---
sourceDocument: Australia API Reference
sourceDocumentLink: https://servicenow-prod.fluidtopics.net/r/api-reference

 Release :

    - australia

ft:locale :

    - en-US

ft:publication_title :

    - Australia API Reference

ft:clusterId :

    - crapiref

bundleId :

    - crapiref

workflow :

    - Creator


---

# AI Assets Inventory API

# AI Assets Inventory API {#ariaid-title1}

Release version: Australia  
Updated June 8, 2026  
![](https://www.servicenow.com/docs/portal-asset/ico-clock) 18 minutes to read  
The AI Assets Inventory APIs provide programmatic access to AI assets managed under the AI Control Tower application.
The AI Assets Inventory endpoints enable:

* Listing assets filtered by asset class with optional filtering, pagination, and sorting.
* Retrieving detailed information about a specific asset including its related assets.
* Querying governance data such as lifecycle phase, risk classification, and assessments (when the GRC AI Governance plugin is active).
{#ai-assets-inventory-api__ul_zhv_nxh_njc}

The AI Assets Inventory API requires the sn_ai_governance.integration.rest role and the AI Governance \[sn_ai_governance\] plugin to access it. The GET /details endpoint requires the AI Control
Tower Core \[sn_grc_ai_gov\] plugin to be active for Governance, Risk, and Compliance (GRC) lookups.

This API belongs to the sn_ai_governance namespace.

See [AI asset inventory](https://www.servicenow.com/docs/access?context=ai-inventory&version=australia&pubname=australia-intelligent-experiences&ft:locale=en-US) for more information about managing AI assets inventory in the [AI Control Tower](https://www.servicenow.com/docs/access?context=ai-control-tower-landing&version=australia&pubname=australia-intelligent-experiences&ft:locale=en-US).

## AI Assets Inventory - GET /api/sn_ai_governance/assets/{asset_class} {#ariaid-title2}

Retrieves a paginated list of AI governance records of a given asset class, with optional filters, sorting, and pagination.
Use this endpoint to:

* Browse all AI assets of a specific class.
* Filter assets by governance status, risk level, department, vendor, provider, etc.
* Page through inventories for reporting purposes.
{#ai-assets-inventory-GET-asset-class__ul_sjv_bzh_njc}

### URL format

Versioned URL: /api/sn_ai_governance/{api_version}/assets/{asset_class}

Default URL: /api/sn_ai_governance/assets/{asset_class}

### Supported request parameters

{#ai-assets-inventory-GET-asset-class__entry__2}{#ai-assets-inventory-GET-asset-class__version-not_optional-RESTAPI}

| Name | Description |
|-|-|
| api_version | Optional. Version of the endpoint to access. For example, <kbd class="ph userinput">v1</kbd> or <kbd class="ph userinput">v2</kbd>. Only specify this value to use an endpoint version other than the latest. Data type: String |
| asset_class | Required. Asset class table name. The value is matched against the Model Categories table, asset_class \[cmdb_model_category.asset_class\] field. Valid table values: * `alm_ai_system_digital_asset`: AI Systems (skills, agents, use cases) * `alm_ai_model_digital_asset`: AI Models * `alm_ai_prompt_digital_asset`: AI Prompts * `alm_ai_dataset_digital_asset`: AI Datasets {#ai-assets-inventory-GET-asset-class__ul_aqz_tzh_njc} Data type: String |
[Table 1. Path parameters]

{#ai-assets-inventory-GET-asset-class__entry__8}

| Name | Description |
|-|-|
| risk_classification | Filters results by the risk score of the AI asset. Supports comma-separated values. Valid values: * `1`: High risk * `2`: Medium risk * `3`: Low risk * `4`: Unacceptable risk * `5`: To be determined (default for new records) * 6: Critical {#ai-assets-inventory-GET-asset-class__ul_qhq_dc3_njc} Data type: String as an integer |
| lifecycle_status | Filters results by life cycle status of the AI asset. Valid values: * `1`: In review * `2`: Approved * `3`: Rejected * `4`: Deployed * `5`: AI steward review * `6`: Approved for development * `7`: Ready for deployment * `8`: Approved for deployment * `9`: Canceled * `10`: Offboarded Data type: String |
| state | Filters results by the installation status of the AI asset. Values are instance-dependent. Refer to the install_status field's choice list on the cmdb_ci table in your instance to enumerate them. The platform default 'Installed' is typically value 1. Data type: String |
| asset_type | Filter by model category name or sys_id. Valid names: * AI System * AI Model * AI Prompt * AI Dataset * Generative AI * Agentic AI * Classic AI {#ai-assets-inventory-GET-asset-class__ul_chj_n33_njc} These values are the canonical names referenced by the app and are stable across instances unless renamed. Table: CMDB Model Category \[cmdb_model_category\] for name; AIGovernanceWsConstants.MODEL_CATEGORIES for sys_id. Data type: String |
| lifecycle_phase | Filter by lifecycle phase name or sys_id. Valid name values: * Assess * New * Build and test * Build * Pre-deploy * Deploy * Offboard * Assess offboarding * Pre-offboarding {#ai-assets-inventory-GET-asset-class__ul_px2_233_njc} Note: Customer instances may add or rename these values. Refer to your instance's sn_ai_governance_lifecycle table. Table: AI Governance Lifecycle \[sn_ai_governance_lifecycle\] Data type: String |
| department | Filter by department name or sys_id. Table: Department \[cmn_department\] Data type: String |
| managed_by | Filter by user_name or sys_id of the user managing the asset. Table: User \[sys_user\] Data type: String |
| vendor | Filter by vendor company name or sys_id. Table: Core Company \[core_company\] Data type: String |
| provider | Filter by provider/manufacturer name or sys_id (matched against the product model's manufacturer). Table: Core Company \[core_company\] Data type: String |
| created_from | Display date format of the calling user's session. Format: YYYY-MM-DD Data type: String |
| created_to | Display date format of the calling user's session. Format: YYYY-MM-DD Data type: String |
| limit or sysparm_limit | Number of records to return. If limit is missing, less than 1, or non-numeric, the configured default is used. If limit exceeds the configured maximum, it's silently capped to the maximum (no warning). Minimum: 1 Maximum: 500 Default: 100 Data type: Integer |
| offset or sysparm_offset | Number of records to skip. If offset is missing or non-numeric, it's treated as 0; negative offsets are clamped to 0. Default: 0 Data type: Integer |
| sort_by | Field to sort by. Valid values: * risk_classification * lifecycle_phase * lifecycle_status * asset_type * department * managed_by * state * vendor * provider {#ai-assets-inventory-GET-asset-class__ul_itv_ck3_njc} Data type: String Default: Filters by the sys_created_on table field (table: \[sn_ai_governance_asset_governance_details\]), descending (newest first). |
| order_by | Sort direction. Case-insensitive. Only applied when sort_by is provided and valid. Valid values: * `asc`: Ascending order * `desc`: Descending order {#ai-assets-inventory-GET-asset-class__ul_kq2_wj3_njc} Default: `asc` Data type: String |
[Table 2. Query parameters]

