If a page uses an irrelevant structured data type, start by preserving one representative example. It gives the investigation a concrete reference and makes the eventual correction easier to judge.
Find the likely cause
The desired search appearance drives the choice instead of the content.
Treat this as an explanation to verify against the actual work. Look at the input, the relevant decision, and the final result together. If the evidence does not support this diagnosis, investigate the mismatch before applying a convenient but unrelated fix.
Make the targeted correction
Select a type that accurately describes the actual page and supported use.
Structured data should describe the page's actual visible content accurately and be checked against the requirements of the intended feature.
Check that the repair worked
Verify the applicable documentation before deploying the markup.
Repeat the check on the final version that the reader or customer will encounter. An approved draft, a preview, and a published result can differ; the acceptance decision should concern the version people actually use.
Prevent the next related failure
A separate issue to watch for is this: aI-generated structured data invents ratings or reviews. Remove invented values and include only appropriate supported facts.
Monitor the useful outcome
Track validation errors, consistency with visible content, and eligibility without assuming a guaranteed search presentation.
Keep a short record of the original symptom, the evidence behind the diagnosis, and the result of the acceptance check. That record makes the solution reusable when the same condition appears again, without assuming that every superficially similar problem has the same cause.
Official reference for the platform or standard discussed: Google Search Central: structured data.