AI Service Graph Connector for GCP Vertex AI

  • Release version: Australia
  • Updated March 12, 2026
  • 2 minutes to read
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    Summary of AI Service Graph Connector for GCP Vertex AI

    The AI Service Graph Connector for GCP Vertex AI enables ServiceNow customers to seamlessly discover and import AI assets from their Google Cloud Platform (GCP) environment into the ServiceNow AI Control Tower. This integration catalogs AI systems, agents, models, tools, and prompts, while automatically collecting usage data to populate the AI Control Tower value dashboard. This provides comprehensive visibility and governance over AI operations within ServiceNow.

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    Supported Versions and Roles

    • The connector is supported on ServiceNow releases: Australia, Zurich, and Yokohama.
    • Required user roles include snaidisc.discoveryadmin and sncmdbintutil.sgcadmin to configure and manage the connector.

    Setup and Prerequisites

    Initial configuration requires several key setup steps:

    • ServiceNow Prerequisites: Enable write permissions on the Data Source table by selecting appropriate access rights (create, update, delete) and clear cached data for the Data Source and Tables using a background script to ensure proper data refresh.
    • GCP Vertex AI Prerequisites: Create a dedicated GCP service account with least-privilege access and assign necessary Vertex AI roles at project or organization level. Enable required APIs in GCP. A JSON key file is needed for authentication; if available, JKS file creation can be skipped.
    • Cloud Trace Service: Must be enabled in GCP to capture detailed AI data such as prompts, tools, models, and sub-agents. Without it, only top-level agent names are discoverable. Agents must be redeployed after enabling Cloud Trace for full discovery.
    • Register the connector within the ServiceNow instance following detailed setup instructions to complete integration.

    Data Mapping and Integration

    The connector organizes discovered AI data into staging and target tables within ServiceNow’s CMDB and related classes to maintain structured asset management. Key data sources and their mapped tables include:

    • Execution Data: Stored in AI usage tables.
    • AI Systems: Mapped to CMDB AI system components, product models, and digital asset tables.
    • Models, Tools, and Prompts: Stored in respective AI model, tool, and prompt product model and digital asset tables.
    • System Subcomponents: Managed via many-to-many relationship tables for AI system subcomponents.

    What This Enables for ServiceNow Customers

    By implementing this connector, customers gain automated and comprehensive discovery of their GCP Vertex AI assets directly within ServiceNow. This enhances AI governance by providing visibility into AI models, agents, and usage, supporting better management, compliance, and optimization of AI resources across their enterprise IT environment.

    The AI Service Graph Connector for GCP Vertex AI enables you to discover and import AI assets from your Google Cloud environment into ServiceNow AI Control Tower.

    The connector integrates with your Google Cloud Platform account to catalog AI systems, agents, models, and prompts. Usage data is automatically collected and populated into the AI Control Tower value dashboard, providing comprehensive visibility and governance of your AI operations.

    Download apps from the Store

    Visit the  ServiceNow store website to download the AI Service Graph Connector for GCP Vertex AI application.

    Supported ServiceNow versions

    This connector is supported on the following ServiceNow releases:

    Release Status
    Australia Supported
    Zurich Supported
    Yokohama Supported

    User Roles

    You must have one of the following roles assigned.

    Required Roles
    sn_ai_disc.discovery_admin
    sn_cmdb_int_util.sgc_admin

    ServiceNow Prerequisites

    Complete the following setup steps once when configuring the connector for the first time.

    Note:
    Updating data source access and clear cache is a prerequisite that needs to be completed only once, when setting up a new instance for the first time.
    Update Data Source Access

    The connector requires write permissions to the Data Source table to create data sources.

    To enable data source creation:
    1. Select Global from the application picker.
    2. Navigate to Application Access.
    3. Select the Can create, Can update, and Can delete check boxes.
    4. Select Update.
    5. Switch to the connector application scope.
    Clear cache

    Clear the cached data for the Data Source and Tables.

    To clear the cache:
    1. Navigate to System Definition > Background Scripts.
    2. Enter the following script in the Run Script text box:
      GlideTableManager.invalidateTable('sys_data_source');
      GlideCacheManager.flushTable('sys_data_source');
      GlideTableManager.invalidateTable('sys_db_object');
      GlideCacheManager.flushTable('sys_db_object');
      
    3. Select Run Script.
      Note:
      The script might take several minutes to complete. After completion, switch to the connector application scope.
    4. After completion, switch to the connector application scope.

    GCP Vertex AI Prerequisites

    Follow the setup instructions to create a service account, assign roles, bind roles to the service account, and enable APIs. To create a JKS file, a JSON file is required. If a JSON file is available, skip the JKS file creation step. After completing setup, register the connector in your ServiceNow instance. For setup instructions and API details, see the Service Graph connector for GCP Vertex AI- Setup Instructions [KB2731256] KB article.

    Note:
    If Cloud trace service is not turned on, you will only be able to view the reasoning engine name, which is the top-level agent.

    Cloud trace service is required to capture details like prompts, tools, models, and sub-agents. These are discovered only after they have been executed at least once.

    If Cloud trace service is not enabled. You must enable cloud trace service and redeploy the agents to properly discover AI agents, tools, models, prompts and sub-agents.

    Service Account and Role Configuration

    Create a dedicated GCP service account with least-privilege access. The connector requires permissions to query Vertex AI agents and observability data.

    The service account requires the following:

    • A service account created in your GCP project with the appropriate Vertex AI roles.
    • Roles bound to the service account at the project or organization level.
    • Required APIs are enabled in your GCP project.

    Data Mapping

    The following table lists the data sources, the staging tables, and the target tables  CMDB CI classes and non-CMDB classes where data is stored for a  GCP Vertex AI  project.

    Table 1. Data sources, staging tables, and target tables
    Data source Staging table Target tables
    SG-GCPVertexAI-Execution sn_ai_disc_gcp_sgc_sg_gcp_execution sn_ai_disc_ai_usage
    SG-GCPVertexAI-System sn_ai_disc_gcp_sgc_sg_gcp_ai_system cmdb_ai_system_component_product_model

    alm_ai_system_digital_asset

    cmdb_ci_function_ai

    cmdb_rel_asset_ci

    SG-GCPVertexAI-Model sn_ai_disc_gcp_sgc_sg_gcp_ai_model cmdb_ai_model_product_model

    alm_ai_model_digital_asset

    SG-GCPVertexAI-Tool sn_ai_disc_gcp_sgc_sg_gcp_ai_tool sn_ent_ai_tool
    SG-GCPVertexAI-Prompt sn_ai_disc_gcp_sgc_sg_gcp_ai_prompt cmdb_ai_prompt_product_model

    alm_ai_prompt_digital_asset

    SG-GCPVertexAI-System Subcomponent M2M sn_ai_disc_gcp_sgc_sg_gcp_ai_system_subcomponent_m2m sn_ent_ai_system_subcomponent_m2m