--- sourceDocument: Brazil Enable AI sourceDocumentLink: https://www.servicenow.com/docs/r/intelligent-experiences Release : - brazil ft:locale : - en-US ft:publication_title : - Brazil Enable AI ft:clusterId : - platai bundleId : - platai workflow : - Platform --- # Managing AI asset details # Managing AI asset details {#ariaid-title1} Release version: Brazil Updated October 19, 2026 ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 3 minutes to read Confirm what an AI asset is, who owns it, how it operates, and what other assets depend on it before approving a change, investigating a score, or responding to an audit question. An AI asset record stores the metadata, operating characteristics, related assets, and supporting documents that describe how the asset is built, owned, and used. The Details tab consolidates this information so that asset owners can keep the record current and AI stewards can reference it during reviews and audits. The Details tab is available for both managed and unmanaged assets. For an unmanaged asset, it is the only tab on the record where this information appears, and is the starting point for review or onboarding. ## AI asset details {#disc-ai-asset-details__details-section} Use the Details section to confirm and maintain the administrative metadata that identifies an AI asset, shows where it came from, and clarifies who is accountable for it. Asset owners reference these values to keep the record current. AI stewards reference them during reviews and audits. The asset tag contains the unique ID assigned to every asset. Each asset tag consists of a type prefix followed by a 20-digit number. Use the Provider, Vendor, and Source system fields to tell who built an asset, who supplies it, and where it was discovered or imported from. Provider : The organization that built the asset. Assets that ServiceNow builds show Service-now.com. AI agents that your organization builds on your instance show your company name. For assets that a connector discovers on another platform, the connector sets the provider. Vendor : The company that the asset was purchased from. AI agents that run on your instance show ServiceNow as the vendor, including agents that your organization builds. For assets that a connector discovers on another platform, the vendor is that platform's company, such as Google or Databricks. Source system : The platform or instance that the asset came from. For assets that a connector discovers, this is the connector's platform, such as Google Vertex AI or Databricks. For assets that you import from another instance by using multi-instance management, this is the name of that instance. Assets that are created on your instance don't show a source system. For details about multi-instance management, see [Multi-instance](https://www.servicenow.com/docs/OTIuZD7vyKgDv5zYzEXFNw "The Multi-instance Framework enables a prod (manager) instance to manage multiple sub-prod (managed) instances and facilitate communication for AI Control Tower."). For example, an AI agent that your organization builds shows your company as the provider and ServiceNow as the vendor, and has no source system. The Managed by field identifies the asset owner who keeps the record accurate and receives lifecycle tasks. To update any of these values, edit them on the asset record. ## Use and purpose {#disc-ai-asset-details__use-and-purpose-section} Use the Use and purpose section to capture how an AI system operates and what outcome it produces. AI stewards reference these values to classify risk and set appropriate guardrails. Asset owners reference them when responding to audit or regulatory questions about how the asset behaves. When this section is populated when a record is first created, whether for a managed or unmanaged asset, the system uses it to assign the asset an initial risk rating automatically. For example, the System autonomy level field records how independently the asset acts, with values that range from Assistive (AI suggests) at one end to Fully Automated Execution at the other. The Intended outcome of the AI system field records what business outcome the asset produces, with values such as Efficiency Boost, Decision Guidance, and Automation of Tasks. Together, these values give reviewers context to classify the asset and identify the controls that apply to it. Other fields in the section capture how end users interact with the asset, the level of human involvement in its workflow, and free-text descriptions of the data it uses and the people it affects. To update Use and purpose values, see [Update the use and purpose of an AI asset](https://www.servicenow.com/docs/AydRNAYWrP1e9KP22xlIag "Update the use and purpose values for an AI asset when its operating characteristics or business outcome change so that risk classifications and governance controls continue to reflect how the asset behaves."). ## Asset relationship map {#disc-ai-asset-details__asset-relationship-map-section} An AI asset can depend on other AI assets. For example, an AI system can use AI models, prompts, and datasets; can invoke other AI systems; and can be associated with one or more business applications. Use the asset relationship map to see these connections, assess the impact of a planned change, and navigate to a related asset's record. Business application connections require the Enterprise Architecture for AICT plugin, which installs automatically with AI Control Tower Core at the required version. For upgrade-order considerations, see [Enterprise Architecture for AICT plugin installation and upgrade considerations](https://www.servicenow.com/docs/bO_6DuQV~nz6~~86SHvJ4A "Upgrading AI Risk and Compliance, Enterprise Architecture Workspace, and AI Control Tower Core out of sync with each other temporarily affects the AI system-to-business application association."). Figure 1. Related AI assets For step-by-step guidance, see [Trace the relationships between AI assets](https://www.servicenow.com/docs/qPQvCmTnFZ8MNOwSSZJRHA "Identify the AI assets that depend on or feed into a specific AI asset to assess the impact of a planned change, investigate an unexpected evaluation score, or respond to an audit question about how data and models flow through your AI inventory."). ## Attachments {#disc-ai-asset-details__attachments-section} Use the Attachments section to keep supporting documents with the asset record, such as model cards, dataset cards, vendor contracts, and third-party documentation. Attached files open in the embedded document viewer, so reviewers can read them without downloading the file. * **[Update the use and purpose of an AI asset](https://www.servicenow.com/docs/AydRNAYWrP1e9KP22xlIag)** Update the use and purpose values for an AI asset when its operating characteristics or business outcome change so that risk classifications and governance controls continue to reflect how the asset behaves. * **[Use and purpose fields](https://www.servicenow.com/docs/_~GLxMS2SP87ZJAYXq3~gw)** Field and value reference for the Use and purpose section of an AI asset record. AI stewards and AI asset owners reference these values during onboarding, reviews, and audits. * **[Trace the relationships between AI assets](https://www.servicenow.com/docs/qPQvCmTnFZ8MNOwSSZJRHA)** Identify the AI assets that depend on or feed into a specific AI asset to assess the impact of a planned change, investigate an unexpected evaluation score, or respond to an audit question about how data and models flow through your AI inventory. * **[Associate a business application with an AI system](https://www.servicenow.com/docs/_Ex6iwDEjJoJrcARnHRSvQ)** Associate an existing business application with an AI system asset, independently of whether the Enterprise Architecture Workspace plugin is installed.