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sourceDocument: Australia Enable AI
sourceDocumentLink: https://www.servicenow.com/docs/r/australia/intelligent-experiences

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    - australia

ft:locale :

    - en-US

ft:publication_title :

    - Australia Enable AI

ft:clusterId :

    - platai

bundleId :

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workflow :

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---

# Managing your AI asset inventory

# Managing your AI asset inventory {#ariaid-title1}

Release version: Australia  
Updated August 5, 2026  
![](https://www.servicenow.com/docs/portal-asset/ico-clock) 5 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 Managing your AI asset inventory

The AI asset inventory in AI Control Tower provides ServiceNow customers with a centralized record of all AI assets across their organization, including AI systems, models, prompts, and datasets.
It enables comprehensive tracking and governance by collecting assets discovered automatically, added manually, or integrated via connectors.
This inventory is essential for managing AI asset participation in governance, monitoring, and risk workflows.
Show full answer Show less  

## Key Features

* **Comprehensive Asset Tracking:** View all AI assets by type (datasets, prompts, models, systems, servers) with detailed columns such as name, type, operational state, governance status, risk classification, domain, and assigned stewards.
* **Governance Control:** Set assets as managed to include them in governance workflows or leave them unmanaged to exclude them, controlling lifecycle management, risk classification, security, and privacy processes.
* **Filtering and Refinement:** Filter assets by type, risk level, lifecycle state, and management status to prioritize attention and governance efforts.
* **Manual and Automated Asset Addition:** Add assets manually when not discoverable automatically, and understand discovery methods through connectors or traces.
* **AI System Governance:** Govern primary AI applications (Agentic AI, Generative AI, Classic AI) by risk classification, stewardship assignment, performance monitoring, and value measurement all in one record.
* **Model and Dataset Visibility:** Track AI models including vendor and lifecycle data, and datasets supporting training and evaluation to ensure compliance, data lineage, and risk assessment.
* **Prompt Management:** Maintain control over AI system prompts and templates to ensure alignment with policies and acceptable use standards, and understand the impact of prompt changes.
* **Duplicate Asset Detection:** Identify and review potential duplicate AI assets to streamline governance and avoid redundant efforts.
* **Bulk Management and Automation:** Use automation rules to classify and manage large numbers of AI assets efficiently based on defined conditions.
* **Evaluation and Quality Monitoring:** Enable evaluation scoring to detect quality and safety regressions in AI assets and track trends for timely intervention.
* **Deactivation Capability:** Deactivate managed AI agents directly from the inventory using kill switch protocols for immediate containment.

## Access and Roles

Access to the AI asset inventory requires either the AI steward or AI system owner roles, ensuring governance responsibilities are assigned to appropriate personnel.

## Practical Impact for ServiceNow Customers

By leveraging the AI asset inventory, customers can achieve full visibility and control over their AI assets, ensuring compliance with governance policies, managing risk effectively, and maintaining operational integrity. The inventory supports proactive oversight through automation, evaluation, and direct intervention capabilities, empowering organizations to maintain trustworthy and compliant AI deployments at scale.  
Track every AI system, model, prompt, and dataset across your enterprise and control which assets participate in governance, monitoring, and risk workflows.

## Key benefits {#disc-ai-asset-inventory__key-benefits}

The AI asset inventory is the central record of AI assets in your organization. Assets that AI Control Tower discovers or identifies through traces appears here, organized by asset type.

* Get a complete picture of every AI asset across your organization, including assets discovered automatically and those added manually or through connectors.
* Control which assets participate in governance, monitoring, and risk workflows by setting management status directly from the inventory list.
* Filter and refine the asset list by type, risk classification, lifecycle state, asset status, and management status to focus on what needs attention.
* Add assets manually when a connector or trace can't reach them. See [Creating AI assets manually](https://www.servicenow.com/docs/1yiXBzbNrSilZdYDHgcVcA "You can create AI assets manually to track and manage the life cycles of your AI systems, AI models, prompts, and datasets.").

{#disc-ai-asset-inventory__ul_key_benefits}

For the ways AI Control Tower adds assets to your inventory automatically, see [Discovering AI assets](https://www.servicenow.com/docs/XtCTTEOQwE2~knZgwn9KmA "Populate your AI asset inventory automatically as AI Control Tower discovers AI assets across external platforms, hyperscaler traces, and your ServiceNow instance.").
Figure 1. AI asset inventory

## AI assets list columns {#disc-ai-asset-inventory__ai-assets-list-columns}

{#disc-ai-asset-inventory__table_ux4_5dv_kkc__entry__2}

| Column | Description |
|-|-|
| Name | The name of the AI asset as registered in AI Control Tower. |
| Asset type | The category of the AI asset, such as AI dataset, AI prompt, AI model, MCP server, or AI system. |
| State | The operational state of an AI asset. |
| Status | The governance status of the asset within its current phase. |
| Managed status | Indicates whether the asset is actively governed. Displays as true or false. |
| Domain | Domain the asset belongs to. |
| Managed by | The team or individual responsible for governing the asset. |
| Risk classification | The assessed risk level of an AI asset. |
| Updated | The date and time the asset record was last modified. |
[ ]

{#disc-ai-asset-inventory__table_ux4_5dv_kkc}

## Required roles {#disc-ai-asset-inventory__required-roles}

The AI steward \[sn_ai_governance.ai_steward\] or AI system owner \[sn_ai_asset_mgmt.ai_asset_owner\] role is required to access the AI asset inventory.