{#ai-assets-inventory-GET-asset-class__entry__40}

| Name | Description |
|-|-|
| None |   |
[Table 3. Request body parameters (XML or JSON)]

### Headers

The following request and response headers apply to this HTTP
action only, or apply to this action in a distinct way. For a list of general headers used
in the REST API, see [Supported REST API headers](https://servicenow-prod.fluidtopics.net/qh7RcF0RI6a~i9u3octdlg "REST (REpresentational State Transfer) is a simple stateless architecture that provides standards between computer systems on the web, making it easier for them to communicate with each other.").
{#ai-assets-inventory-GET-asset-class__entry__44}{#ai-assets-inventory-GET-asset-class__accept-RESTAPI}

| Header | Description |
|-|-|
| Accept | Data format of the response body. Supported types: application/json or application/xml. Default: application/json |
[Table 4. Request headers]

{#ai-assets-inventory-GET-asset-class__table_nhb_my1_sjc__entry__2}

| Header | Description |
|-|-|
| None |   |
[Table 5. Response headers]

{#ai-assets-inventory-GET-asset-class__table_nhb_my1_sjc}

### Status codes

The following status codes apply to this HTTP action. For a
list of possible status codes used in the REST API, see [REST API HTTP response
codes](https://servicenow-prod.fluidtopics.net/qh7RcF0RI6a~i9u3octdlg "REST (REpresentational State Transfer) is a simple stateless architecture that provides standards between computer systems on the web, making it easier for them to communicate with each other.").
{#ai-assets-inventory-GET-asset-class__entry__52}{#ai-assets-inventory-GET-asset-class__entry-200-status-code}

| Status code | Description |
|-|-|
| 200 | Successful. The request was successfully processed. |
[Table 6. Status codes]

### Response body parameters (JSON or XML)

{#ai-assets-inventory-GET-asset-class__entry__56}

| Name | Description |
|-|-|
| sys_id | Sys ID of the governance record. Table: sn_ai_governance_asset_governance_details |
| asset_name | Display name of the underlying digital asset. Table/field: Asset \[asset\], display_name |
| asset_type | Name of the underlying asset's model category. Table/field: Asset Model Category \[asset.model_category\], name |
| created_on | Display value of the governance record's sys_created_on field. Table: sn_ai_governance_asset_governance_details |
[ ]

### Get All AI Systems

This example retrieves all AI systems in the given instance.

    curl -X GET \ 
      'https://instance.service-now.com/api/sn_ai_governance/v1/assets/alm_ai_system_digital_asset' \ 
      -u 'username:password' \ 
      -H 'Accept: application/json'

Response body.

    {
      "result": [
        {
          "sys_id": "a1b2c3d4e5f6a7b8c9d0e1f2a3b4c5d6",
          "asset_name": "Customer Service Virtual Agent",
          "asset_type": "AI System",
          "created_on": "2025-06-18 12:00:00"
        },
        {
          "sys_id": "b2c3d4e5f6a7b8c9d0e1f2a3b4c5d6e7",
          "asset_name": "HR Benefits Chatbot",
          "asset_type": "Agentic AI",
          "created_on": "2025-06-04 08:30:00"
        },
        {
          "sys_id": "c3d4e5f6a7b8c9d0e1f2a3b4c5d6e7f8",
          "asset_name": "IT Incident Classifier",
          "asset_type": "Classic AI",
          "created_on": "2025-05-21 15:45:00"
        },
        {
          "sys_id": "d4e5f6a7b8c9d0e1f2a3b4c5d6e7f8a9",
          "asset_name": "Fraud Detection System",
          "asset_type": "AI System",
          "created_on": "2025-05-07 10:00:00"
        },
        {
          "sys_id": "e5f6a7b8c9d0e1f2a3b4c5d6e7f8a9b0",
          "asset_name": "Document Summarization Agent",
          "asset_type": "Generative AI",
          "created_on": "2025-04-23 17:20:00"
        }
      ]
    }

### Get High-Risk AI Systems in Production {#ai-assets-inventory-GET-asset-class__example_uq3_gl3_njc}

This example retrieves all AI Systems with a high-risk classification in the instance.

    curl -X GET \ 'https://instance.service-now.com/api/sn_ai_governance/v1/assets/alm_ai_system_digital_asset?risk_classification=1&state=1' \ 
      -u 'username:password' \ 
      -H 'Accept: application/json' 

Response body.

