---
title: AI steps
description: Learn about AI steps for integrating AI capabilities into your workflows.
url: https://www.elastic.co/elastic/docs-builder/docs/3016/explore-analyze/workflows/steps/ai-steps
applies_to:
  - Elastic Cloud Serverless: Preview
  - Elastic Stack: Preview since 9.3
---

# AI steps
AI steps allow your workflows to interact with AI services and Elastic AI agents. Use them to analyze data, generate insights, make context-aware decisions, and automate intelligent responses.
The following AI step types are available:
- **Prompt** (`ai.prompt`): Send prompts to [AI connectors](https://docs-v3-preview.elastic.dev/elastic/docs-builder/docs/3016/reference/kibana/connectors-kibana/gen-ai-connectors) (such as OpenAI or Google Gemini)
- **Agent** (`ai.agent`): Invoke Elastic AI agents built in [Agent Builder](https://www.elastic.co/elastic/docs-builder/docs/3016/explore-analyze/ai-features/elastic-agent-builder)


## Prompt

The `ai.prompt` step sends a prompt to an AI connector and returns the response. Use this step to:
- Summarize or interpret data
- Extract insights from unstructured text
- Make context-aware decisions based on data in your workflow
- Generate structured output based on a defined schema

To use a specific AI connector, configure it through Kibana's [Connectors framework](https://www.elastic.co/elastic/docs-builder/docs/3016/deploy-manage/manage-connectors). If you don't configure a connector, this step uses the connector selected as the **Default AI Connector** in [GenAI Settings](/elastic/docs-builder/docs/3016/explore-analyze/ai-features/manage-access-to-ai-assistant#the-genai-settings-page). [Elastic Managed LLMs](https://docs-v3-preview.elastic.dev/elastic/docs-builder/docs/3016/reference/kibana/connectors-kibana/elastic-managed-llm) are available out of the box and require no setup.
<note applies-to="Self-managed Elastic deployments: Generally available">
  On self-managed deployments, you must configure an AI connector before using this step.
</note>


### Parameters

Use the following parameters in the `with` block to configure the step:

| Parameter     | Type   | Required | Description                                                                                                                                                                                                |
|---------------|--------|----------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| `prompt`      | string | Yes      | The prompt text to send to the AI connector. Can include template variables to reference data from previous steps, inputs, or constants.                                                                   |
| `connectorId` | string | No       | The ID or name of the AI connector to use. If omitted, uses the [default AI connector](/elastic/docs-builder/docs/3016/explore-analyze/ai-features/manage-access-to-ai-assistant#the-genai-settings-page). |
| `schema`      | object | No       | A JSON Schema object that defines the structure of the expected response. When provided, the AI connector returns structured data matching the schema.                                                     |
| `temperature` | number | No       | Controls randomness in the AI response. Accepts values from `0` to `1` (for example, `0.3`). Lower values produce more deterministic responses; higher values produce more random responses.               |


### Output structure

The `ai.prompt` step produces output in the following structure:
```yaml
content: <response> 
response_metadata: <metadata> 
```

Reference the output in subsequent steps using `steps.<step_name>.output.content`.

### Example: Analyze an alert

This example sends an alert to an AI connector for severity analysis.
```yaml
steps:
  - name: analyze_alert
    type: ai.prompt
    with:
      prompt: "Analyze this security alert and determine its severity: {{ event | json }}"
      connectorId: "my-openai-connector"
```


### Example: Structured output with schema

This example uses `schema` to return a structured response with specific fields and types.
```yaml
steps:
  - name: categorize_alert
    type: ai.prompt
    with:
      prompt: "Analyze this alert and categorize it: {{ event | json }}"
      connectorId: "security-analysis-connector"
      schema:
        type: object
        properties:
          severity:
            type: string
            enum: [low, medium, high, critical]
          category:
            type: string
          requires_human_review:
            type: boolean
      temperature: 0.3
```


## Agent

The `ai.agent` step invokes an Elastic AI agent built using Elastic Agent Builder. The agent processes the input message and returns a response, optionally using tools and maintaining conversation context. Use this step to invoke an agent as a "reasoning engine" that summarizes data, classifies events, or makes decisions before passing the results to the next step in your automation.
For detailed configuration options and examples, refer to [Work with AI agents in Elastic Workflows](/elastic/docs-builder/docs/3016/explore-analyze/ai-features/agent-builder/agents-and-workflows#use-the-ai.agent-step).