--- sourceDocument: Australia Enable AI sourceDocumentLink: https://www.servicenow.com/docs/r/australia/intelligent-experiences Release : - australia ft:locale : - en-US ft:publication_title : - Australia Enable AI ft:clusterId : - platai bundleId : - platai workflow : - Platform --- # Discover and manage AI assets # Discovering and managing AI assets {#ariaid-title1} Release version: Australia Updated October 28, 2026 ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 2 minutes to read Summarize ![AI sparkle icon](https://servicenow.com/docs/portal-asset/ai-sparkle-icon) Summarized using AI This content was generated using new OpenAI-powered functionality. Results are provided on an as is basis and are not guaranteed to be accurate or complete. ## Summary of Discovering and managing AI assets This capability enables ServiceNow customers to build and maintain a comprehensive inventory of all AI assets across their organization. It addresses the challenge of managing numerous AI systems, models, prompts, datasets, and MCP servers that may exist in various business units, including shadow AI and undocumented integrations. Having a centralized AI asset inventory is essential for effective governance, monitoring, and risk management of AI deployments. Show full answer Show less ## Key Features * **AI Asset Inventory:** Provides a centralized view of all AI assets, allowing customers to manage assets portfolio-wide or focus on individual assets. Users can mark assets as managed or unmanaged, filter by asset type or lifecycle stage, manually add unreachable assets, and respond to recommendations for asset attention. * **AI Asset Records:** Each asset record offers detailed governance information, evaluation scores, lifecycle status, and value contribution. Customers can perform asset-level actions such as initiating lifecycle reviews, submitting change requests, or enabling evaluations. * **AI Gateway:** Governs connections to external AI tools via MCP servers within the ServiceNow environment. It monitors transaction volumes and success rates, enforces approval workflows, and allows AI stewards to manage MCP server records, pause/resume transactions, and administer global MCP clients. This complements Service Graph Connectors by focusing on governance rather than discovery of external AI. * **ServiceNow Arc Agent Records:** Tracks installations of the ServiceNow Arc agent on user devices as instances under a single agent record. The Fleet tab provides details on installation status, last report time, and operational capability. AI stewards can block or unblock Arc on specific devices without affecting others. ## Key Outcomes * Complete visibility into all AI systems and resources across the enterprise, eliminating governance blind spots caused by shadow AI and undocumented assets. * Centralized management and monitoring of AI asset lifecycle and governance posture to support compliance and risk mitigation efforts. * Controlled and governed integration of external AI tools through AI Gateway, ensuring secure and approved interactions within the ServiceNow platform. * Effective tracking and management of ServiceNow Arc agents on user devices to maintain security and operational control. Get a complete picture of every AI system in your organization by building and maintaining a comprehensive AI asset inventory. ## Why discovery matters {#aict-discovering-ai-assets__overview} Before you can govern, monitor, or measure the impact of AI, you need to know what AI assets exist in your organization. Many enterprises operate dozens or hundreds of AI systems across business units, with no single team holding a complete picture. Shadow AI, untracked models, and undocumented integrations create blind spots in governance and risk management. AI Control Tower addresses this by providing multiple discovery pathways that feed into a single AI asset inventory --- a centralized record of every AI system, model, prompt, dataset, and MCP server across your enterprise. See [Discovering AI assets](https://www.servicenow.com/docs/XtCTTEOQwE2~knZgwn9KmA "Populate your AI asset inventory automatically as AI Control Tower discovers AI assets across external platforms, hyperscaler traces, and your ServiceNow instance."). ## AI asset inventory {#aict-discovering-ai-assets__managing-assets} View and manage AI assets across your entire portfolio or focus on a single asset in the AI Control Tower inventory. The Inventory page is designed to give you a complete picture of every AI asset in your organization. From the inventory, you can make assets managed or unmanaged, filter by asset type or lifecycle stage, manually add assets that aren't reachable by automated methods, and respond to recommendations for assets that need attention. See [Managing your AI asset inventory](https://www.servicenow.com/docs/3ZVjUL6I1LvmAqJ6Hjecgg "Track every AI system, model, prompt, and dataset across your enterprise and control which assets participate in governance, monitoring, and risk workflows."). ## AI asset records {#aict-discovering-ai-assets__asset-records} The asset record is where you investigate and act on a single asset. In the asset record, you can review the asset's governance posture, evaluation scores, lifecycle progress, and value contribution. You can initiate asset-level actions such as starting a lifecycle review, submitting a change request, or turning on evaluation. See [Working with AI asset records](https://www.servicenow.com/docs/IMP4iJYdv_OXD3xVLe~CTw "An asset record consolidates the state of a single AI asset and the actions you can take on it, so you can understand the asset's situation and respond from one page."). ## Connecting external AI through AI Gateway {#aict-discovering-ai-assets__connecting-ai-gateway} AI Gateway manages MCP (Model Context Protocol) server connections, providing a governed pathway for external AI tools to interact with your ServiceNow environment. Where Service Graph Connectors focus on discovering what AI exists externally, AI Gateway focuses on governing how external AI tools connect to and operate within your platform. When an MCP server is added through AI Agent Studio, AI Gateway tracks the connection, monitors transaction volumes and success rates, and enforces approval workflows if MCP server approval controls are active. AI stewards can review MCP server records, pause and resume transactions, and manage global MCP clients from the AI Gateway settings page. AI Gateway provides a comprehensive view of all connected MCP servers, showing name, total transactions, and success rate. Total transactions represent all tool calls (MCP method equal to "tools/call"), and the success rate reflects the proportion of those calls returning a successful HTTP status. ## ServiceNow Arc agent records {#aict-discovering-ai-assets__arc-agent-records} ServiceNow Arc appears in the inventory as a single agent record, and each installation on a user's device is tracked as an instance of that record. On the Fleet tab, you can see who has Arc installed, when each installation last reported, and whether it can run. AI stewards can block Arc on specific devices from this tab and unblock it later, without affecting other installations. See [Working with ServiceNow Arc agent records](https://www.servicenow.com/docs/qbfVo8Pdu~yco80T1sschA "Track every installation of ServiceNow Arc across your organization and stop it from running on specific devices, all from one record in the AI Control Tower inventory.").