    {
      "result": [
        {
          "sys_id": "f6a7b8c9d0e1f2a3b4c5d6e7f8a9b0c1",
          "asset_name": "Fraud Detection System",
          "asset_type": "AI System",
          "created_on": "2025-05-07 10:00:00"
        },
        {
          "sys_id": "a7b8c9d0e1f2a3b4c5d6e7f8a9b0c1d2",
          "asset_name": "Credit Risk Scoring Engine",
          "asset_type": "Classic AI",
          "created_on": "2025-04-07 14:30:00"
        }
      ]
    }

### Get AI Models with Pagination {#ai-assets-inventory-GET-asset-class__example_hzg_jl3_njc}

The following example retrieves a paginated list of AI Model digital assets of max 50 records starting at the first record.

    curl -X GET \ 
      'https://instance.service-now.com/api/sn_ai_governance/v1/assets/alm_ai_model_digital_asset?limit=50&offset=0' \ 
      -u 'username:password' \ 
      -H 'Accept: application/json'

Response body.

    {
      "result": [
        {
          "sys_id": "1a2b3c4d5e6f7a8b9c0d1e2f3a4b5c6d",
          "asset_name": "GPT-4o Fine-tuned -- Legal Review",
          "asset_type": "AI Model",
          "created_on": "2025-01-31 16:00:00"
        },
        {
          "sys_id": "2b3c4d5e6f7a8b9c0d1e2f3a4b5c6d7e",
          "asset_name": "BERT Sentiment Classifier v2",
          "asset_type": "AI Model",
          "created_on": "2025-01-30 12:00:00"
        },
        {
          "sys_id": "3c4d5e6f7a8b9c0d1e2f3a4b5c6d7e8f",
          "asset_name": "Whisper Speech-to-Text",
          "asset_type": "AI Model",
          "created_on": "2025-01-29 08:00:00"
        }
      ]
    }

### Get AI Systems Created in a Date Range {#ai-assets-inventory-GET-asset-class__example_jvl_4l3_njc}

This example retrieves all AI Systems created in Q1 2025 (January 1 -- March 31) from the AI Governance inventory.

    curl -X GET \ 
      'https://instance.service-now.com/api/sn_ai_governance/v1/assets/alm_ai_system_digital_asset?created_from=2025-01-01&created_to=2025-03-31' \  
      -u 'username:password' \ 
      -H 'Accept: application/json'

Response body.

    {
      "result": [
        {
          "sys_id": "4d5e6f7a8b9c0d1e2f3a4b5c6d7e8f9a",
          "asset_name": "Q1 2025 Sales Forecasting Agent",
          "asset_type": "Generative AI",
          "created_on": "2025-03-28 09:00:00"
        },
        {
          "sys_id": "5e6f7a8b9c0d1e2f3a4b5c6d7e8f9a0b",
          "asset_name": "Compliance Monitoring System",
          "asset_type": "AI System",
          "created_on": "2025-02-27 11:30:00"
        },
        {
          "sys_id": "6f7a8b9c0d1e2f3a4b5c6d7e8f9a0b1c",
          "asset_name": "Employee Onboarding Assistant",
          "asset_type": "Agentic AI",
          "created_on": "2025-01-26 20:00:00"
        },
        {
          "sys_id": "7a8b9c0d1e2f3a4b5c6d7e8f9a0b1c2d",
          "asset_name": "IT Knowledge Base Search",
          "asset_type": "Classic AI",
          "created_on": "2025-01-01 04:00:00"
        }
      ]
    }

### Get AI Prompts by Department and Vendor {#ai-assets-inventory-GET-asset-class__example_wdm_4l3_njc}

This example retrieves all AI Prompts from the Engineering department associated with the Acme vendor from the AI Governance inventory.

    curl -X GET \ 
      'https://instance.service-now.com/api/sn_ai_governance/v1/assets/alm_ai_prompt_digital_asset?department=Engineering&vendor=Acme' \ 
      -u 'username:password' \ 
      -H 'Accept: application/json'

Response body.

    {
      "result": [
        {
          "sys_id": "8b9c0d1e2f3a4b5c6d7e8f9a0b1c2d3e",
          "asset_name": "Code Review Prompt Template",
          "asset_type": "AI Prompt",
          "created_on": "2025-06-18 12:00:00"
        },
        {
          "sys_id": "9c0d1e2f3a4b5c6d7e8f9a0b1c2d3e4f",
          "asset_name": "Bug Triage Summarization Prompt",
          "asset_type": "AI Prompt",
          "created_on": "2025-05-21 15:45:00"
        }
      ]
    }

### Get AI Systems Managed by a Specific User, Sorted by Department Descending {#ai-assets-inventory-GET-asset-class__example_sqm_4l3_njc}

This example retrieves all AI Systems managed by Jane Smith from the AI Governance inventory, sorted by department in descending order.

    curl -X GET \ 
      'https://instance.service-now.com/api/sn_ai_governance/v1/assets/alm_ai_system_digital_asset?managed_by=jane.smith&sort_by=department&order_by=desc' \ 
      -u 'username:password' \ 
      -H 'Accept: application/json'

Response body.