## Accessing the AI asset inventory {#disc-ai-asset-inventory__accessing}

Navigate to AllAI Control TowerHomeInventoryAssets.

## AI systems {#disc-ai-asset-inventory__ai-systems}

An AI system is a deployed AI application or capability that your organization uses to perform work. Examples include Now Assist skills, AI agents built in AI Agent Studio, and AI-powered applications running on external platforms. AI systems are the primary unit of governance in AI Control Tower, and the assets you classify for risk, assign stewards to, monitor for performance, and measure for value.

In the Inventory, AI systems are identified by asset type: Agentic AI, Generative AI, or Classic AI. Select the AI systems tab to filter to these three types together.

* Filter to AI systems only to focus on the assets central to your governance program, regardless of provider.
* Select an AI system record to review lifecycle details, risk classification, monitoring data, and value metrics in one place.
* Designate AI systems as managed to bring them into governance workflows, or initiate a steward review to transition an unmanaged system automatically.
{#disc-ai-asset-inventory__ul_ai_systems}

## AI models {#disc-ai-asset-inventory__ai-models}

An AI model is a machine learning model or large language model (LLM) that powers one or more AI systems. Tracking models in the inventory gives you visibility into which models are in use across your organization, which vendors
supply them, and whether they are approved for their current deployment context.

* Identify which models are active across your organization, including models imported from external providers such as OpenAI, Mistral AI, and Google.
* Review provider, vendor, and lifecycle state for each model to confirm models are from approved sources and are current.
* Spot models that may need review as vendors release new versions or as vendor relationships change.
{#disc-ai-asset-inventory__ul_ai_models}

## AI datasets {#disc-ai-asset-inventory__datasets}

A dataset is a collection of data used for training, fine-tuning, or evaluating an AI model. Tracking datasets in the inventory supports data lineage, compliance documentation, and risk assessment for AI systems that depend on
specific training data.

* Track training, fine-tuning, and evaluation datasets alongside the models they support to maintain data lineage across your AI portfolio.
* Review provider, asset state, and management status for each dataset to identify datasets that may affect risk classification for dependent AI systems.
* Support compliance documentation by keeping a complete record of the data your AI models were built on.
{#disc-ai-asset-inventory__ul_datasets}

## AI prompts {#disc-ai-asset-inventory__prompts}

A prompt is a system prompt or prompt template that shapes the behavior of an AI system. Prompts define the instructions, context, and constraints an AI model operates under, making them a key governance asset for organizations
that require AI behavior aligns with policy and acceptable use standards.

* See all system prompts and templates in use across your organization's AI systems in one place.
* Identify prompts that may need policy review or update as acceptable use standards evolve.
* Understand the reach of any prompt change before making it by tracking which AI systems and models each prompt supports.
{#disc-ai-asset-inventory__ul_prompts}

## Reviewing duplicate AI assets {#disc-ai-asset-inventory__reviewing-duplicates}

AI asset deduplication can detect assets in your inventory that perform the same function, such as when
two teams independently build similar AI agents to solve the same problem. AI Control Tower surfaces these likely duplicates as a group for an AI steward to review. The AI steward can then confirm the group as true duplicates or dismiss it, before changes are made to relevant asset
records. For more information, see [Duplicate AI assets](https://www.servicenow.com/docs/ZWjpr_2p7Au77BljOB53sw "AI asset deduplication in AI Control Tower identifies duplicate records in the AI asset inventory for AI Stewards to review and consolidate.").

## Managing the status of AI assets {#disc-ai-asset-inventory__section_esd_pml_hjc}

Control whether an AI asset participates in governance workflows by setting its management status. Managed assets are included in lifecycle management, governance, risk classification, value assessment, security, and privacy
capabilities. Unmanaged assets are tracked in the inventory but excluded from those workflows. For more information, see [Managed and unmanaged AI assets](https://www.servicenow.com/docs/qaIYUAdP735ntoFfH3Yb1Q "Control whether an AI asset participates in governance workflows by changing the status in AI Control Tower.").

## Managing AI assets in bulk {#disc-ai-asset-inventory__section_bulk_managing_assets}

Classify large numbers of AI assets automatically instead of moving them to managed one at a time by creating automation rules. A rule matches assets against conditions you define, such as asset type or usage patterns, and marks
every matching asset as managed at each scheduled run. For more information, see [Managing AI assets in bulk](https://www.servicenow.com/docs/HuzDBeT~q47GLlzlNohlfA "Classify large numbers of AI assets automatically instead of moving them to managed one at a time by creating automation rules.").

## Managing evaluations {#disc-ai-asset-inventory__section_jn4_sll_hjc}

Detect quality and safety regressions in your managed AI assets by enabling evaluation. Evaluation scoring assesses AI interactions against configurable quality and safety metrics and surfaces trends so you can investigate
regressions before they affect users. Disable evaluation when an asset no longer needs active scoring; historical scores are retained either way. For more information, see [Evaluating AI systems](https://www.servicenow.com/docs/X8~KzD33o9v8q1cWl~10FA "Monitor the quality and safety of select AI systems by enabling evaluations.").

## Deactivating managed AI agents {#disc-ai-asset-inventory__section_deactivate}

Deactivate a managed AI agent directly from its asset record using AI agent containment with
kill switch protocol. For more information, see [Deactivate a managed AI agent](https://www.servicenow.com/docs/Fu91DqHah4nXTwwvRkQcWA "Deactivate a managed AI agent directly from its asset record using kill switch protocol, even if the agent has no associated security event.").

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