Why can an AI answer be wrong even when the information on the…

Direct answer

Correct information on a website does not mean that every system will find the page, read it, match it to the correct entity, select the relevant passage and carry it into an answer accurately. An error can occur during access, indexing, retrieval, entity resolution, source combination or generation.

In plain language

The correct answer may be written in a book. A student can still be wrong if they open the wrong book, use an old edition or misunderstand the right page. Correct information in one place does not make every link in the answer chain correct.

Why this matters

If the problem is misdiagnosed, a team may keep rewriting the text when the real cause is blocked access, the wrong canonical page, an outdated third-party record or confused identity.

Do not confuse

Publishing and crawler access are different.
Being crawled and being indexed are different.
Being in an index and being selected for a particular query are different.
Selecting a source and generating an accurate answer are different.

What should you do?

Preserve the incorrect answer in its raw form together with the date and system details.
Split each error in the answer into a single claim.
Check access to and index status of the relevant canonical page.
Find old or third-party sources that conflict with it.
Apply the correction at the correct layer and measure again with the same test.

How do you audit it?

Is the correct URL accessible?
Was the correct entity selected?
Which sources did the answer use?
Is an old or conflicting source dominant?
Did the error arise before or after retrieval?

Limit

An external test cannot reveal every internal decision made by a closed system. An audit draws reasonable, limited inferences from observable evidence.