    {
      "result": [
        {
          "sys_id": "0d1e2f3a4b5c6d7e8f9a0b1c2d3e4f5a",
          "asset_name": "Sales Lead Scoring Engine",
          "asset_type": "Classic AI",
          "created_on": "2025-05-07 10:00:00"
        },
        {
          "sys_id": "1e2f3a4b5c6d7e8f9a0b1c2d3e4f5a6b",
          "asset_name": "Customer Service Virtual Agent",
          "asset_type": "AI System",
          "created_on": "2025-06-18 12:00:00"
        },
        {
          "sys_id": "2f3a4b5c6d7e8f9a0b1c2d3e4f5a6b7c",
          "asset_name": "Code Generation Assistant",
          "asset_type": "Generative AI",
          "created_on": "2025-06-04 08:30:00"
        }
      ]
    }

### Filter AI Models by Provider {#ai-assets-inventory-GET-asset-class__example_bwn_4l3_njc}

This example retrieves all AI Models provided by OpenAI from the AI Governance inventory.

    curl -X GET \ 
      'https://instance.service-now.com/api/sn_ai_governance/v1/assets/alm_ai_model_digital_asset?provider=OpenAI' \ 
      -u 'username:password' \ 
      -H 'Accept: application/json'

Response body.

    {
      "result": [
        {
          "sys_id": "3a4b5c6d7e8f9a0b1c2d3e4f5a6b7c8d",
          "asset_name": "GPT-4o Fine-tuned -- Legal Review",
          "asset_type": "AI Model",
          "created_on": "2025-06-18 12:00:00"
        },
        {
          "sys_id": "4b5c6d7e8f9a0b1c2d3e4f5a6b7c8d9e",
          "asset_name": "GPT-4o Mini -- Internal Q&A",
          "asset_type": "AI Model",
          "created_on": "2025-06-04 08:30:00"
        },
        {
          "sys_id": "5c6d7e8f9a0b1c2d3e4f5a6b7c8d9e0f",
          "asset_name": "text-embedding-3-large",
          "asset_type": "AI Model",
          "created_on": "2025-04-23 17:20:00"
        }
      ]
    }

## AI Assets Inventory - GET /api/sn_ai_governance/assets/{sys_id}/details {#ariaid-title3}

Retrieves comprehensive details about a specific AI governance record.
This endpoint retrieves the following record information for a single asset:

* Basic asset information such as display name, asset class, asset type.
* Life cycle phase and status, risk classification, state.
* Related assets.
* Governance, Risk, and Compliance (GRC) information (assessments, risks, issues, policy exceptions) when the sn_grc_ai_gov plugin is active.
{#ai-assets-inventory-GET-details__ul_hds_dxn_njc}

### URL format

Versioned URL: /api/sn_ai_governance/{api_version}/assets/{sys_id}/details

Default URL: /api/sn_ai_governance/assets/{sys_id}/details

### Supported request parameters

{#ai-assets-inventory-GET-details__entry__2}{#ai-assets-inventory-GET-details__version-not_optional-RESTAPI}

| Name | Description |
|-|-|
| api_version | Optional. Version of the endpoint to access. For example, <kbd class="ph userinput">v1</kbd> or <kbd class="ph userinput">v2</kbd>. Only specify this value to use an endpoint version other than the latest. Data type: String |
| sys_id | Sys_id of the governance record to retrieve. Table: AI Asset Governance Details \[sn_ai_governance_asset_governance_details\] Note: This isn't the sys_id of the AI Dataset Digital Asset \[alm_ai_dataset_digital_asset\] table. Data type: String |
[Table 7. Path parameters]

{#ai-assets-inventory-GET-details__entry__8}

| Name | Description |
|-|-|
| include_risk_info | Optional. Flag that indicates whether to perform GRC plugin lookups, such as ai_assessments, risk_assessments, regulatory_risk_assessments, bulk_risk_assessments, control_assessments, issues, policy_exceptions, and risks. Has no effect when the sn_grc_ai_gov plugin is inactive. Valid values: * true: Enables the lookup. Missing values or any other value ('true', 'False', '0') enables the lookup. * false: (case sensitive) Skips the lookup operation. {#ai-assets-inventory-GET-details__ul_tkv_nyn_njc} Default: true Data type: String |
[Table 8. Query parameters]

{#ai-assets-inventory-GET-details__entry__12}

| Name | Description |
|-|-|
| None |   |
[Table 9. Request body parameters (XML or JSON)]

### Headers

The following request and response headers apply to this HTTP
action only, or apply to this action in a distinct way. For a list of general headers used
in the REST API, see [Supported REST API headers](https://servicenow-prod.fluidtopics.net/qh7RcF0RI6a~i9u3octdlg "REST (REpresentational State Transfer) is a simple stateless architecture that provides standards between computer systems on the web, making it easier for them to communicate with each other.").
{#ai-assets-inventory-GET-details__entry__16}{#ai-assets-inventory-GET-details__accept-RESTAPI}

| Header | Description |
|-|-|
| Accept | Data format of the response body. Supported types: application/json or application/xml. Default: application/json |
[Table 10. Request headers]

{#ai-assets-inventory-GET-details__entry__20}

| Header | Description |
|-|-|
| None |   |
[Table 11. Response headers]

