Stop 12 · AI & Modern BA PracticesTopics · 6/7

Evaluating AI Output Quality

In short

AI output always looks confident and well-formatted, even when it's wrong. Whatever your job, the skill that now matters is checking it properly before your name goes on it.

AI-generated requirements or analysis can look polished while missing critical business nuance, containing factual errors, or introducing subtle ambiguity — critically reviewing AI output is now as important as prompting it well.

The purple blob at a fruit cart inspects a mango through a magnifying glass.

Think of it like this

Buying mangoes at the cart

The shiniest mango on the cart can still be sour or soft inside. So you press it, smell it and maybe ask for a taste. You don't judge it by the shine. Treat AI output the same: polish isn't proof.

Watch it happen

Running one AI answer through five checks

Accurate?

Complete?

Relevant?

Consistent?

Safe?

1/6Accurate: are the facts, numbers and names correct? Check at least one against a trusted source.

The big ideas

What you need to know

Fluent is not factual

AI predicts likely-sounding text. It can make up a statistic, a source or a feature that sounds perfectly real.

Verify the risky bits

Focus your checking on numbers, names, dates, legal or medical claims and anything a decision depends on.

Use a checklist

Accuracy, completeness, relevance, consistency and safety. A checklist stops you skimming because it looks good.

Your name, your responsibility

When you share it, you own it. 'The AI said so' won't help when a client finds the mistake.

Save yourself the pain

Common mistakes

Oops

Judging AI output by how professional it sounds.

Do this instead

Judge it by whether the facts check out and whether it fits your real context.

Oops

Asking the same AI 'Are you sure?' as your only check.

Do this instead

Verify against an outside source: your data, documents, an expert or an official website.

Your mission

Grade three AI answers

~30 min

Quick check

An AI summary of a market report quotes a precise figure with a source you can't find anywhere. What's the safest move?

Go deeper

1Take an AI-generated requirements draft and audit it for ambiguity or missing edge cases.
2Practice fact-checking any numeric claim an AI tool includes in an analysis.
3Define what 'good' looks like for a task before evaluating AI's attempt at it.