How to build a proactive agent for AI outbound calling

Most people design reactive AI agents. They sit and wait unless prompted. That’s it. And while there’s certainly a time and place for this kind of solution, it leaves the wider (and arguably more important) use case unaddressed: proactive support.

See, while your customer’s order got delayed, and your AI agent was fully capable of finding that out, it waited until the annoyed customer called. By that point, the situation had already turned to damage control. The package is already late, and your customer found out the hard way.

Now, compare that situation with a proactive AI agent purpose-made for outbound calling. When it makes a call and notices the delayed shipment, it reaches out to the customer first (by phone or text) with all the context it needs to solve the issue.

This use case goes beyond your sales team autodialer. Below, we show you the customer service version: how to trigger outreach from customer data, load context before the agent says hello, schedule callbacks and follow-ups, and stay on the right side of consent rules.

What is a proactive AI agent?

A proactive AI agent is an AI agent that starts conversations with customers based on events in your systems (like a shipping delay or missed payment) and handles the resulting conversation across voice or messaging.

Imagine your AI agent calling a customer to let them know a package is going to be late before they check the system and see it themselves. That’s a proactive AI agent. If a customer calls you, angry about a late-discovered delay that’s potentially derailed their plans, now you’re stuck being reactive.

Proactive AI agents aren’t sales dialers. A proactive service agent contacts existing customers about something specific to their account, at a moment when the contact is useful to them. That changes the experience on the receiving end, and it changes how you think about consent.

How to build a proactive AI agent for outbound calling

A proactive agent has six moving parts, and the order matters. Each of these needs to be in place before the next. Consent comes before any trigger fires, and context loads before the first message goes out.

1. Get consent and contact rules in place first

Outbound calling comes with rules, and AI isn’t exempt from them. The FCC ruled that AI-generated voices count as artificial voices under the Telephone Consumer Protection Act. The TCPA's consent requirements apply to AI voice calls (Mayer Brown's analysis covers the details).

Ouroutbound AI calling tutorial prioritizes this from the get-go, pointing builders to:

• The TCPA

The TCPA

• Twilio's Terms of Service

Twilio's Terms of Service

• Twilio's Voice Services Policies

Twilio's Voice Services Policies

We also recommend a conversation with your counsel. However, this article isn't legal advice, and the rules vary by country, state, and use case.

Build these into the system before the agent makes its first call:

• Consent records: Store which customers agreed to be contacted, on which channels, and for what purpose. Stick to them and never deviate.

Consent records: Store which customers agreed to be contacted, on which channels, and for what purpose. Stick to them and never deviate.

• Opt-out handling: Honor opt-out requests on every channel, and stop pending outreach when a customer opts out.

Opt-out handling: Honor opt-out requests on every channel, and stop pending outreach when a customer opts out.

• Contact-time rules: Define when your agent is allowed to reach out, based on the customer's local time and applicable regulations. This is for legality and decency.

Contact-time rules: Define when your agent is allowed to reach out, based on the customer's local time and applicable regulations. This is for legality and decency.

2. Trigger outreach from CRM events

Twilio triggers proactive AI outreach from CRM events by pairing Twilio Segment (which detects the event in your customer data) with Twilio Agent Connect (which starts the conversation). Your server sits between them and decides whether to reach out.

Here's how it works:

• Customer data flows into Segment. CRM records, order events, and payment status sync into unified customer profiles.

Customer data flows into Segment. CRM records, order events, and payment status sync into unified customer profiles.

• An event triggers a journey.Engage Journeys runs event-triggered journeys that react to customer behavior as it happens, like an order status changing to delayed.

An event triggers a journey.Engage Journeys runs event-triggered journeys that react to customer behavior as it happens, like an order status changing to delayed.

• Segment calls your server. TheWebhook destination or aDestination Function sends the event to your Agent Connect server.

Segment calls your server. TheWebhook destination or aDestination Function sends the event to your Agent Connect server.

• Your server checks the rules. Before anything goes out, your code confirms consent, contact-time rules, and whether this customer already heard from you today.

Your server checks the rules. Before anything goes out, your code confirms consent, contact-time rules, and whether this customer already heard from you today.

• Agent Connect starts the conversation. Your server calls the outbound method for the right channel, and the agent takes it from there.

Agent Connect starts the conversation. Your server calls the outbound method for the right channel, and the agent takes it from there.

Segment helps when the trigger depends on data from several systems, like a delayed order for a customer who's also contacted support twice this week.

3. Load context before the agent reaches out

You’re the one reaching out first. That means you shouldn’t be confirming your recipient’s name or account number. Your agent should already know who it's calling and why.

Twilio Conversation Memory stores observations and conversation summaries on each customer's profile. Its Recall endpoint returns the most relevant memories for a customer, and when you don't pass a conversation ID, it returns their most recent observations and summaries. Call Recall when the trigger fires, then pass that context and the event details into the agent's instructions.

Context should predicate every proactive AI agent conversation. And the more context, the better.

Consider this context-loaded order update: "Hi Rachel, it's the support assistant from [company]. Your replacement router is running two days late. I can switch it to expedited shipping at no charge, or set up a callback with our team. Which works better?"

4. Pick the channel and start the conversation

Twilio Agent Connect supports agent-initiated conversations over SMS, Voice, WhatsApp, and RCS. Each channel has an outbound method in the Python and TypeScript SDKs.

On messaging channels, the method creates the conversation through Conversation Orchestrator and sends the first message. On voice, it places a call that connects to your Agent Connect server, whereConversationRelay handles speech-to-text and text-to-speech. An optional welcome greeting plays the moment the customer picks up.

Whichever channel you use, customer replies flow into the same message handler as inbound conversations. Your tools, policies, and escalation rules apply automatically.

