Create and Configure an AI Agent

This page walks you through the process of creating a new AI agent. By defining its goals, tools, and inputs, you can automate complex tasks and decision-making within your Appian applications. You'll learn how to define an AI agent's goals, add tools, and configure its inputs and outputs.

For foundational concepts, see About AI Agents. For best practices, see Best Practices for Designing AI Agents.

Before you begin: Prepare your tools and actions

AI agents rely on existing Appian design objects—called tools—to access data, trigger processes, or retrieve context. There are two types of tools:

• Action tools: Process models that perform actions like creating or updating records.
• Knowledge tools: Design objects that provide data or context, such as record types, expression rules, or documents.

To ensure your AI agent runs smoothly, make sure the following are ready before you start building an AI agent.

1. Prepare process models for action tools

If your AI agent will perform actions (for example, create or update records), you'll need at least one process model configured as an action tool.

• Use a clear, focused process that performs a single task without calling child processes.
• Include a record type input configured with a specific record type (not a process variable) if the AI agent needs to write to records.
• Add a Write Records node to the process model when the AI agent must create or update data.
• Avoid using multiple Write Records nodes for different record types in one process model.
• If you're using DocCenter, prepare a process model that calls the AIDC extraction process. You may need a lookup rule to find the appropriate extraction model key. You cannot add an AI skill directly as a tool.
• Avoid overlapping, similarly-named tools as this can confuse the AI agent.

2. Prepare record types, rules, or documents

If your AI agent will retrieve or reference data, prepare knowledge tools that provide structured or contextual information:

• Record types: The AI agent can only query one record type at a time. Related or aggregated queries must be handled in an expression rule.
• Expression rules: Create expression rules to store custom queries or logic.
• Documents and Folders: Upload supported text-based files (.pdf, .docx, .csv, .txt, etc.) to Appian. For guidance on choosing the right document strategy for your use case, see Working with Documents in AI Agents.

3. Check access and naming

Ensure your AI agent can access its tools and that naming conventions support clear interpretation:

• Verify that the initiator of the AI agent has at least Viewer permission to all connected tools and their underlying objects.
• Use clear, descriptive tool names and input labels. For example, use budgetRequestRecord instead of record.
• Search for existing design objects before creating new tools to avoid duplicates.

4. Keep it simple

Start small by assigning only the tools the AI agent truly needs. Most AI agents perform best with fewer than 15 tools. Once you've tested and confirmed your AI agent works well, you can always add more tools later.

AI agents excel at cross-system orchestration. If your use case requires gathering data from multiple sources (CRM, support system, analytics platform) and taking action based on the combined context, AI agents can handle this complexity more effectively than traditional process models with complex branching logic.

Next: Create and configure an AI agent to define its goals, add tools, and set up inputs and outputs.

For more detail on tool behavior and limitations, see AI Agent Reference.

Create an AI agent

Create an AI agent that automates processes based on your instructions. To speed up configuration, you can add existing tools or build new ones directly during setup.

To add a new AI agent:

1. In the Build view, click NEW > AI Agent.
   

2. Configure the following properties:

   Property	Description
   Name	Enter a name that follows the recommended naming standard.
   Description	(Optional) Enter a brief description. This description is only used to help you identify what this AI agent does.

3. Enter Goals and Instructions that give the AI agent detailed guidance to help it perform its work.

   Tip:  

   • Be clear and specific.
   • Describe steps or conditions the AI agent should follow.
   • Use plain language to ensure the AI agent understands the task.
4. Click ADD TOOL. The Add Tool screen appears.
   

   Scroll or drag to pan · ⌘+/⌘− to zoom · Esc to close

5. Select the design object you want the tool to use. This links the tool to the specific object the AI agent will access. The object's metadata automatically appears below the Action Tools section. You can navigate directly from a tool's configuration to its underlying design object by clicking the object's name.
   

   Scroll or drag to pan · ⌘+/⌘− to zoom · Esc to close

6. Click Create.

7. Repeat steps 4-6 to add multiple tools to the same AI agent.

   You are adding tools to a single AI agent, not creating separate AI agents for each tool. However, avoid assigning too many tools to your AI agent, as this can impact performance.

8. (Optional) Click ADD to define Inputs and Outputs. Configure the following properties:
   • Enter a Name and Description.
   • Search for and select the data type. Data types can be Text, Integer, Decimal, Boolean, Date, Datetime, Document, Folder, Record Type, CDT, Map, User, and Group.
   • (Optional) Select the Is Required checkbox.

     Tip:  Mark an input or output as required if the AI agent needs it to start the task or continue the workflow.

   • Click OK.
9. Click SAVE AGENT.

Next steps

After creating your AI agent, you can:

• Test your AI agent using the guidance in Test and Monitor AI Agents
• Integrate it into your applications by using it in process models
• Deploy it to other environments using Deploy AI Agents Between Environments

For troubleshooting common issues, see Troubleshooting AI Agents.

Feedback