---
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


---

# GCP Vertex AI

# AI Service Graph Connector for GCP Vertex AI {#ariaid-title1}

Release version: Australia  
Updated March 12, 2026  
![](https://www.servicenow.com/docs/portal-asset/ico-clock) 2 minutes to read
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![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 AI Service Graph Connector for GCP Vertex AI

The AI Service Graph Connector for GCP Vertex AI enables ServiceNow customers to discover, import, and manage AI assets from their Google Cloud Platform (GCP) environment within ServiceNow AI Control Tower.
It catalogs AI components such as systems, agents, models, and prompts, while automatically collecting usage data to provide visibility and governance through the AI Control Tower value dashboard.
Show full answer Show less  

## Supported Versions and Roles

* The connector supports ServiceNow releases: Australia, Zurich, and Yokohama.
* Users must have either the **snaidisc.discoveryadmin** or **sncmdbintutil.sgcadmin** roles to configure and use the connector.

## Setup and Prerequisites

To configure the connector, complete these key steps:

* **ServiceNow Prerequisites:** Update data source access permissions to allow creation, updating, and deletion of data sources. Clear the cached data for the Data Source and Tables by running a provided background script. This step is only required once per instance setup.
* **GCP Vertex AI Prerequisites:** Create a dedicated least-privilege GCP service account with appropriate Vertex AI roles bound at the project or organization level. Enable required APIs and Cloud Trace service for full discovery of AI components (including prompts, tools, models, and sub-agents).
* Register the connector in your ServiceNow instance following the official setup instructions.

**Note:** Without enabling Cloud Trace service in GCP, only the top-level agent name will be visible; detailed discovery requires Cloud Trace and agent redeployment.

## Data Mapping and Integration

The connector imports data from GCP Vertex AI into ServiceNow using specific data sources, staging tables, and target Configuration Management Database (CMDB) and non-CMDB classes. This structured mapping ensures AI assets and usage data are properly cataloged and linked for governance and operational insight. Key data categories mapped include:

* Execution data stored in AI usage tables.
* AI systems and components stored in CMDB AI system and related product model classes.
* Models and tools mapped to AI model and tool classes.
* Prompts mapped to AI prompt product models.
* System subcomponents handled with many-to-many relationship tables.

## Benefits for ServiceNow Customers

* Seamlessly integrate GCP Vertex AI assets into ServiceNow AI Control Tower for consolidated AI governance.
* Gain comprehensive visibility into AI operations with automated usage data collection.
* Ensure compliance and control over AI components through structured cataloging and CMDB integration.
* Enable proactive management of AI models, tools, and prompts aligned with enterprise governance policies.  
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 {#gcp-vertex-ai__section_hnt_wk5_k3c}

Visit the  ServiceNow store website to download the [AI Service Graph Connector for GCP Vertex AI](https://store.servicenow.com/store/app/5b3cfb8a87e7fa14a6c6fc48cebb3512) application.

## Supported ServiceNow versions {#gcp-vertex-ai__section_czc_fhj_m3c}

This connector is supported on the following ServiceNow releases:
{#gcp-vertex-ai__table_iqv_hss_mjc__entry__2}

| Release | Status |
|-|-|
| Australia | Supported |
| Zurich | Supported |
| Yokohama | Supported |
[ ]

{#gcp-vertex-ai__table_iqv_hss_mjc}

## User Roles {#gcp-vertex-ai__section_c33_hhj_m3c}

You must have one of the following roles assigned.
{#gcp-vertex-ai__section_c33_hhj_m3c__entry__1}

| Required Roles |
|-|
| sn_ai_disc.discovery_admin |
| sn_cmdb_int_util.sgc_admin |
[ ]

## ServiceNow Prerequisites {#gcp-vertex-ai__section_lck_s4k_cjc}

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.
{#gcp-vertex-ai__ol_hsm_ycf_wjc}

Clear the cached data for the Data Source and Tables.  
To clear the cache:

1. Navigate to System DefinitionBackground 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.
{#gcp-vertex-ai__ol_kcn_1df_wjc}

## GCP Vertex AI Prerequisites {#gcp-vertex-ai__section_ew1_zjj_m3c}

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 \[KB2731256\]](https://support.servicenow.com/kb_view.do?sysparm_article=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 {#gcp-vertex-ai__section_wny_ydl_tjc}

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.
{#gcp-vertex-ai__ul_amp_z2l_tjc}

## Data Mapping {#gcp-vertex-ai__section_xlf_vnk_m3c}

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.
{#gcp-vertex-ai__table_pps_vnk_m3c__entry__3}

| 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 |
[Table 1. Data sources, staging tables, and target tables]

{#gcp-vertex-ai__table_pps_vnk_m3c}

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