### Status codes

The following status codes apply to this HTTP action. For a
list of possible status codes used in the REST API, see [REST API HTTP response
codes](https://servicenow-prod.fluidtopics.net/qh7RcF0RI6a~i9u3octdlg "REST (REpresentational State Transfer) is a simple stateless architecture that provides standards between computer systems on the web, making it easier for them to communicate with each other.").
{#ai-assets-inventory-GET-details__entry__24}{#ai-assets-inventory-GET-details__entry-200-status-code}

| Status code | Description |
|-|-|
| 200 | Successful. The request was successfully processed. |
| 400 | Sys_id path parameter missing or empty. Provide a valid sys_id in the URL path. |
| 401 | Invalid or missing credentials. Check username/password or OAuth token. |
| 403 | Caller lacks the required role(s). Ensure the user holds the sn_ai_governance.integration.rest role. |
| 404 | Possible causes: * asset_class doesn't match any Model Categories table, asset_class \[cmdb_model_category.asset_class\] value. Use one of the four documented asset_class values. * No governance record exists for the given sys_id. Verify the sys_id is a row in the AI Asset Governance Details \[sn_ai_governance_asset_governance_details\] table. {#ai-assets-inventory-GET-details__ul_abr_s34_njc} |
| 500 | Unhandled exception. For example, invalid date format. Check logs to verify date inputs use the calling user's session date format. |
[Table 12. Status codes]

### Response body parameters (JSON or XML) {#ai-assets-inventory-GET-details__section_y3q_jj4_njc}

The top-level response shape is the same for all asset classes. The related_assets object structure varies by asset class. See the Related Assets section for response parameters categorized by class.
{#ai-assets-inventory-GET-details__table_z3q_jj4_njc__entry__2}

| Name | Description |
|-|-|
| ai_assessments | GRC AI assessments associated with this asset. Empty array if the GRC plugin isn't active or include_risk_info is `false`. Data type: Array of Objects ``` ``` |
| asset_class | Table name (sys_class_name) of the digital asset. Valid values: * `alm_ai_system_digital_asset`: AI Systems (sub_ai_systems, tools, ai_models, ai_prompts, evaluation_datasets, input_outputs, configuration_items, business_applications) * `alm_ai_model_digital_asset`: AI Models (derived_ai_models, training_datasets, evaluation_datasets, ai_systems, input_outputs, model_lineages, configuration_items, business_applications) * `alm_ai_prompt_digital_asset`: AI Prompts (ai systems) * `alm_ai_dataset_digital_asset`: AI Datasets (ai_systems, ai_models, parent_datasets, child_datasets) {#ai-assets-inventory-GET-details__ul_x1f_1d4_njc} Data type: String |
| asset_type | Display value of the asset's model_category. Data type: String |
| bulk_risk_assessments | GRC bulk risk assessments. Same conditions as ai_assessments. Data type: Array of Objects "bulk_risk_assessments": [ { } ] |
| control_assessments | GRC controls. Data type: Array of Objects "control_assessments": [ { } ] |
| display_name | Display name of the underlying digital asset. Data type: String |
| issues | GRC issues associated with this asset. Data type: Array of Objects "issues": [ { } ] |
| lifecycle_phase | Life cycle phase of the asset. Data type: Object "lifecycle_phase": { "sys_id": "String", "name":   "String" } |
| lifecycle_phase.sys_id | Sys_id of the life cycle phase record. Table: AI Governance Lifecycle \[sn_ai_governance_lifecycle\] Data type: String |
| lifecycle_phase.name | Display value of the life cycle phase record. Data type: String |
| lifecycle_status | Raw stored integer value of the status field on the governance record. This is the choice value, not the display label. Refer to the status field's choice list to enumerate values. Data type: String |
| policy_exceptions | GRC policy exceptions. Data type: Array of Objects "policy_exceptions": [ { } ] |
| regulatory_risk_assessments | GRC regulatory risk classifications. Same conditions as ai_assessments. Data type: Array of Objects "regulatory_risk_assessments": [ { } ] |
| related_assets | Related-asset groupings; structure depends on asset_class. returns different fields depending on the asset_class of the requested governance record. See the Related Assets section for associated parameters organized by asset type. Data type: Object "related_assets": [ { } ] |
| risk_assessments | GRC risk assessments. Same conditions as ai_assessments. Data type: Array of Objects "risk_assessments": [ { } ] |
| risk_classification | Display value of risk_score on the governance record. Possible values: * `1`: High risk * `2`: Medium risk * `3`: Low risk * `4`: Unacceptable risk * `5`: To be determined (default for new records) * 6: Critical {#ai-assets-inventory-GET-details__ul_qhq_dc3_njc} Data type: String |
| risks | GRC risks. Data type: Array of Objects "risks": [ { } ] |
| state | Install status on the linked digital asset. The serialized value reflects the raw integer (for example, 1), not the display label. Note: This differs from the state field inside related_assets items, which returns the display value. Data type: String |
[Table 13. Common response parameters]

{#ai-assets-inventory-GET-details__table_z3q_jj4_njc}

### Related Assets {#ai-assets-inventory-GET-details__section_ajq_jj4_njc}

The related_assets object returns different fields depending on the asset_class of the requested governance record. Each table documents the fields returned for that asset class, along with the structure of each item in the returned array.  
Note:  
For related assets that have a governance record,

* sys_id is the governance record's sys_id (not the digital asset's sys_id),
* name is the governance display value,
* additional governance fields (risk_classification, lifecycle_status, lifecycle_phase, state) are included.

