---
sourceDocument: Brazil Conversational Interfaces
sourceDocumentLink: https://www.servicenow.com/docs/r/conversational-interfaces
Release :
- brazil
ft:locale :
- en-US
ft:publication_title :
- Brazil Conversational Interfaces
ft:clusterId :
- convint
bundleId :
- convint
workflow :
- Platform
---
# Configure agentic conversations
# Configuring agentic conversations in Virtual Agent {#ariaid-title1}
Release version: Brazil
Updated September 10, 2026
 4 minutes to read
Summarize
 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 Configuring agentic conversations in Virtual Agent
The Virtual Agent in ServiceNow Brazil release offers advanced agentic conversations that enable it to reason, plan, and execute user requests by orchestrating multiple AI agents, skills, virtual agent topics, conversational actions, knowledge base (KB) articles, and other supported resources.
This capability allows the assistant to handle complex, multi-part user queries by breaking them down into discrete tasks and executing them sequentially or in parallel as needed.
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## Key Features
* **Multi-agent orchestration:** The Virtual Agent automatically selects specific agents or falls back to a Search Agent based on the assistant's scope to fulfill user tasks and subtasks.
* **Automatic skill execution:** Discovered skills are executed automatically to complete user requests without requiring manual intervention.
* **Handling complex queries:** The system can parse multi-part utterances involving combinations of skills, agents, and QnA, breaking them into actionable steps with dependencies and context awareness.
* **Interrupt and restart conversations:** Users can halt ongoing queries mid-execution via an interrupt icon and restart conversations with new queries.
* **Error handling and fallbacks:** The Virtual Agent provides user-friendly messages and options when it cannot understand requests, encounters system errors, or session timeouts occur. Fallbacks include connecting to live agents, creating support requests, or viewing office hours based on configuration.
* **Session timeout management:** Warnings are issued before session inactivity timeouts, allowing users to continue or restart conversations seamlessly.
* **Task failure notifications:** For multi-step tasks, if any step fails, the Virtual Agent informs the user and offers fallback options configured in the system.
## Practical Outcomes for ServiceNow Customers
* Enhanced user experience with intelligent handling of complex and multi-intent queries through agentic conversation orchestration.
* Improved task automation by enabling the Virtual Agent to autonomously execute multiple related tasks sequentially, reducing manual effort.
* Greater reliability with error management and fallback options that keep conversations productive even when issues arise.
* Flexibility for users to interrupt and restart conversations, helping maintain control over interactions.
* Accurate and context-aware responses by leveraging multiple knowledge sources, agents, and skills to address diverse user needs.
**Note:** It is important to review AI-generated responses for accuracy before taking any action to ensure correctness.
When you query a Virtual Agent, it reasons, plans, and executes across a wide variety of options. The Virtual Agent can use AI agents, virtual agent topics, conversational actions and subflows, catalogs, KB articles, custom skills, and any ServiceNow Otto for Virtual Agent supported skills to help you.
* If specific agents are available for the assistant to perform user tasks or subtasks, they are used.
* If no specific agent is available for the task or subtask, the system automatically employs the Search Agent to discover answers or appropriate skills within the system. This is based on the assistant's scope.
* If skill execution is required, the system automatically executes the discovered skills.
* The system plans and orchestrates execution among multiple agents, skills, and QnA to accomplish complex tasks.
{#agentic-conversations-vad__ul_gjw_vfp_hfc}
Note:
When a Virtual Agent conversation is triggered, any updates or comments in the record's work notes display as the AI agent rather than the user who initiated the conversation.
## Examples of AI agent behavior for user utterances {#agentic-conversations-vad__section_gs2_lqp_hfc}
The examples will consider the following available example resources in the system:{#agentic-conversations-vad__table_llk_4dq_hfc__entry__3}
| Agents | Skills/Topics | KB Articles |
|-|-|-|
| Check IT Ticket status agent Email Agent Meeting scheduling Agent | Order coffee Order food Order laptop Order accessories | Spam ESPP policy |
[ ]
{#agentic-conversations-vad__table_llk_4dq_hfc}
Scenario 1: Multiple questions from KB articles
Utterance: How do I avoid spam? How do I detect it?
