The symptom is specific: aI-generated structured data invents ratings or reviews. Start with the affected item and identify the decision or input that could produce this behavior.
Find the likely cause
The model fills optional fields with plausible examples.
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
Remove invented values and include only appropriate supported facts.
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
Compare every claim in the markup with genuine visible page information.
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: markup describes a different product from the page. Populate fields from the correct authoritative product record.
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.