> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://help.sigmacomputing.com/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://help.sigmacomputing.com/_mcp/server.

# Create AI columns (Beta)

This documentation describes one or more public beta features that are in development. Beta features are subject to quick, iterative changes; therefore the current user experience in the Sigma service can differ from the information provided in this page.

This page should not be considered official published documentation until Sigma removes this notice and the beta flag on the corresponding feature(s) in the Sigma service. For the full beta feature disclaimer, see [Beta features](/docs/sigma-product-releases#beta-features).

Create AI columns to enrich your data using natural language prompts. AI columns allow you to construct dynamic prompts that reference specific table columns, preview the resulting JSON or text output on a subset of your data, and then apply the prompt to the entire table.

AI columns can perform tasks like:

* Enrich data with additional context or details
* Generate summaries of text data
* Classify data into categories
* Translate text into different languages

Depending on the connection you are creating an AI column on, AI columns use the Snowflake's <a href="https://docs.snowflake.com/en/sql-reference/functions/ai_complete" target="_blank">AI\_COMPLETE</a> function or the Databricks <a href="https://docs.databricks.com/aws/en/sql/language-manual/functions/ai_query" target="_blank">ai\_query</a> functionto generate responses.

This document covers how to [create](#create-an-ai-column) AI columns, [edit](#edit-an-ai-column) AI columns, and some example [AI column prompts](#example-ai-column-prompts).

You can also see [AI column usage statistics for your organization](#view-ai-column-usage-information), as well as [set usage limits for AI columns](/docs/configure-ai-column-token-limit).

The use of AI features is subject to the following [disclaimer](/docs/notice-for-enabling-ai-enabled-features-in-sigma).

## System and user requirements

The ability to use AI columns requires the following:

* An AI provider must be configured for your organization. See [Configure an AI provider](/docs/configure-ai-features-for-your-organization#configure-an-ai-provider).
* You must be assigned an account type with the **Create AI column** permission enabled. See [Account types](/docs/account-type-and-license-overview).
* You must be the workbook owner or be granted **Can edit** [access to the workbook](/docs/folder-and-document-permissions).
* You must have a Snowflake or Databricks connection with write access enabled. See [Connect to Snowflake](/docs/connect-to-snowflake) and [Configure write access](/docs/connect-to-snowflake#configure-write-access), or [Connect to Databricks](/docs/connect-to-databricks) and [Configure write access](/docs/connect-to-databricks#configure-write-access).
* If you are using a Snowflake connection, the user associated with the Snowflake connection must have:
  * The `CORTEX_USER` or `AI_FUNCTIONS_USER` database role. See the Snowflake documentation on <a href="https://docs.snowflake.com/en/user-guide/snowflake-cortex/aisql-privileges-and-access#cortex_user-database-role" target="_blank">CORTEX\_USER database role</a> and <a href="https://docs.snowflake.com/en/user-guide/snowflake-cortex/aisql-privileges-and-access#ai_functions_user-database-role" target="_blank">AI\_FUNCTIONS\_USER database role</a>.
  * The USE AI FUNCTIONS privilege. See the Snowflake documentation on <a href="https://docs.snowflake.com/en/user-guide/snowflake-cortex/aisql-privileges-and-access#use-ai-functions-on-the-account-privilege" target="_blank">USE AI FUNCTIONS account privilege</a>.
* If you are using a Databricks connection, the connection must meet the following requirements:
  * The connection cannot use Databricks SQL Classic (the `ai_query` function is not supported by the Classic tier).
  * If connected to Databricks SQL Pro, you must enable [AWS PrivateLink](https://docs.databricks.com/aws/en/security/network/classic/privatelink) to use the `ai_query` function.
  * Databricks Runtime 15.4 LTS or above is recommended; using 15.3 or below can result in slower performance.
  * For batch interface scenarios, Databricks Runtime 15.4 LTS or above is required.
  * Your workspace must be in a supported [Model Serving region](https://docs.databricks.com/aws/en/machine-learning/model-serving/model-serving-limits#regions).
  For more information, see the [ai\_query function reference](https://docs.databricks.com/aws/en/sql/language-manual/functions/ai_query) in the Databricks documentation.

