AI Content QC Checklist Built on Google's Guidance

Before you publish AI-assisted content, check twelve things: four that block publication outright and eight you score. Each maps to a line in Google's own documentation, which I read on 13 November 2026. Google says it judges content by usefulness and reliability, not by how it was made, but it also names scaled, low-value AI pages as spam. This checklist is how I would turn that into a repeatable gate.

Key Takeaways

• Google's generative AI guidance says AI can help with research and structure, but generating many pages without adding value may violate its scaled content abuse spam policy.
• The same page says AI-generated content should be manually fact-checked and reviewed before publishing, and that the review covers titles, meta descriptions, structured data and image alt text.
• Google's people-first content guide supplies most of the quality questions: original information, insight beyond the obvious, careful production, clear sourcing, and a Who, How and Why check.
• Google's spam policies say scaled content abuse applies "no matter how it's created", so the test is value to users, not the tool.
• The 12-point gate below is my own structure. The scoring thresholds are my convention, not Google's, and no checklist predicts rankings.
• For batches of similar pages, run the gate on a pilot of five before you scale, and rerun it on a sample after each batch.

What Google actually says

Three Google pages carry the substance. None contains a score or a threshold, so everything below that looks like a number is mine.

One timing note. The fact-check wording on the generative AI page is covered in my earlier post on Google's AI content guidance and the fact-check rule, which reports an October 2026 update. The page text I fetched shows no last-updated date, so I cannot confirm that date independently. The guidance itself is consistent with Google's 2023 post on AI content, which says AI use gives no ranking advantage or penalty by itself.

The 12-point gate

Four hard-fail checks

Any "no" means the page does not ship. These are binary because each maps to something Google treats as a baseline.

1. Every fact is traced. Each number, date, name, price and quote has a source you opened. Google calls manual fact-checking critical for AI-generated content. Pass test: the reviewer can click from each claim to its source in under a minute.
2. Metadata reviewed by a human. Title, meta description, structured data and image alt text were read, not just generated. Structured data was validated and follows the feature's guidelines.
3. Original value is nameable. You can state in one sentence what this page offers that the sources it draws on do not: original data, a framework, first-hand method, or a clearer synthesis. Google asks whether content adds real value rather than copying or rewording others.
4. Not one of many near-identical pages. If the page belongs to a batch, it differs from its siblings in substance, not just in a swapped keyword or city. Google's spam policy lists mass-produced pages with little user value among its examples.

Eight scored checks (0, 1 or 2 points each)

Scoring is out of 16. My working thresholds, which are conventions and not Google rules: 13 or more publishes, 9 to 12 goes back for fixes, 8 or below is rewritten or not published. For health, money, safety or legal topics, Google's guide says its quality assessment puts greater weight on trust, so I would require a named expert reviewer (check 9 scored at 2) regardless of total.

On disclosure, Google's 2023 post says listing AI as an author is probably not the best way to show AI involvement. A short "how this was produced" note is the closer fit to the "How" question.

Ecommerce add-on

For product pages feeding Google Merchant Center, the generative AI page says AI-generated images need the IPTC DigitalSourceType value TrainedAlgorithmicMedia in their metadata, and AI-generated product titles and descriptions must be specified separately and labelled as AI-generated. Add that as check 13 if you run a product feed.

Running the gate on a batch: a hypothetical example

This is an illustrative scenario with an invented company, "Example Academy", not a real project or result.

Example Academy wants 40 comparison pages, one per course pair. An AI tool drafts all 40 from a spreadsheet.

1. Pilot five. The reviewer runs the 12-point gate on five pages. Two fail check 4: only the course names differ, the body text is interchangeable. One fails check 1: a fee figure has no source.
2. Fix the template, not the pages. The team adds a section that only exists when data supports it (for example, a real difference in schedule or assessment), and a fact sheet with sourced fees.
3. Re-pilot. Five new pages are scored again. Hard fails clear.
4. Sample. After drafting the remaining 35, the reviewer scores 8 at random and every page that touches fees or outcomes.
5. Decide per page. Score 13 or more ships. A page with nothing distinct to say is merged into a stronger page, or left out.

For a longer treatment of why such pages often disappoint, see why most AI content isn't ranking. For tooling that generates pages at scale, programmatic SEO tools compared covers the production side.

What this means for marketers

• This week: score your last five AI-assisted pages. Do not expect perfection; look for which checks fail most often and fix the process there.
• Put a name on check 9. A reviewer who is recorded, with a link to their background, strengthens the Who answer. Your about page and an editorial and correction policy support it.
• Gate before scale, not after. Fixing a template costs less than auditing 400 pages.
• Leave alone: pages that score well. Do not add AI disclosures to everything by reflex; Google ties disclosure to where readers would reasonably ask how content was made.
• My view: the checklist is a process control, not a ranking lever. Passing it makes a page defensible and useful; it does not promise traffic.

Common mistakes

• Treating "a human skimmed it" as a fact-check. Check 1 requires tracing, not reading.
• Reviewing the body but not the title tag, meta description and schema, which Google says need the same review.
• Scoring all pages in a batch together, so a good average hides a failing template.
• Adding a vague "written with AI" footer and calling check 7 done.
• Using the checklist as proof of quality to a client. It documents process only.

Caveats

Google's documentation does not publish a pass mark, and my thresholds are untested judgment. Google also says the Search Quality Rater Guidelines are not a ranking guide and rater ratings do not directly influence rankings, so I have not used them as a scoring source. I have not run this gate on live client pages for this post.

FAQ

Does Google penalize AI-generated content?

Google's guidance says it focuses on usefulness and reliability rather than how content is produced. Using AI to generate many pages mainly to manipulate rankings can break its scaled content abuse policy, whatever tool made them.

Do I have to label content as AI-generated?

Google does not set a blanket rule in the pages I read. It says explaining how content was created can help readers, and recommends disclosure where a reader would reasonably ask. For automatically generated content, it suggests describing how automation was used.

What does Google mean by Who, How and Why?

Who asks whether the author is clear. How asks whether the page explains how it was produced, including any automation or AI. Why asks whether it was made mainly to help visitors rather than to attract search traffic.

Does the fact-check rule cover meta descriptions?

Yes. Google's generative AI page says the same review applies to titles, meta descriptions, structured data and image alt text, since those can appear in Search results.

How many pages should a human review in a batch?

Google gives no number. My convention is to review a pilot of five, then a random sample plus every page with fees, outcomes or health, money or safety claims. Raise the sample if the pilot shows failures.

Is a score of 13 out of 16 a Google standard?

No. The 12-point structure and thresholds are mine, built from Google's questions. Use them as an internal control and adjust them to your risk.

Where should an AI-generated product description be labelled?

For Google Merchant Center, Google's page says AI-generated product data should be specified separately and labelled as AI-generated. AI-generated images need the IPTC DigitalSourceType value TrainedAlgorithmicMedia.

Want help with this?

I'm Younus Fardeen, an organic growth, SEO and AEO strategist with 4+ years of marketing experience across edtech and startup teams. If you want help setting up a pre-publish quality gate for AI-assisted content, see my work and reach me through the contact form at younusfardeen.com.