World Model Readiness Where the bot ends, a human begins

Module · Where the bot ends, a human begins

The AI-in-Customer-Service Check

A support bot handles the easy questions cheaply, right up until it confidently gives a wrong answer to an angry customer with nowhere to go. The economics are real and so is the reputational downside. This module checks the five controls that decide whether automated support helps or corrodes trust: a defined scope, a working escalation path, honest disclosure, quality monitoring of what the bot actually says, and a loop that learns from the conversations it got wrong.

Question 1 of 5 · Bot scope is defined

Is there a clear line for what your support bot may and may not handle?

A bot without a defined scope answers everything, including the refund policy it guessed and the medical question it should never touch. Scope written as explicit boundaries, enforced by the system, is what keeps a helpful assistant from becoming a liability with a chat window.

Question 2 of 5 · Escalation actually works

When the bot cannot help, can a customer reach a human without a fight?

The fastest way to turn a minor issue into a lost customer is a bot that loops, deflects and hides the exit. A named, easy path to a human, triggered by the customer or by the bot recognising its own limits, is the safety valve the whole system depends on.

Question 3 of 5 · Customers know it is AI

Do customers know when they are talking to a bot rather than a person?

Pretending a bot is human buys a few smoother minutes and a lasting trust cost when the customer works it out, and they do. Clear disclosure is increasingly a legal duty as well as a decency one, and it sets expectations that make the whole interaction go better.

Question 4 of 5 · Answers are monitored

Do you know how often your bot gives customers wrong or unhelpful answers?

A bot fails silently: no complaint, no ticket, just a customer who quietly gave up or acted on bad information. Without sampling and monitoring the actual answers, you are trusting a system you have never audited to speak for you thousands of times a day.

Question 5 of 5 · Failures feed learning

When the bot fails a conversation, does anything change as a result?

Every bot has conversations it handles badly. The question is whether those failures end as a shrug, or as a fix to the knowledge base, the scope or the escalation rule. A support bot that does not learn from its worst days repeats them indefinitely.

For the statistics · one click each

Three questions for the public picture

These do not affect your score. They feed the anonymised, aggregated statistics; groups under 8 respondents are never shown.

What share of customer contacts does AI handle without a human?

None
Under a quarter
A quarter to half
More than half
We do not track it

Do you tell customers when they are talking to a bot?

Yes, up front
Only if they ask
No
We are not sure
No support bot yet

How easily can a customer reach a human when the bot cannot help?

One step, quickly
Possible but slow
Hard to find
No human option
No support bot yet

Your context

Used to calibrate the report. Company size and sector remain in the anonymized dataset; your email does not.