AI assets, giving you a holistic view of your enterprise.
- You can now adjust the sampling rate for more Post-runtime metrics.
- Improved accuracy of AI threat metrics and evaluation datasets that use Traceloop for continuous monitoring in Overview and Runtime metrics. Access issues metrics now support external agents. Azure, Google Cloud Platform (GCP), and Google Vertex AI assets are now supported.
- The Security tab of the AI asset record shows the AI asset security score and metrics for an individual asset.
- AI Service Graph Connector for GCP Vertex AI
- The Service Graph Connector for GCP Vertex AI now displays as "AI Connector for Google" to align with the AI Connector naming convention.
- Activity Center tasks for the asset owner
- Users with the AI Asset Owner [sn_ai_asset_mgmt.ai_asset_owner] role can access and act on risk and compliance lifecycle tasks, such as impact assessments and control attestations, from the Activity Center. The Activity Center surfaces AI asset tasks, issues, policy exceptions, and AI cases for the asset owner. On the asset record page, all lifecycle tasks specific to the assigned assets can be accessed and performed.
- AI Control Tower (legacy) changed in Zurich Patch 7:
- Security & privacy tab in AI Control Tower
-
- The Autonomous vs. supervised AI tools chart has been removed.
- The Prompt injection, Offensive content, and Sensitive data tabs have been removed and replaced by Access and Guardrails tabs. Metrics have been reorganized into those two tabs.
- In Configurations, under Data, the Data privacy tab was renamed to Security & privacy. In that tab, the data leak detection and anonymization section was renamed to sensitive data input and anonymization.
- AI Control Tower (legacy) changed in Zurich Patch 5:
- Changes to Now Assist usage measurement
- Starting with Australia Early Access, AI usage measurement is transitioning from a 365-day look-back model to a 365-day burn-down model, with usage resetting at the contract anniversary date. For more information, refer to KB KB2704710: AI Usage - Overview & New Measurement Logic.
- AI Control Tower (legacy) changed in Zurich patch 4
- Miscellaneous changes
-
- The AI asset inventory plugin structure has been updated.
- The AI asset owner [sn_ai_asset_mgmt.ai_asset_owner] role enables the Product Owner view experience with a personalized home page and enhanced visibility into AI assets to simplify task management.
- AI discovery: The Innovation lab store application (AWS AI discovery plugin) is decommissioned. Uninstall the AWS AI discovery plugin prior to installing the AI discovery plugin (sn_ai_disc).
- AI cases management has moved under the AI cases tab on the AI Control Tower home page.
Deprecated features
The AI Gateway application is deprecated in the Australia release and is no longer supported.
Activation information
Install AI Control Tower by requesting it from the ServiceNow Store. Visit the ServiceNow Store website to view all the available apps and for information about submitting requests to the store. For cumulative release notes information for all released apps, see the ServiceNow Store version history release notes.
Accessibility information
- Dark theme
- The new Coral theme includes a dark theme option for web and mobile experiences. This option is commonly used to alleviate eye strain and improve readability.