* Non-agentic response: Produces a single mixed answer.
* Agentic response: Breaks it into two questions and provides a better answer for each one of them.
{#agentic-conversations-vad__ul_rhj_b1q_hfc}
Scenario 2: Multiple skills with slot filling
Utterance: Hey, order a coffee for me, preferably dark roast and something to eat, maybe a pizza?
* Non-agentic response: Produces a single answer. Mostly listing all matching available skills. No auto-execution since it matched multiple skills.
* Agentic response: Breaks it into two distinct tasks, order coffee and order food/pizza. Executes one after another, completing the entire user request.
{#agentic-conversations-vad__ul_fmk_mbq_hfc}
Scenario 3: Complex utterance with a combination of skills, agents, and QnA
Utterance: I am going on PTO tomorrow. Get my expense report and my IT ticket status. Send a summary of the expense report to John Jacob and the details on ticket status to Robert Williams, informing them of my PTO and requesting them to work on them.
* Non-agentic response: Produces a single answer. It lists all matching available skills. No auto-execution will take place since it matched multiple skills.
* Agentic response: Breaks it into multiple distinct tasks, reasons and plans, understands the dependencies, and executes one after another, completing the entire user request using output from prior actions as context as needed.
{#agentic-conversations-vad__ul_rm1_g2q_hfc}
Scenario 4: Complex utterance with a combination of QnA (KB) and agent
Utterance: What is the maximum contribution amount for espp? Send an email to Robert with the details.
* Non-agentic response: Produces a single answer and doesn't complete or even suggest the second action since there's no corresponding skill.
* Agentic response: Understands the two separate intents and executes them in sequence while using the output from the first intent to fulfill the second intent.
{#agentic-conversations-vad__ul_iyp_2sq_hfc}
## Halting and restarting agentic conversations {#agentic-conversations-vad__section_slj_3zp_sfc}
If you want to stop an agentic conversation mid-query, hover over the send icon ![Send icon.]() while the agent is researching a query. The icon becomes an interrupt flow icon ![Interrupt flow icon.](). Select the icon and the conversation stops. A message appears: The current conversation has been stopped, but you can begin again. Enter a new query to restart the agentic conversation.
## Error handling and fallback options {#agentic-conversations-vad__section_hwh_kys_k3c}
When the AI agent can't understand a request, encounters a system error, or a session becomes inactive, it displays a message and presents options to help you continue.
* When ServiceNow Otto can't find an answer, it will provide options based on how the assistant was configured. Options may include:
* Requesting a live agent
* Creating a support request
* Viewing office hours
{#agentic-conversations-vad__ul_ztc_3rt_k3c}
For example, if you ask about a topic the AI agent can't find information on, you might see a message such as: "I can't find anything on that directly but I can help you explore other options." Select one of the
displayed options to continue.
* Session timeout due to inactivity:If you stop responding during a conversation, the AI agent waits for a set period before ending the session. When a session is about to time out, you will receive a warning message. For
example: "Looks like you've left this conversation. Would you like to keep going?". If you want to continue, respond to resume the conversation.
If there is no response to the warning, the session ends with a session end
message. For example, "Our chat has timed out due to inactivity. Just start a new conversation whenever you're ready. I'll be here to help!". You can start a new chat to continue getting help.
* Technical errors and system timeout:If the AI agent encounters a backend error or can't complete a request due to a technical issue, it displays a message and presents fallback options. For example: "It looks like I'm
having trouble completing your request right now because of a technical failure. But I can help you explore other options." You can select one of the available fallback options to continue.
* Errors during agentic tasks:When you ask the AI agent to complete a multi-step task on your behalf, it plans and carries out the steps automatically. If a step in the plan can't be completed, it lets you know and offers
fallback options so you can decide how to proceed.
For example, if the AI agent is creating an expense report and encounters a problem, it displays a message such as: "Unfortunately that didn't work. But I can help you
explore other options." The fallback options available depend on your configuration.
{#agentic-conversations-vad__ul_cfg_qrt_k3c}
Note:
Review AI generated responses for accuracy before taking action.