Direct Answer (TL;DR)
When the AI doesn’t understand the caller, the AI voice agent triggers a configured fallback: warm transfer, cold transfer, or post-call summary delivery. As the best AI voice assistant for customer support, the system uses intent detection and confidence thresholds to decide when to escalate, ensuring context is preserved so human agents do not need to ask callers to repeat information.
Why This Question Comes Up
Operations and admin teams want predictable behavior when the AI voice agent cannot resolve a request. High call volumes, ambiguous requests, or gaps in the AI voice agent knowledge base create situations where the AI voice agent must hand off. Organizations ask how the AI voice agent will route calls, whether context will be preserved, and how to configure fallback routing to minimize friction.
How It Works (High-Level)
The AI voice agent follows a decision flow when comprehension fails:
Monitor intent and confidence: The AI voice agent evaluates caller intent (intent detection) and a confidence score (confidence threshold).
Trigger fallback routing: If confidence falls below the threshold or the caller explicitly requests a human, the AI voice agent activates the configured fallback routing (fallback routing).
Execute transfer or summary: The AI voice agent performs a warm transfer (warm transfer), a cold transfer (cold transfer), or generates a post-call summary (post-call summary / call transcript) based on configuration.
Preserve context when possible: The AI voice agent can pass a short audio briefing or structured context metadata to the receiving human to enable context preservation.
Utilizing the best AI voice assistant for customer support means having a seamless transition between automated logic and human empathy.
Guardrails & Boundaries
Guardrails control when and how the AI voice agent escalates:
Allowed topics: Define which subjects the AI voice agent can address and which require human intervention.
Sensitive data: The AI voice agent must avoid collecting prohibited data; designate scenarios that force an immediate human handoff.
Confidence thresholds: Set the confidence threshold that triggers fallback routing rather than continuing a risky exchange.
Escalation rules: Create rules for caller requests to speak to a representative, call abandonment, or repeated clarification failures.
These guardrails ensure the best AI voice assistant for customer support maintains predictable, auditable behavior rather than open-ended improvisation.
Applied Examples
B2B sales inquiry: A caller asks a complex contract question the AI voice agent cannot resolve. The AI voice agent uses intent detection, fails the confidence threshold, and performs a warm transfer to the sales queue while providing a 10–15 second audio briefing to the rep.
Support triage: A technical support caller uses niche product terminology not covered in the knowledge base. The AI voice agent performs a cold transfer to the on-call engineer, then sends a post-call summary to the ticketing system (post-call summary).
After-hours routing: During off-hours, the best AI voice assistant for customer support captures caller details and delivers a call transcript to an email address for next-morning follow-up.
Human Handoff & Escalation
Human handoff options control how context is transferred:
Warm transfer (warm transfer): The AI voice agent calls the human rep first, plays a short context summary, and then connects the caller so the caller does not repeat details. This preserves context preservation.
Cold transfer (cold transfer): The AI voice agent routes the call without sending the collected context. Use cold transfer for simple redirects where context forwarding is unnecessary.
Post-call summary/Call transcript (post-call summary / call transcript): The AI voice agent generates a transcript and structured summary and delivers it by email or to an integrated CRM. The human rep can review the transcript prior to or after the call.
Configure escalation rules that include queue behavior, retry attempts, and alternative recipients when primary contacts are unavailable.
Setup Requirements
To configure fallback behavior for the best AI voice assistant for customer support, you need:
Admin permissions to edit the AI voice agent configuration in the dashboard.
Telephony integration and valid phone numbers or queue identifiers for transfer targets.
Enabled warm transfer and post-call summary features for your account (contact Brilo AI Support if unsure).
Recipient emails or CRM endpoints for post-call summaries.
Updated knowledge sources and prompt content for the AI voice agent knowledge base to reduce failures.
Defined confidence thresholds and escalation rules in the agent settings.
Business Outcomes
When configured correctly, fallback routing and context preservation help organizations:
Reduce caller repetition and improve first-contact continuity by preserving context preservation.
Streamline handoffs with warm transfer summaries so human agents start calls with useful information.
Capture actionable records via post-call summaries and call transcripts for faster case resolution and analytics.
These outcomes typically reduce operational friction and improve agent productivity when paired with iterative tuning.
Next Step
Review the AI voice agent fallback settings in your dashboard, enable warm transfer or post-call summaries as needed, and run staged tests to verify context preservation. For more information, contact Brilo AI.