Direct Answer (TL;DR)
When an AI voice agent is unsure, the agent follows configured fallback behavior: it attempts to clarify the caller’s request (ask a short follow-up question (clarifying question)), applies confidence thresholds (confidence threshold) to decide whether to continue, and then performs a fallback action such as a cold transfer (cold transfer), warm transfer with context (warm transfer), voicemail, or decline. Brilo AI business phone systems use admin-defined transfer rules and Phonebook destinations so uncertain calls either resolve with the agent or escalate to humans with context.
Why This Question Comes Up
Admin and support leads need predictable behavior when callers present ambiguous intent. Unclear routing causes poor customer experience, repeated questions for human agents, and missed safeguards. Teams ask how to prevent needless transfers, ensure safety escalations trigger, and keep handoffs efficient. Understanding default runtime behaviors and how to change them in the agent prompt and Actions console reduces these risks.
How It Works (High-Level)
An AI voice agent evaluates incoming audio and maps it to intents using internal confidence scoring (confidence threshold). When the confidence score falls below configured thresholds or a high-priority phrase is detected, the AI voice agent:
Attempts one or more clarifying questions (clarifying question) to resolve ambiguity.
Re-checks intent after clarification and retries the workflow if confidence improves.
If unresolved, executes a configured fallback action such as cold transfer, warm transfer (warm transfer with context), call deflection, voicemail, or scripted decline.
The AI business phone system maintains conversational context across attempts and logs decisions for later analysis.
Guardrails & Boundaries
Define explicit guardrails so the AI voice agent stays within safe boundaries:
Approved topics: list what the AI voice agent can and cannot handle.
Escalation criteria: set high-priority phrases (safeguarding keywords) that always trigger immediate human transfer.
Clarification limits: cap the number of clarifying questions before escalation to avoid loops.
Confidence thresholds: set numeric or rule-based thresholds for auto-resolution versus escalation.
These guardrails ensure predictable handoffs and prevent improvisation outside approved workflows.
Applied Examples
Ambiguous billing request: The AI voice agent transforms customer support by asking one clarifying question (clarifying question). If the caller responds with identifiable billing intent and confidence rises, the agent provides the answer. If not, the agent offers a warm transfer with a brief case summary (warm transfer).
Angry caller with threat language: The agent detects safeguarding keywords and immediately performs an escalation (escalation) to a human agent per the transfer rule.
After-hours support: The agent attempts clarification once, then records voicemail (fallback action) and schedules a callback instead of routing to unavailable staff.
Human Handoff & Escalation
Human handoffs are configurable and preserve context to avoid caller repetition:
Cold transfer: forward the call without context when immediate routing is required.
Warm transfer with context: send a brief summary with intent, recent questions, and confidence score so the human receives context before or during pickup.
Handoff metadata: include transcript snippets, caller-provided identifiers, and transfer reason in the handoff bundle.
Transfer routing: map destinations in Phonebook and prioritize recipients based on availability and escalation rules.
Use warm transfer and handoff metadata for an efficient human takeover and faster resolution in any AI business phone system.
Setup Requirements
To control uncertain behavior, you must:
Have admin access to the Brilo AI console.
Open the target agent and review the core instruction (agent “prompt”) to include a clear fallback strategy.
Configure Actions > Call transfer rules and add conditions (e.g., “caller asks for human,” safeguarding keywords).
Ensure Phonebook entries and destination phone numbers are valid and mapped.
Set confidence thresholds and clarify how many clarifying attempts the AI voice agent should make.
Configure voicemail, retry behavior, and warm-transfer summaries.
Test with a dedicated phone number and scripted ambiguous scenarios.
Business Outcomes
Properly configured uncertain-call handling delivers:
Fewer unnecessary transfers and lower human agent workload.
Faster resolution for routine requests through targeted clarifying questions.
Safer handling of critical phrases via immediate escalation.
Better human-agent efficiency because warm transfers include context and reduce repeat questioning.
These outcomes improve service consistency while keeping safety and compliance controls intact.
Next Step
Review your agent prompts and Actions > Call transfer rules in the Brilo AI console. Start with one ambiguous scenario, set a clear fallback action, and run live tests for your AI business phone system using a test number. Monitor logs for confidence scores, clarifying-question attempts, and successful warm transfers, then iterate on thresholds and prompt language. For more information, book a call with us today!