AI Assets Inventory API

  • Release version: Australia
  • Updated June 8, 2026
  • 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).

    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 for more information about managing AI assets inventory in the AI Control Tower.

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

    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.

    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

    Table 1. Path parameters
    Name Description
    api_version Optional. Version of the endpoint to access. For example, v1 or v2. 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

    Data type: String
    Table 2. Query parameters
    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

    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

    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
    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

    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

    Default: asc

    Data type: String
    Table 3. Request body parameters (XML or JSON)
    Name Description
    None

    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.

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

    Default: application/json
    Table 5. Response headers
    Header Description
    None

    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.

    Table 6. Status codes
    Status code Description
    200 Successful. The request was successfully processed.

    Response body parameters (JSON or XML)

    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

    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

    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

    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

    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

    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

    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

    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.

    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

    Table 7. Path parameters
    Name Description
    api_version Optional. Version of the endpoint to access. For example, v1 or v2. 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 8. Query parameters
    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.

    Default: true

    Data type: String
    Table 9. Request body parameters (XML or JSON)
    Name Description
    None

    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.

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

    Default: application/json
    Table 11. Response headers
    Header Description
    None

    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.

    Table 12. Status codes
    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.
    500 Unhandled exception. For example, invalid date format. Check logs to verify date inputs use the calling user's session date format.

    Response body parameters (JSON or XML)

    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.

    Table 13. Common response parameters
    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)

    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

    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

    Related Assets

    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.

    When no governance record exists, only the base fields are returned.

    Table 14. AI System (asset_class: alm_ai_system_digital_asset)
    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 15. AI Model (asset_class: alm_ai_model_digital_asset)
    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 16. AI Prompt (asset_class: alm_ai_prompt_digital_asset)
    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 17. AI Dataset (asset_class: alm_ai_dataset_digital_asset)
    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"
  }
]

    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)

    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

    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

    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

    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'