People Use AI
Customer Support

Pre-launch testing and validation of AI support replies, knowledge gaps, real-world inputs, and human handoff paths

Before launch, teams intentionally test AI support systems—including shadow-mode or private-draft workflows for email or chat—by reading early replies aloud, probing undocumented questions, replaying messy real-world inputs, and validating escalation and human handoff flows so failures in tone, safety, knowledge boundaries, and routing are caught before customers experience them.

Why the human is still essential here

Humans design realistic test scenarios, judge whether replies are safe and on-brand, verify fallback and escalation behavior, and decide whether the system is ready for customers.

How people use this

First-reply read-aloud review

Before launch, managers listen to the first batch of Intercom Fin answers to catch awkward phrasing, robotic tone, or confusing wording.

Intercom Fin

Launch-week answer audits

Teams use Forethought Agent QA to sample early automated replies and identify subtle errors or answer patterns that need prompt or content fixes.

Forethought Agent QA

Out-of-docs policy probes

Reviewers ask Ada questions about policies or exceptions that are not documented to verify the bot declines gracefully instead of inventing an answer.

Ada

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How-To
Article

Deploy Email AI Agent in shadow mode

Shadow mode lets you evaluate the Email AI Agent using real incoming email tickets without sending AI-generated responses to customers.

Unlike live mode, the Email AI Agent in shadow mode does not own tickets or perform customer-facing actions. Instead, it runs silently in parallel with human agents, adds private notes, and allows them to review and use them before the Email AI Agent is deployed in live mode.

Deploying the Email AI Agent in shadow mode provides the following benefits:

Evaluate AI-generated responses without sending them to customers.

Allow human agents to review and manage all customer communications.

Assess AI performance before enabling live mode.

Identify knowledge gaps to improve AI responses and your knowledge base.

F
FreshdeskProduct documentation team
Aug 4, 2026
Tip
Reddit

before we go live with any AI support setup, I run through the same checklist. Here's what's on it.

not a formal list or anything, just stuff I actually run through now because I've seen what happens when you don't

test it as your worst customer not your best one vague question, typo in it, missing half the context. if it handles that you're probably fine. most people only test the clean version and then wonder why it breaks on real customers

ask it something that's not in the docs not to be mean to the AI, just to see what it does when it doesn't know. does it say it doesn't know or does it just... make something up confidently. very different outcomes

go through every case you've had to escalate manually before if a human has had to step in for it, the AI will hit it eventually. better to find out in testing than from a pissed off customer

make the "talk to a human" option obvious not in a footer somewhere. actually there. especially for anything touching money or cancellations

read the first 20 answers out loud sounds dumb but you catch things this way that you miss reading. if anything sounds slightly off it needs fixing before customers hear it

most of the issues I end up seeing in tickets could've been caught in like 30 mins of this before launch. anyway hope it helps someone

S
ShotOil1398Customer Support practitioner
Apr 17, 2026