Autonomy Ceiling Review (Onboarding)

Autonomy Ceiling Review (Onboarding)

1. 01

   Map every client call type to a resolution band before any AI agent goes live

   Split inbound volume into three buckets: fully automatable (order status, hours, address changes), agent-assist (billing disputes, cancellation saves), and human-only (escalations, legal, retention offers). Nectar Desk's AI Voice Bot resolves 40-65% of inbound calls autonomously, so the ceiling is set by call mix, not by the platform.

2. 02

   Set the containment target as a range, not a single number

   Write the client-facing commitment as a band (for example 35-55% containment in month one) and define what happens at each end. A single promised figure turns a normal variance into a breach conversation.

3. 03

   Define the warm-transfer rule and test it on a live call

   Specify the exact conditions that push a caller to a human (two failed intent matches, sentiment drop, or an explicit request) and confirm the handoff carries transcript context so the client's team is not restarting the conversation.

4. 04

   Confirm where client call data is stored and whether it trains a shared model

   Forrester analysts argue private AI deployments outperform public tools for B2B use cases because shared model access erases differentiation. Document the data path for each client account before the first call is recorded.

5. 05

   Classify the deployment by autonomy level and add review checkpoints

   Tag the workflow as assistive, semi-autonomous, or fully autonomous. Any tier that touches client-facing communications or CRM writes gets a human-review checkpoint until two consecutive weeks of clean transcripts.

6. 06

   Load vertical vocabulary and the client's top 20 intents into the knowledge base

   Generic training data produces generic containment. Pull the client's last 90 days of transcripts, extract recurring phrasing, and load it before launch. This is the step that separates a managed retainer from a resold seat.

7. 07

   Agree the QA sampling rate and the weekly reporting format in writing

   State how many transcripts get reviewed per week, who reviews them, and which three metrics appear in the client report. NICE CXone evaluates 100% of interactions automatically, but a human sample still catches tone failures that scoring models miss.