---
title: Create AI model assets
description: Create AI assets to track and manage the life cycles of your AI models.
locale: en-US
canonical_url: https://www.servicenow.com/docs/r/australia/intelligent-experiences/ai-control-tower/create-ai-model-assets.html
release: australia
product: AI Control Tower
classification: ai-control-tower
topic_type: task
last_updated: "2026-03-12"
reading_time_minutes: 4
keywords: [Now Assist, generative AI]
breadcrumb: [Creating AI assets, Use, AI Control Tower \(legacy\), Enable AI experiences]
---

# Create AI model assets

Create AI assets to track and manage the life cycles of your AI models.

## Before you begin

Role required: sn\_ai\_governance\_ai\_steward or sn\_ai\_asset\_mgmt.ai\_asset\_owner

## About this task

An AI model is a program that is trained to process data and generate outputs, such as predictions, content, recommendations, and decisions, without human intervention. You can use an AI model to perform a specific task, such as image recognition, data classification, or price prediction.

## Procedure

1.  Navigate to **Workspaces** > **AI Control Tower**.

2.  From the AI Control Tower, open the AI assets view.

3.  From the navigation menu of the AI assets view, navigate to either **AI asset inventory - Managed** > **AI Models** or **AI asset inventory - Unmanaged** > **AI Models**.

4.  Select **Add AI model**.

5.  In the Details section of the Add AI model form, fill in the fields.

<table id="table_osx_kg5_bfc"><thead><tr><th>

Field

</th><th>

Description

</th></tr></thead><tbody><tr><td>

Name

</td><td>

Name of the AI model.

</td></tr><tr><td>

Provider

</td><td>

People or organization that developed the AI model.

</td></tr><tr><td>

Version

</td><td>

Version of the AI model.

</td></tr><tr><td>

Supported languages

</td><td>

Languages that are supported by the AI model.

</td></tr><tr><td>

Deployment guidelines

</td><td>

Guidelines or instructions on how to deploy the AI model.

</td></tr><tr><td>

Training procedure

</td><td>

Method that you’re using to train the AI model.

</td></tr><tr><td>

Context window

</td><td>

Maximum number of tokens that the AI model can process and recall when generating outputs.

</td></tr><tr><td>

Model size in MB

</td><td>

Size of the AI model in megabytes \(MB\).

</td></tr><tr><td>

Model parameters info

</td><td>

Internal variables that the AI model learns during training to process data and generate outputs.

</td></tr><tr><td>

Description

</td><td>

Brief description of the AI model.

</td></tr><tr><td>

Managed by

</td><td>

User who is assigned to manage the AI model. This field is automatically set to the user who creates the AI model asset.**Note:** This field is editable only if you have the AI steward \(sn\_ai\_governance\_ai\_steward\) role. If you have the AI asset owner \(sn\_ai\_asset\_mgmt.ai\_asset\_owner\) role, this field is read-only.

</td></tr><tr><td>

State

</td><td>

State of the AI model. The options are **Draft** and **Deployed**.

</td></tr><tr><td>

License details

</td><td>

License that you are using for the AI model.

</td></tr><tr><td>

Base model

</td><td>

Base model, also known as a foundation model or pre-trained model, that the AI model was built from.

</td></tr><tr><td>

Department

</td><td>

Department that the AI model belongs to.

</td></tr><tr><td>

Supported locations

</td><td>

Locations in which the AI model is supported.

</td></tr><tr><td>

Model card

</td><td>

Brief document that describes important information about the AI model, including the context, intended use, training data, and limitations of the model.

</td></tr><tr><td>

Model weights info

</td><td>

Numerical parameters that define how the AI model learns during training so that it can generate more desired outputs.

</td></tr><tr><td>

Required infrastructure

</td><td>

Integrated software and hardware components that are required for developing, deploying, and managing the AI model.

</td></tr><tr><td>

Evaluation metrics report

</td><td>

Report that provides data for the metrics that you’re using to evaluate the effectiveness of the AI model.

</td></tr></tbody>
</table>6.  Select **Next**.

7.  In the Related assets section of the Add AI model form, associate the AI model with related datasets.

    Related datasets include any collections of data that can help test or train the AI model.

    1.  Depending on the type of related dataset that you want associate the AI model with, select one of the following options from the asset type menu:

        -   To associate the AI model with a dataset that can help test it, select **Evaluation datasets**.
        -   To associate the AI model with a dataset that can help train it, select **Training datasets**.
        The corresponding asset list opens.

    2.  Associate the AI model with the related dataset.

        Depending on if the related dataset is currently available in your asset inventory, proceed with one of the following options:

        -   To associate the AI model with a related dataset that is currently available, use the following steps:

            1.  Select the Add from inventory drop-down menu on the header of the corresponding asset list.
            2.  Select **Add from inventory**.
            3.  In the Add from inventory dialog box, select the check box for the related dataset that you want to associate the AI model with.

                **Note:** If you want to associate the AI model with multiple related datasets, select the check box for each dataset.

            4.  Select **Add**.
            The dialog box closes and the selected dataset appears in the corresponding asset list.

        -   To associate the AI model with a related dataset that is not currently available, use the following steps:

            1.  Select the Add from inventory drop-down menu on the header of the corresponding asset list.
            2.  Select **Create**.
            3.  Create the dataset by following the proceeding steps in [Create dataset assets](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/intelligent-experiences/ai-control-tower/create-dataset-assets.md).
            The new dataset appears in the corresponding asset list.

8.  Select **Submit for review**.

    **Note:** If you aren’t ready to submit the AI model for review, select **Save** instead. You can then edit it and submit it for review later by navigating to **AI assets** &gt; **Lifecycle** &gt; **Onboard** and then selecting the AI model from the list. When the AI asset record opens, continue editing the AI model details.


## Result

The AI model is added to your AI asset inventory. It automatically enters the onboard stage of the AI asset life cycle and is updated with a Lifecycle status of AI steward review.

## What to do next

Users who are assigned the AI steward \(sn\_ai\_governance.ai\_steward\) role can start the review process to begin tracking and managing the life cycle of the AI model. For detailed instructions, see [Complete AI asset lifecycle](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/intelligent-experiences/ai-control-tower/complete-ai-asset-lifecycle.md).

**Parent Topic:**[Creating AI assets](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/intelligent-experiences/ai-control-tower/creating-ai-assets.md)