## Limitations

* AI columns are only supported for Snowflake and Databricks connections.
* AI column prompts cannot reference another AI column.
* AI columns cannot be used with actions.
* AI columns cannot be used in input tables.
* If you [swap the data source](/docs/change-the-data-source-for-a-workbook-data-model-or-element#change-the-data-source-for-an-element) for a table with an AI column, you need to create the AI column again.
* If you materialize a workbook with an AI column that has not finished loading, the materialization will not fail. The materialization will return `Null` for the AI column rows that have not finished loading.
* If you are creating an AI column on a Databricks connection, the following is not supported:
  * Configuring the **Response format** of the column output.
  * Usage information on AI columns in the [Usage dashboard](/docs/usage-overview).

## Create an AI column

To create a new AI column:

1. From the table you want to add the AI column to, select the down arrow <img src="https://sigma-docs-screenshots.s3.us-west-2.amazonaws.com/Icons/caret.svg" alt="" /> to open the column menu.

2. Select **Add column via** > **AI column...**.

3. If you have have any filters, grouping, or sorting on your table, you are prompted to select one of the following options to add your AI column to:
   * **A new child table based on the current table**: The AI column is added to a new child element that is based on the current table. The child table's data is a subset of the parent table, and only contains rows that were not excluded from the parent table (e.g. through filters). Selecting this option can improve query speed and reduce compute costs in the data platform.
   * **This table**: The AI column is added to the currently selected table, and generates output for all rows in the source table, including rows that may be filtered out.

After selecting an option, select **Next**.

4. Configure your column in the **AI column generation** modal:
   1. **Column name**: Enter a name for your AI column.
   2. **LLM model**: Select a model from the dropdown.
   3. **Prompt**: Enter your prompt. To reference an existing column in the table, press the **=** key on your keyboard, then search for and select the column you want to reference. You must reference at least one column in your prompt. See [Example AI column prompts](#example-ai-column-prompts).
   4. (optional) Turn on the **Response format** toggle to format the AI column response as JSON. Enter the following information for each field you want to include in the JSON response:
      * **Name**: Enter a name for the field.
      * **Type**: Select a data type from the dropdown.
      * **Description**: Provide additional context for the LLM on the field's contents and how to format the response. At least one field must be added if **Response format** is enabled.
   5. Select **Preview** to preview the output of the first 100 rows of your AI column.
   6. Select **Create**. The AI column appears in your workbook, either as part of the existing table, or as part of a new child element.

## Edit an AI column

To edit an existing AI column:

1. From the AI column, select the down arrow <img src="https://sigma-docs-screenshots.s3.us-west-2.amazonaws.com/Icons/caret.svg" alt="" /> to open the column menu.
2. Select **Edit AI column...**.
3. Make your changes to the AI column configuration.
4. Select **Update**.

## Example AI column prompts

For example, given a large table of sales representative call logs with information about the call participants, duration, and transcripts, you can create an AI column to:

* Summarize lengthy transcripts
  * Example prompt: "Write a brief executive summary of each call, with the following information included in the first sentence: the \[Account Name], \[Date] and \[Call Duration]. Use the \[Full Transcript] to summarize what went well, and any potential risks or blockers, in 2-3 sentences."

* Classify calls into categories
  * Example prompt: "Classify the primary conversation topic for each row's \[Full Transcript] into one of the following categories: Discovery, Demo, Negotiation, Renewal, Other. Return only the category name."

* Extract information from unstructured text
  * Example prompt: "Extract the any competitor company names mentioned by \[External Participants] in the \[External Speaker Transcript] and provide a 1-sentence summary for why they were mentioned."

## Set AI column token usage limits

Sigma admins can set AI column usage token limits for individual connections. If no token limit is set, the default limit is 10 million tokens per connection per month. See [Configure token usage limits for AI columns](/docs/configure-ai-features-for-your-organization#configure-ai-column-token-limit) for instructions on how to set token limits.

## View AI column usage information

Sigma admins can view AI column usage information in Usage dashboards. AI column usage information is only supported for Snowflake connections. See [Usage overview](/docs/usage-overview) for more information.