Using AI Agent Actions

While AI Agent is replying to a Contact, it can perform specific platform actions like assigning the conversation, closing it, or updating contact information. Understanding these actions helps you design AI Agents that handle conversations smoothly and logically.

This guide covers exactly how each action works, how to write effective instructions for them, and how to avoid common pitfalls like conflicts with your existing Workflows.

Why Actions Are Important

Your AI Agent’s replies help handle customer conversations smoothly. But often, replying alone isn’t enough—your Agent also needs to take clear next steps to move Leads across sales or support pipeline.

That’s exactly what Actions are for. They help your AI Agent move beyond just replying, ensuring conversations progress logically down the conversion funnel, customer details stay accurate, and teams always know who should handle each chat next.

By using the right actions, your AI Agent knows exactly what to do while replying—giving your team peace of mind and keeping your conversations organized and effective.

Timing & Action Behavior

• AI Agents always perform actions before generating a reply.

• Actions like “Close Conversation” or “Assign Conversation” take effect once a scenario is received. For example, if the Contact said there are no more questions, AI Agent will first close the conversation, and then generate a thank you note.

How actions work with audio messages

AI Agents can now understand audio messages shared by Contacts in real conversations.

When an audio file is received:

• It is automatically transcribed into text so the AI Agent can understand its content.

• The AI Agent processes the transcribed message and can perform relevant actions, such as assigning the conversation, updating Contact fields, or closing it, based on what was said.

• You can view transcripts of audio messages sent to AI Agents below the message bubble.

Important notes:

• Audio messages that are sent before a conversation is assigned to an AI Agent will not be taken into context and will not be displayed.

• Transcriptions may not show up instantly. Refresh your browser or switch to another conversation and back in to view transcript.

Supported audio and video file formats:

• Audio: MP3, WAV, FLAC, M4A, OGG/OGA, Opus, AAC, AIFF, WEBA

• Video: AVI, M4V, MKV, MOV, MP4, MPEG, MPG, WEBM, WMV, 3GPP

Writing Instructions to Trigger Actions

Good AI Agent instructions directly lead to clear, actionable responses. When writing instructions, keep these best practices in mind:

• Clearly specify conditions and desired outcomes. For example:

- If the customer asks about pricing, reply with our standard packages and assign the conversation to @Sales Team.

• Use straightforward, simple language. Avoid ambiguity.

• Anticipate common scenarios and build clear, simple instructions for each action.

• You can also define what to tell the customer when an action is used. For example:

- Once booking date and time are collected, reply to the Contact: "Thank you for your booking. We look forward to seeing you on $contact.bookingdate at $contact.bookingtime."

Chaining Actions Together

You can combine multiple actions in one scenario with common examples below.

For chained actions (For example, 1️⃣ Update Lifecycle → 2️⃣ Update Contact Field → 3️⃣ Close Conversation), make sure to place them in “Instructions” and ensure that the actions are turned on.

Examples:

Update Contact Field + Assign Conversation

- Collect and save Phone Number, then assign the conversation to a @Sales Team by round robin.

Update Lifecycle Stage + Close Conversation

- Update Lifecycle to "Issue Resolved", and close the converstion by summarising the customer issue and the solution provided.

Best practices:

• Keep it logical and goal-driven: Only chain actions if they naturally follow one another (e.g., qualify a lead → close the conversation → assign to Sales).

• Keep the order clear: Place actions in a sequence that reflects how a real conversation would flow — don’t assign a conversation before collecting the key info.

• Don’t overload one scenario: Stick to 2–3 actions max. Too many chained actions can make it harder for the AI Agent to predict and troubleshoot.

• Be explicit in your instructions: Clearly state each step, rather than relying on the AI Agent to “guess” what comes next.

What to avoid:

• Vague instructions

- If it feels like the issue is resolved, maybe update Lifecycle or something.

Problem: AI Agent won’t know which Lifecycle stage to use or when to trigger the action.

• Contradicting actions

- Assign to @Sales Team, then unassign if not needed.

Problem: This creates confusion for the AI Agent and leaves the conversation in an undefined state.

• Overloading one scenario

- Update Lifecycle to Qualified, collect phone number, update Contact Field with location, assign to @Sales Team, assign again to @Support Team, and close the conversation.

Problem: Too many steps in one chain make the flow unpredictable and hard to debug. Best to split them and follow natural order. For example: First, ask for phone number, then save it. Second, update Lifecycle to “Qualified", etc

Avoiding Workflow & Assignment Conflicts

When setting up actions, ensure they don’t conflict with your existing Workflows or manual team assignments:

• Check Workflow assignments: If you have Workflows assigning conversations automatically, ensure these don’t override your AI Agent’s assignments unintentionally.

• Default AI Agent considerations: If using a default AI Agent, ensure its actions align with any automated Workflows that trigger at conversation open.

Best practice: Regularly review your Workflows alongside AI Agent settings to avoid conflicts and unexpected behavior.

Available AI Agent Actions

AI Agents can perform the following actions while replying:

• Close conversations

• Assign to agent or team

• Update Contact fields

• Update Lifecycle stage

• Add comments

• Trigger Workflow

• Handle Calls