---
sourceDocument: Yokohama Enable AI
sourceDocumentLink: https://servicenow-prod.fluidtopics.net/r/yokohama/intelligent-experiences

 Release :

    - yokohama

ft:locale :

    - en-US

ft:publication_title :

    - Yokohama Enable AI

ft:clusterId :

    - platai

bundleId :

    - platai

workflow :

    - Platform


---

# GCP Vertex AI

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

Release version: Yokohama  
Updated March 12, 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 AI Service Graph Connector for GCP Vertex AI

The AI Service Graph Connector for GCP Vertex AI enables ServiceNow customers to 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, and prompts from GCP, and automatically collects usage data to populate the AI Control Tower value dashboard.
This provides comprehensive visibility and governance over AI operations directly within ServiceNow.
Show full answer Show less  

## Supported Versions and Roles

* The connector supports ServiceNow releases: Australia, Zurich, and Yokohama.
* Required roles for using the connector include **snaidisc.discoveryadmin** and **sncmdbintutil.sgcadmin**.

## Setup and Prerequisites

Initial configuration requires several key steps:

* **Update Data Source Access:** Grant write permissions on the Data Source table to enable data source creation within ServiceNow.
* **Clear Cache:** Run a background script to clear cached data for the Data Source and Tables to ensure proper connector operation.
* **GCP Vertex AI Setup:** Create and configure a GCP service account with appropriate roles, enable necessary APIs, and prepare either a JSON or JKS file for authentication.
* **Register the Connector:** Complete registration of the connector within your ServiceNow instance following detailed setup instructions.

**Note:** Enabling the Cloud Trace service in GCP is essential to capture detailed AI asset information such as prompts, tools, models, and sub-agents. Without Cloud Trace, only top-level agent names are visible. If not enabled initially, enable Cloud Trace and redeploy agents for full discovery.

## Data Integration and Mapping

The connector organizes data into specific sources, staging tables, and target CMDB or non-CMDB classes, facilitating structured import and governance of AI components:

* **Execution Data:** Captured in staging and AI usage tables.
* **AI Systems:** Mapped to system components, digital assets, functions, and relationships in the CMDB.
* **Models:** Imported into model and digital asset tables.
* **Tools and Prompts:** Stored in AI tool and prompt-specific tables and models.
* **System Subcomponents:** Managed through many-to-many relationship tables for detailed asset linkage.

## Practical Benefits

By leveraging this connector, ServiceNow customers can:

* Gain centralized visibility and governance over AI assets deployed in GCP Vertex AI through the AI Control Tower.
* Automatically track AI usage data to assess operational performance and compliance.
* Maintain an up-to-date CMDB with detailed AI system, model, tool, and prompt information directly imported from GCP.
* Ensure compliance and operational control by integrating AI asset data within ServiceNow's governance framework.  
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 checkboxes.
4. Select Update.
5. Switch to the connector application scope.
{#gcp-vertex-ai__ol_sgt_yts_mjc}  
Clear cache

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

1. Navigate to System Definition \> Background Scripts
2. Paste the following script into 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 may take several minutes to complete.
4. After completion, switch to the connector application scope.
{#gcp-vertex-ai__ol_sy1_n5s_mjc}

## 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.

## 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}