A policy that tells search platforms how to handle factual errors in AI-generated answers about a brand, and defines the process for submitting updates.
Marketers reading about managing structured markup data within search engines.
01What it is and how it works
When an AI system returns a brand‑related answer, the system checks whether the answer matches any Correction markup that the brand has published. If the markup signals a factual error, the system replaces the incorrect snippet with the corrected text or adds a note that a correction exists. The policy also tells the platform how long a correction stays active and what signals (e.g., dateModified) trigger a refresh.
It is a set of rules that say how to fix wrong facts in AI search results for a brand.
02What to do about it
You can start fixing errors today by following these steps:
- Audit the top AI‑generated answers for your brand and note any inaccuracies.
- Create or update a
Correctionstructured‑data block on a dedicated page. Use thedateModifiedfield to indicate when the fix was made. - Submit the page URL through the Search Console’s URL Inspection tool to prompt a re‑crawl.
- Monitor the Search Console’s Coverage report for any “Submitted URL marked as a correction” status.
03How it is measured or noticed
The platform logs a correction event each time it swaps an AI snippet for a corrected version. Marketers can see these events in the Search Console under the Enhancements > Corrections report. Additionally, the presence of the correction rich result in the SERP (a small “Corrected” label) signals that the policy is active.
04Common mistakes
- Leaving the
dateModifiedfield blank, which prevents the system from recognizing a new correction. - Using generic text instead of the precise corrected fact, causing the AI to ignore the markup.
- Placing the
Correctionmarkup on a 404 page or a page blocked by robots.txt.
05Limits and confusion
A Corrections Policy only applies to AI‑generated answers that pull data from structured markup. It does not affect organic snippets that are purely text‑based, nor does it replace a full legal disclaimer. Brands sometimes confuse a Corrections Policy with a general Content Policy; the former is a technical request for factual updates, while the latter governs what content may appear at all.
06Worked example
"Our product’s battery life was listed as 8 hours, but the official spec is 10 hours. We added aCorrectionblock on https://example.com/corrections/battery‑life withdateModified: 2024‑08‑20. Within 48 hours the AI answer changed to show the 10‑hour figure and displayed a ‘Corrected’ badge."
Frequently asked questions
How does a Corrections Policy differ from a regular content update policy?
No, it is not the same as a regular content update policy. A Corrections Policy specifically guides AI search platforms on swapping out AI‑generated answers that contain factual errors, using correction markup, whereas a content update policy covers broader changes to website content.
Should we create a Corrections Policy for every brand we manage?
It depends on the brand’s presence in AI‑generated search results. If the brand’s data is frequently pulled into AI snippets, a Corrections Policy is valuable; otherwise, the effort may outweigh the benefit.
Who is responsible for adding the correction markup that the AI system reads?
The brand’s SEO or web‑team typically adds the correction markup to the site’s structured data. Once the markup is published, the AI platform can detect it and replace erroneous snippets.
Does a Corrections Policy still work if the AI model’s training data is outdated?
Usually, it only affects the live retrieval of structured markup, not the model’s static training data. The policy can correct answers that are generated on the fly, but it won’t rewrite facts already baked into the model.
What happens if we submit an incorrect correction markup?
If the markup is wrong, the AI platform may replace a correct answer with another error, and you’ll see a correction event logged as a failure. You’ll notice it through monitoring tools that flag unexpected correction events.
How long does it take for a correction event to appear after we update the markup?
Typically, the change is reflected within a few hours after the markup is crawled, but it can take up to 24 hours for the platform to log the correction event. During that window, you can monitor logs to confirm the swap.
Asked out loud
spoken, not typedThe same term in the words somebody uses speaking to an assistant rather than typing into a box — written from the situation, which is why each one carries the situation it came from.
Yes, you can fix it immediately by publishing the correct correction markup on your site. Once the crawler picks it up, the AI platform will log a correction event and swap the snippet.
Usually, you need to add or update the correction markup on the relevant page and then request a recrawl if the platform allows it. The corrected answer should appear within a few hours, giving you time before the meeting.
First, check your site's structured data documentation for the specific correction schema and add it to the page that feeds the AI snippet. If you're still unsure, contact your SEO team or the platform’s support for guidance.