{#ai-assets-inventory-GET-details__ul_ksb_sj4_njc}

When no governance record exists, only the base fields are returned.
{#ai-assets-inventory-GET-details__table_zz3_c14_njc__entry__2}

| Name | Description |
|-|-|
| ai_models | AI Models referenced from the system's ai_models field. Data type: Object ai_models: [ { "sys_id": "String", "name": "String", "asset_class": "String", "asset_type": "String", // Governance fields (when record exists): "risk_classification": "String", "lifecycle_status": "String", "lifecycle_phase": "String", "state": "String" } ] |
| ai_prompts | AI Prompts referenced from the system's ai_prompts field. Data type: Object ai_prompts: [ { "sys_id": "String", "name": "String", "asset_class": "String", "asset_type": "String", // Governance fields (when record exists): "risk_classification": "String", "lifecycle_status": "String", "lifecycle_phase": "String", "state": "String" } ] |
| business_applications | Business applications mapped to this asset's product model via the Product Model Map \[sn_apm_ws_ba_product_model_map\] table. Returned only if that table exists in the instance. Data type: Object business_applications: [ { "sys_id": "String", "name": "String" } ] |
| configuration_items | CIs related to this digital asset via the Asset-CI Relationship \[cmdb_rel_asset_ci\] table. Data type: Object configuration_items: [ { "sys_id": "String", "name":   "String" } ] |
| evaluation_datasets | AI datasets referenced from the system's evaluation_datasets field. Data type: Object evaluation_datasets: [ { "sys_id": "String", "name": "String", "asset_class": "String", "asset_type": "String", // Governance fields (when record exists): "risk_classification": "String", "lifecycle_status": "String", "lifecycle_phase": "String", "state": "String" } ] |
| input_outputs | Input/output specifications for this system. Table/field: AI Input Output \[sn_ent_ai_input_output\], Category \[io_category\] Data type: Object input_outputs: [ { "sys_id": "String", "name": "String", "description": "String", "io_type": "String", "information_object": "String" } ] |
| sub_ai_systems | AI Systems registered as subcomponents of this system, sourced from the AI System Subcomponent Map \[sn_ent_ai_system_subcomponent_m2m\] table where `ai_subcomponent_reference_table = alm_ai_system_digital_asset`; this indicates that the field name ai_subcomponent_reference_table should be filled with the AI Asset tables. When a governance record exists for the related asset, the governance record's sys_id, name, and governance fields are included. When no governance record exists, only the base fields are returned. Data type: Array of Objects sub_ai_systems: [ { "sys_id": "String", "name": "String", "description": "String", "asset_class": "String", // Governance fields (when record exists): "risk_classification": "String", "lifecycle_status": "String", "lifecycle_phase": "String", "state": "String" } ] |
| tools | Enterprise AI tools registered as subcomponents, sourced the AI System Subcomponent Map \[sn_ent_ai_system_subcomponent_m2m\] table where `ai_subcomponent_reference_table = sn_ent_ai_tool`; this indicates that the field name ai_subcomponent_reference_table should be filled with the tools tables. Data type: Array of Objects tools: [ { "sys_id": "String", "name": "String", "description": "String", "asset_class": "String", // Governance fields (when record exists): "risk_classification": "String", "lifecycle_status": "String", "lifecycle_phase": "String", "state": "String" } ] |
[Table 14. AI System (asset_class: alm_ai_system_digital_asset)]

{#ai-assets-inventory-GET-details__table_zz3_c14_njc} {#ai-assets-inventory-GET-details__table_rnd_5b4_njc__entry__2}

| Name | Description |
|-|-|
| derived_ai_models | AI Models whose base_model points to this model. Table: AI Model Digital Asset \[alm_ai_model_digital_asset\] Data type: Array of Objects derived_ai_models: [ { "sys_id": "String", "name": "String" } ] |
| training_datasets | Datasets referenced from this model's training_datasets field. Table: AI Dataset Digital Asset \[alm_ai_dataset_digital_asset\] Data type: Array of Objects training_datasets: [ { "sys_id": "String", "name":   "String" } ] |
| evaluation_datasets | Datasets referenced from this model's evaluation_datasets field. Table: AI Dataset Digital Asset \[alm_ai_dataset_digital_asset\] Data type: Array of Objects evaluation_datasets: [ { "sys_id": "String", "name":   "String" } ] |
| ai_systems | AI Systems whose ai_models field contains this model. Table: AI System Digital Asset \[alm_ai_system_digital_asset\] Data type: Array of Objects ai_systems: [ { "sys_id": "String", "name":   "String" } ] |
| input_outputs | Input/output specifications. Table: AI Input Output \[sn_ent_ai_input_output\] table, Category \[io_category\] field Data type: Array of Objects input_outputs: [ { "sys_id": "String", "name": "String", "description": "String", "io_type": "String", "information_object": "String" } ] |
| model_lineages | Models of this type. Table: AI Model Lineage \[sn_ent_ai_model_lineage\], AI model digital asset \[ai_model\] column Data type: Array of Objects model_lineages: [ { "sys_id": "String", "dataset":  "String", "activity": "String", "training_procedure": "String", "model_checkpoint_id": "String", "user_group": "String", "start_time": "String", "end_time": "String" } ] |
| configuration_items | CIs related to this digital asset. Table: Asset-CI Relationship \[cmdb_rel_asset_ci\] Data type: Array of Objects configuration_items: [ { "sys_id": "String", "name":   "String" } ] |
| business_applications | Business applications mapped to this asset's product model, if the Product Model Map \[sn_apm_ws_ba_product_model_map\] table exists in the instance. Data type: Array of Objects business_applications: [ { "sys_id": "String", "name":   "String" } ] |
[Table 15. AI Model (asset_class: alm_ai_model_digital_asset)]

