Workflow recipe: Using an AI agent to collect customer info and immediately escalate to a human agent


When a customer reaches out for support on a messaging channel, you can configure an AI agent to collect their information and immediately escalate the conversation to a human agent. You might choose to do this if you prefer to provide your customers with human support, rather than letting the AI agentrespond with AI-generated replies.


What's my plan?







All Suites

Team, Growth, Professional, Enterprise, or Enterprise Plus










Support

Team, Professional, or Enterprise











The functionality described in this article is being rolled
out to all Suite and Support plans from May 11 through June 12, 2026. You may not
see this functionality in your account yet. See this announcement for details.




Note: If you previously configured a default messaging response on your messaging channel,
follow the instructions in this article to implement the same functionality using an
AI agent.

When a customer reaches out for support on a messaging channel, you can configure an AI
agent to collect their information and immediately escalate the conversation to a human
agent. You might choose to do this if you prefer to provide your customers with human
support, rather than letting the AI agent respond with AI-generated replies.
This article contains the following topics:

Understanding the workflow
Step 1: Create an AI agent
Step 2: Create an action to check the customer’s authentication status
Step 3: Create a form template to collect the customer’s information
Step 4: Set your business hours in your AI agent
Step 5: Edit the welcome reply
Step 6: Test, activate, and validate



Understanding the workflow

Even if you want human agents to provide support to your customers, you can still
benefit from an AI agent. You can configure an AI agent to:


Greet customers: Every time a customer begins a conversation with your AI
agent in the Web Widget, the AI agent’s first response is the welcome message
you configure.

Collect information: The AI agent presents the customer with a form to be
filled out. You can configure this form to collect whatever information your
human agents will need to solve the customer’s request, such as details about
the issue or the customer’s contact information. This saves your human agents
time because they already have the necessary information to act on customer
requests by the time the requests reach them.

Escalate requests: The AI agent tells the customer that their request is
being sent to your support team. Behind the scenes, human agents are notified
that a support request has been received, and they can accept the request and
begin responding to the conversation.

Optionally, you can also configure the AI agent to behave differently depending on:


Your business hours:
During business hours, the AI agent can escalate the conversation to a
human agent on a messaging channel, where the agent can immediately
begin conversing with the customer.
Outside of business hours, the AI agent can collect the customer’s
information and escalate the request as an email ticket to your support
team.



Customer authentication status:
If the customer is authenticated, the AI agent won't collect the email
and name in the form. However, any other information that needs to be
collected can be.
If the customer isn’t authenticated, you can collect their email and
name in addition to any other information that needs to be collected.




This workflow utilizes the AI agent welcome reply, which is a default system reply that’s sent to the customer at the
beginning of a conversation. You’ll edit the dialogue associated with this reply to
contain the AI agent messages, actions, and forms needed to carry out the workflow
described above.


Note: If you set up an AI agent as described in this article,
this workflow does not consume paid automated resolutions. However,
automated resolutions can be consumed if you add additional configuration to the
AI agent, like connecting knowledge sources or creating use cases.




Step 1: Create an AI agent

First, you need to create the AI agent that converses with customers on your
messaging channel.
To create an AI agent

Follow the step-by-step instructions in Creating an AI agent to automatically resolve
customer issues.



Important: After you create your AI agent, disconnect the help center that was
automatically connected during the creation flow, and make sure you did not add
an external knowledge source. Also, make sure you do not create any use
cases. AI agents with connected knowledge sources and use cases can incur paid
automated resolutions.




Step 2: Create an action to check the customer’s authentication status

Next, create an action that checks the customer’s authentication status.
This information is available through the Sunshine Conversations app user object. The Get user CRM action gets the user’s
authentication status and saves it as a session parameter for the conversation.


Tip: For more information on how authentication
works, see Understanding user authentication for
messaging.