• Messaging: Better for informational updates and anything the customer might want to act on later. A delay notice with options works well as a text.

Messaging: Better for informational updates and anything the customer might want to act on later. A delay notice with options works well as a text.

• Voice: Better for time-sensitive issues or conversations that need back-and-forth, like rescheduling a technician visit for tomorrow morning.

Voice: Better for time-sensitive issues or conversations that need back-and-forth, like rescheduling a technician visit for tomorrow morning.

Regardless of the practicality, honor your customer’s preferences gained in the consent phase. If they want to be contacted about account changes via SMS, don’t call them. And vice versa.

5. Schedule callbacks and follow-up messages

An AI agent schedules callbacks and follow-up messages with tools: one that books a callback slot in your calendar or CRM, and one that queues a follow-up message for a set time. With Twilio, follow-up messages use native Message Scheduling, and your scheduler places callbacks at the booked time through Agent Connect's outbound voice method.

Follow-up messages. Twilio'sMessage Scheduling sends SMS, MMS, WhatsApp, and RCS messages at a fixed time in the future. A few specifics matter for agent design:

• Scheduling window: Messages can be scheduled between 15 minutes and 35 days ahead.

Scheduling window: Messages can be scheduled between 15 minutes and 35 days ahead.

• Messaging Service required: Scheduled messages need a Messaging Service, or Twilio sends them immediately.

Messaging Service required: Scheduled messages need a Messaging Service, or Twilio sends them immediately.

• WhatsApp templates: Scheduled WhatsApp messages need approved templates, validated at send time.

WhatsApp templates: Scheduled WhatsApp messages need approved templates, validated at send time.

Give your agent a tool that creates a scheduled message, and it can say, "I'll text you the tracking link tomorrow morning once it's live," then queue that message before the conversation ends.

Callbacks. When a customer wants a call back, the agent's booking tool checks availability in your calendar or CRM, confirms a slot with the customer, and saves the appointment. At the booked time, your scheduler (like a cron job or a workflow in your existing systems) calls Agent Connect's outbound voice method to place the call.

For the callback itself, run Recall again. Something may have changed since the original conversation, and the agent should know about it before the customer picks up. Proactive AI agents should always start with full context.

6. Hand off when the customer wants a person

Some customers will want a human the moment they realize they're talking to an AI agent. Others will hit an issue the agent can't resolve. Both need a clean, clear exit.

Agent Connect's built-in handoff tool transfers the conversation through a Twilio Studio flow to a human agent inTwilio Flex, carrying the conversation ID, memory store ID, and the reason for escalating. The customer stays on the same call or chat. Add Conversation Intelligence, and the human agent also opens on an AI-generated summary.

AI agent pre-launch checklist

After following these six steps, do a last-minute check before your proactive agent contacts a real customer:

• Is consent recorded and checked in code? Your server should refuse to start outreach for any customer without the right consent on file.

Is consent recorded and checked in code? Your server should refuse to start outreach for any customer without the right consent on file.

• Do opt-outs cancel pending outreach? Twilio's docs note that scheduled messages to customers who later opt out fail at send time, so cancel them yourself when an opt-out arrives.

Do opt-outs cancel pending outreach? Twilio's docs note that scheduled messages to customers who later opt out fail at send time, so cancel them yourself when an opt-out arrives.

• Are frequency limits in place? One delayed order shouldn't trigger three contacts. Cap outreach per customer per day.

Are frequency limits in place? One delayed order shouldn't trigger three contacts. Cap outreach per customer per day.

• Does the agent identify itself? Customers should know who's contacting them and why within the first sentence.

Does the agent identify itself? Customers should know who's contacting them and why within the first sentence.

• Is there a fast path to a human? Test that the handoff works on every channel you use.

Is there a fast path to a human? Test that the handoff works on every channel you use.

• Are your examples safe for your industry? Regulated data, like health information, needs its own architecture review before it enters any outreach flow.

Are your examples safe for your industry? Regulated data, like health information, needs its own architecture review before it enters any outreach flow.

Reach out before they reach in

Every proactive conversation is one fewer frustrated inbound contact. The customer who hears about the delay first (with a fix already on the table) has no reason to call in angry.

And that’s a win for everyone.

Build consent and contact rules first, wire outreach to the events that matter, and give the agent enough context to open with a solution. Do that, and AI outbound calling stops looking like an autodialer and starts working like good service. The way it should.

Give it a try. Sign up for free, and start building your proactive AI agent with Twilio.

Frequently asked questions

What platform can build a proactive AI agent that reaches out to customers based on CRM triggers?

Twilio combines Segment, which detects CRM and customer data events, with Agent Connect, which starts outbound conversations over SMS, Voice, WhatsApp, or RCS. Your server checks consent and contact rules before each outreach.

Can an AI agent autonomously schedule callbacks and send follow-up messages?

Twilio supports both through agent tools. Message Scheduling queues SMS, WhatsApp, MMS, and RCS follow-ups 15 minutes to 35 days ahead. For callbacks, the agent books a slot and your scheduler places the call through Agent Connect.

Is AI outbound calling legal?

Twilio's outbound calling guidance points builders to the TCPA and recommends consulting counsel. The FCC ruled in 2024 that AI-generated voices count as artificial voices under the TCPA, so its consent requirements apply to AI calls.

Which channels can a proactive AI agent use?

Twilio Agent Connect supports agent-initiated conversations over SMS, Voice, WhatsApp, and RCS. Customer replies flow into the same handler as inbound conversations, so one agent covers every channel.

How does a proactive AI agent know a customer's history before reaching out?

Twilio Conversation Memory's Recall endpoint returns a customer's most relevant observations and conversation summaries. Calling it when outreach triggers gives the agent context before the first message or greeting.