--- sourceDocument: Australia Conversational Interfaces sourceDocumentLink: https://www.servicenow.com/docs/r/australia/conversational-interfaces Release : - australia ft:locale : - en-US ft:publication_title : - Australia Conversational Interfaces ft:clusterId : - convint bundleId : - convint workflow : - Platform --- # AI agents in Virtual Agent topics # AI agents in Virtual Agent topics {#ariaid-title1} Release version: Australia Updated September 10, 2026 ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 2 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 AI agents in Virtual Agent topics AI agents in Virtual Agent topics enable you to automate specific tasks by integrating AI capabilities within your Virtual Agent conversations. These agents perform tasks passed to them from Virtual Agent topics, such as consolidating knowledge base article contents, enhancing the interaction and efficiency of your Virtual Agent deployments. Show full answer Show less ## Using AI Agents with the AI Connector Utility AI agents operate within the AI Connector utility accessible via Assistant Designer. This utility allows you to select an AI agent from available options and define specific tasks through input mappings. For example, selecting the "KB content consolidation AI agent" lets you retrieve and summarize knowledge base articles during a Virtual Agent chat. To assign a task, provide a value or script in the Task input mapping variable, such as `return KB00090;` to fetch and consolidate information from a particular knowledge base article. The AI agent then processes the task and returns results directly in the chat. ## Output and Execution Details Each AI agent execution generates a detailed execution plan that includes: * **Execution plan ID:** Identifier for the plan. * **Execution state:** Current status of the task. * **Objective:** Description of the intended task. * **State reason:** Explanation for the current state. * **Messages:** Communication logs during execution. * **Execution tasks:** List of individual tasks performed. * **Execution tools:** Tools utilized in the plan. All execution plans are stored in the `Execution Plan [snaiaexecutionplanlist]` table for tracking and auditing purposes. ## Practical Benefits for ServiceNow Customers * Streamlines complex tasks within Virtual Agent conversations by leveraging AI skills. * Enables dynamic, context-driven content retrieval and consolidation, improving self-service accuracy. * Provides transparency and traceability of AI agent operations through execution plans. * Facilitates easy configuration and task definition via the AI Connector utility without extensive coding. An AI agent custom skill performs a task that you pass to it from a Virtual Agent topic, such as consolidating the content of a knowledge base article. There may be AI agents installed with the Now Assist application that are not used in use cases. To learn how to see all agents that are available to you, see [Find AI agents](https://www.servicenow.com/docs/access?context=find-ai-agents&version=australia&pubname=australia-intelligent-experiences&ft:locale=en-US). An AI agent performs a task that you pass to it inside the AI Connector utility in Assistant Designer. For more information on the AI Connector utility, see [AI Connector utility](https://www.servicenow.com/docs/ou5i0k1cOIePY6OmkI9dCg "Use this utility to link generative AI to custom skills for added versatility in your Virtual Agent LLM (large language model) conversations."). For example, you can use the AI agent in the AI Connector utility to get all data on a knowledge base article. The AI agent provides the article if it is available or notifies you if it can't find it. The agent also provides data on the consolidation itself by way of its output mappings. To see which AI agents are installed on your instance, see [Find AI agents](https://www.servicenow.com/docs/access?context=find-ai-agents&version=australia&pubname=australia-intelligent-experiences&ft:locale=en-US). To use the AI agent, select it from the Skill type drop-down list in the AI Connector utility, then select the AI agent's type from the Select AI agent drop-down list. For example, to have the AI agent consolidate a knowledge base article, select KB content consolidation AI agent. Define the task for the AI agent by placing a value in the Task input mapping variable. You can define a condition, or enter a script or command. For example, enter `return KB00090;` to have the AI agent retrieve that knowledge base article and consolidate its information into a reply in the Virtual Agent chat. The AI agent's output mapping properties are automatically defined when you select the AI agent type. All output mappings are returned in the chat when the AI agent completes the task. {#ai-agent-custom-skill__table_orx_d4v_lfc__entry__2} | Variable | Description | |-|-| | Execution plan ID | ID number of the execution plan. | | Execution state | Current state of the execution plan. | | Objective | Intended task for the execution plan. | | State reason | Reason for the execution plan's current state. | | Messages | List of messages sent through the execution plan. | | Execution tasks | List of tasks in the execution plan. | | Execution tools | List of tools in the execution plan. | [Table 1. AI agent output mapping properties] {#ai-agent-custom-skill__table_orx_d4v_lfc} When the AI agent performs its job, it generates the full plan showing the input and output mappings. Each plan shows the objective, all tasks performed for the objective, and any messages sent or tools used in the plan. All plans are listed in the Execution Plan \[sn_aia_execution_plan_list\] table.