{#ai-assets-inventory-GET-details__table_rnd_5b4_njc} {#ai-assets-inventory-GET-details__table_ll5_hc4_njc__entry__2}

| Name | Description |
|-|-|
| ai_systems | AI Systems whose ai_prompts field contains this prompt. Table: AI System Digital Asset \[alm_ai_system_digital_asset\] Data type: Array of Objects ai_systems: [ { "sys_id": "String", "name":   "String" } ] |
[Table 16. AI Prompt (asset_class: alm_ai_prompt_digital_asset)]

{#ai-assets-inventory-GET-details__table_ll5_hc4_njc} {#ai-assets-inventory-GET-details__table_zyf_qc4_njc__entry__2}

| Name | Description |
|-|-|
| ai_systems | AI Systems whose evaluation_datasets field contains this dataset. Table: AI System Digital Asset \[alm_ai_system_digital_asset\] Data type: Array of Objects ai_systems: [ { "sys_id": "String", "name":   "String" } ] |
| ai_models | AI Models whose training_datasets or evaluation_datasets field contains this dataset. Table: AI Model Digital Asset \[alm_ai_model_digital_asset\] Data type: Array of Objects ai_models: [ { "sys_id": "String", "name":   "String" } ] |
| parent_datasets | Datasets referenced from this dataset's base_datasets field. Table: AI Dataset Digital Asset \[alm_ai_dataset_digital_asset\] Data type: Array of Objects parent_datasets: [ { "sys_id": "String", "name":   "String" } ] |
| child_datasets | Datasets whose base_datasets field contains this dataset. Table: AI Dataset Digital Asset \[alm_ai_dataset_digital_asset\] Data type: Array of Objects child_datasets: [ { "sys_id": "String", "name":   "String" } ] |
[Table 17. AI Dataset (asset_class: alm_ai_dataset_digital_asset)]

{#ai-assets-inventory-GET-details__table_zyf_qc4_njc}  

### Get AI System details

Request to retrieve asset_class
`alm_ai_system_digital_asset` details:

    curl -X GET \
      'https://instance.service-now.com/api/sn_ai_governance/v1/assets/a1b2c3d4e5f6a1b2c3d4e5f6a1b2c3d4/details' \
      -u 'username:password' \
      -H 'Accept: application/json'

Response body:

    {
      "display_name": "Customer Service AI Assistant", 
      "asset_type": "Generative AI", 
      "asset_class": "alm_ai_system_digital_asset", 
      "lifecycle_status": "2", 
      "lifecycle_phase": { "sys_id": "lifecycle123", "name": "Production" }, 
      "state": "1", 
      "risk_classification": "medium", 
      "related_assets": { 
        "sub_ai_systems": [ 
          { 
            "sys_id": "govSub123", 
            "name": "FAQ Handler Sub-Agent", 
            "description": "Handles frequently asked questions", 
            "asset_class": "alm_ai_system_digital_asset", 
            "risk_classification": "low", 
            "lifecycle_status": "2", 
            "lifecycle_phase": "Production", 
            "state": "Active" 
          } 
        ], 
        "tools": [ 
          { 
            "sys_id": "tool123", 
            "name": "Knowledge Base Search", 
            "description": "Searches internal knowledge base", 
            "asset_class": "sn_ent_ai_tool" 
          } 
        ], 
        "ai_models": [ 
          { "sys_id": "govModel123", "name": "GPT-4", 
            "asset_class": "alm_ai_model_digital_asset", "asset_type": "Generative AI", 
            "risk_classification": "1", "lifecycle_status": "2", 
            "lifecycle_phase": "Production", "state": "Active" } 
        ], 
        "ai_prompts": [ 
          { "sys_id": "govPrompt123", "name": "Customer Service Greeting Prompt", 
            "asset_class": "alm_ai_prompt_digital_asset", "asset_type": "Prompt" } 
        ], 
        "evaluation_datasets": [ 
          { "sys_id": "govDataset123", "name": "CS Evaluation Dataset", 
            "asset_class": "alm_ai_dataset_digital_asset", "asset_type": "Dataset" } 
        ], 
        "input_outputs": [ 
          { "sys_id": "io123", "name": "Customer Query", 
            "description": "Natural language customer question", 
            "io_type": "Input", "information_object": "Text" }, 
          { "sys_id": "io456", "name": "AI Response", 
            "description": "AI-generated response to customer", 
            "io_type": "Output", "information_object": "Text" } 
        ], 
        "configuration_items": [ 
          { "sys_id": "ci123", "name": "CS AI Assistant CI" } 
        ], 
        "business_applications": [ 
          { "sys_id": "ba123", "name": "Customer Service Platform" } 
        ] 
      }, 
      "ai_assessments": [], 
      "risk_assessments": [], 
      "regulatory_risk_assessments": [], 
      "bulk_risk_assessments": [], 
      "control_assessments": [], 
      "issues": [], 
      "policy_exceptions": [], 
      "risks": [] 
    }

### Get AI Model details (skip GRC data) {#ai-assets-inventory-GET-details__example_imm_dc4_njc}

Request to retrieve asset_class
`alm_ai_model_digital_asset` details:

    curl "https://instance.servicenow.com/api/sn_ent/asset/ai_system/3b140397435a9210a63d00002fb8f2d7" \
    --request GET \
    --header "Accept:application/json" \
    --user "username":"password"

Response body:

    {
      "display_name": "GPT-4 Turbo", 
      "asset_type": "AI Model", 
      "asset_class": "alm_ai_model_digital_asset", 
      "lifecycle_status": "2", 
      "lifecycle_phase": { "sys_id": "lifecycle456", "name": "Production" }, 
      "state": "1", 
      "risk_classification": "1", 
      "related_assets": { 
        "derived_ai_models": [ 
          { "sys_id": "derived123", "name": "GPT-4 Turbo Fine-tuned for CS" } 
        ], 
        "training_datasets": [ 
          { "sys_id": "train123", "name": "General Training Dataset" } 
        ], 
        "evaluation_datasets": [ 
          { "sys_id": "eval123", "name": "Model Evaluation Dataset" } 
        ], 
        "ai_systems": [ 
          { "sys_id": "sys123", "name": "Customer Service AI Assistant" } 
        ], 
        "input_outputs": [], 
        "model_lineages": [ 
          { 
            "sys_id": "lineage123", 
            "dataset": "Training Dataset v2.0", 
            "activity": "Fine-tuning", 
            "training_procedure": "Supervised Learning", 
            "model_checkpoint_id": "checkpoint_42", 
            "user_group": "AI Team", 
            "start_time": "2026-01-10 08:00:00", 
            "end_time": "2026-01-12 18:30:00" 
          } 
        ], 
        "configuration_items": [ 
          { "sys_id": "ciModel1", "name": "GPT-4 Turbo CI" } 
        ], 
        "business_applications": [ 
          { "sys_id": "baModel1", "name": "AI Platform" } 
        ] 
      }, 
      "ai_assessments": [], 
      "risk_assessments": [], 
      "regulatory_risk_assessments": [], 
      "bulk_risk_assessments": [], 
      "control_assessments": [], 
      "issues": [], 
      "policy_exceptions": [], 
      "risks": [] 
    }

### Get AI Prompt details {#ai-assets-inventory-GET-details__example_ndx_lc4_njc}

Request to retrieve asset_class
`alm_ai_prompt_digital_asset` details:

    curl -X GET \
      'https://instance.service-now.com/api/sn_ai_governance/v1/assets/e5f6a1b2c3d4e5f6a1b2c3d4e5f6a1b2/details' \
      -u 'username:password' \
      -H 'Accept: application/json'

Respone body:

    { 
      "display_name": "Customer Greeting Prompt", 
      "asset_type": "AI Prompt", 
      "asset_class": "alm_ai_prompt_digital_asset", 
      "lifecycle_status": "2", 
      "lifecycle_phase": { "sys_id": "lifecycle789", "name": "Production" }, 
      "state": "Active", 
      "risk_classification": "low", 
      "related_assets": { 
        "ai_systems": [ 
          { "sys_id": "sys123", "name": "Customer Service AI Assistant" } 
        ] 
      }, 
      "ai_assessments": [], 
      "risk_assessments": [], 
      "regulatory_risk_assessments": [], 
      "bulk_risk_assessments": [], 
      "control_assessments": [], 
      "issues": [], 
      "policy_exceptions": [], 
      "risks": [] 
    }

### Get AI Dataset details {#ai-assets-inventory-GET-details__example_as3_vc4_njc}

Request to retrieve asset_class
`alm_ai_dataset_digital_asset` details:

    curl -X GET \
      'https://instance.service-now.com/api/sn_ai_governance/v1/assets/d4e5f6a1b2c3d4e5f6a1b2c3d4e5f6a1/details' \
      -u 'username:password' \
      -H 'Accept: application/json'

Response body:

    { 
      "display_name": "Customer Service Evaluation Dataset", 
      "asset_type": "AI Dataset", 
      "asset_class": "alm_ai_dataset_digital_asset", 
      "lifecycle_status": "2", 
      "lifecycle_phase": { "sys_id": "lifecycle321", "name": "Production" }, 
      "state": "Active", 
      "risk_classification": "low", 
      "related_assets": { 
        "ai_systems": [ 
          { "sys_id": "sys123", "name": "Customer Service AI Assistant" } 
        ], 
        "ai_models": [ 
          { "sys_id": "model123", "name": "GPT-4" } 
        ], 
        "parent_datasets": [ 
          { "sys_id": "parent123", "name": "Base CS Dataset" } 
        ], 
        "child_datasets": [ 
          { "sys_id": "child123", "name": "Extended CS Dataset v2" } 
        ] 
      }, 
      "ai_assessments": [], 
      "risk_assessments": [], 
      "regulatory_risk_assessments": [], 
      "bulk_risk_assessments": [], 
      "control_assessments": [], 
      "issues": [], 
      "policy_exceptions": [], 
      "risks": [] 
    }

### Quick Command Reference {#ai-assets-inventory-GET-details__id_ksm_zf4_njc}

List all AI systems:

    curl -X GET 'https://instance.service-now.com/api/sn_ai_governance/v1/assets/alm_ai_system_digital_asset'
     -u 'user:password' 

Get high-risk assets:

    curl -X GET 'https://instance.service-now.com/api/sn_ai_governance/v1/assets/alm_ai_system_digital_asset?risk_classification=1'
     -u 'user:password' 

Get asset details (skip GRC data):

    curl -X GET 'https://instance.service-now.com/api/sn_ai_governance/v1/assets/{sys_id}/details'
     -u 'user:password'

Paginate results:

    curl -X GET 'https://instance.service-now.com/api/sn_ai_governance/v1/assets/alm_ai_system_digital_asset?limit=100&offset=0'
     -u 'user:password'