To create an action to check authentication status


In the AI agents workspace, select the AI agent you want to work
with.
Click
Content in the sidebar, then select Actions.
Click Create action.
In Name, enter a descriptive name for the action, such as Get
customer authentication status, name, and email.
In Target, select Sunshine Conversations.
In Task, select Get user.
In Field to retrieve, select authenticated.
In Save as parameter, enter the name of the parameter the value
should be saved as, such as authenticated.
Click Get another field and add parameter information for the
customer’s name:

Field to retrieve: givenName

Save as parameter: name


Click Get another field and add parameter information for the customer’s
email:

Field to retrieve: email

Save as parameter: email


Click Create. When you add this action in the welcome reply
dialogue (described below), the AI agent will fetch the indicated fields
from the app user object and save it as session parameters.



Tip: You can find additional optional
configuration for this action in the developer documentation.








Step 3: Create a form template to collect the customer’s information

Create a form template to specify which details to collect from the customer.
Based on their authentication status, the form collects the missing details. For
example, an authenticated user means their email is known to be authenticated in the
first place, so there’s no need for the form to collect the email again.
You should create two different form templates, one for authenticated customers and
one for unauthenticated customers. The form for authenticated customers doesn’t need
to include fields for Name and Email, since those details are already known due to
the authentication, but it should include fields for any other details you want to
collect. The form for unauthenticated customers should include Name and Email, in
addition to any other details you want to collect.
Which form template is shown to the customer depends on their authentication status.
You’ll configure this when you edit the welcome reply’s dialogue, described later in
this article.
To create a form template

Follow the step-by-step instructions in Creating a form template.




Step 4: Set your business hours in your AI agent

Set operating hours in your AI agent that mirror your business hours. Operating hours
define the working hours for your human agents.

To set your business hours


Follow the step-by-step instructions in Setting operating hours.




Step 5: Edit the welcome reply

The last setup step is to edit the dialogue associated with the welcome reply. The
dialogue contains the AI agent messages, actions, and forms needed to carry out the
workflow described above.
To edit the welcome reply


In the AI agents workspace, select the AI agent you want to work
with.
Click
Content in the sidebar, then select Use cases.
In the list of use cases, select Welcome reply.
Select the reply for the language you want to edit.
Click Edit dialogue. The dialogue builder opens.

(Optional) If you have separate default messaging responses for different
channels, click the plus (+) icon above the initial AI agent message block,
select Conditional, and enter integrationID in the empty
field.
In the child Parameter block, select is in the first field
and enter your first channel’s integration ID in the second field.
Click the plus (+) icon under the Conditional field to add and
configure additional Parameter blocks as needed for your other
channels.
Tip: You can make it
easier to see in the conversation logs
which channel’s dialogue branch was followed during a
conversation. First, create an action that
adds a label with the channel’s name. Then, add the action to each
parameter block.



Click the plus (+) icon above the initial AI agent message block and select
Availability.
In the Availability block, click Select rule and select the operating
hours rule you created above.
Under the Open block:
Click the plus (+) icon, select AI agent message, and enter
what the AI agent should say to the customer at the beginning of a
conversation when human agents are available.
Click the plus (+) icon underneath the block you just added, select
Conditional, and enter email in the empty field.
In the Parameter block, select Is (boolean) in the first
field and True in the second field.
Click the plus (+) icon underneath the block you just added, select
AI agent message, and enter the template shorthand for
the authenticated users form. For help finding the template
shorthand, see Adding a structured message
template in a dialogue.

Click the plus (+) icon underneath the block you just added, and
select Escalation.
In the first field, enter what the AI agent should say to
the customer when escalating them to a human agent.
In the second field, select Forward to an agent.



Click the plus (+) icon underneath the Fallback block, select AI
agent message, and enter the template shorthand for the
unauthenticated users form.
Click the link icon underneath the Fallback block and then select
the Escalation block to link the two blocks together.


Repeat step 9 for the Closed block to reflect what should happen when human
agents aren’t available. At this point, your dialogue should look
similar to the following:


Click Publish.


For additional help with the dialogue builder, see Creating dialogues to define scripted conversation flows for AI
agents.



Step 6: Test, activate, and validate

After your AI agent is configured as you want, you should perform three last tasks:

Test the AI agent before making it live for customers. See Testing conversation flows in AI
agents.

Activate the AI agent on the channels you want it to work on. See Activating and managing AI agents.


Validate that AI agent conversations are appearing in the conversations
log. See Reviewing conversation logs for AI
agents.




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