This AI content quality checklist gives you 24 checks to run on every AI-assisted draft before it goes live, grouped into six areas: accuracy, substance, intent, wording, metadata and the rest of your site.
By Kristijan GjorgjioskiIndependent SEO consultantPublished 18 October 2026 · 7 min read
AI drafts look finished long before they are.
The headings are tidy and the sentences flow. Then a client spots an invented statistic, or a price from two years ago.
This AI content quality checklist is the routine I run before any AI-assisted page goes live. It has 24 checks in six groups.
Copy it into a spreadsheet with a status column and work through it on every draft.
You don't need to run every group in the same depth on every page.
Start where your risk is highest:
Every check has a clear end state. If you can't confirm it, it's not done.
Google's guidance on generative AI content says outputs may contain inaccuracies, and that manual fact-checking before publishing is critical.
So this group comes first.
Highlight every figure in your draft: percentages, prices, dates, counts.
Each one needs a named source you've opened yourself. If you can't find one, delete the number or replace it with a pattern you can stand behind.
Done when: every figure has a source, or is gone.
Models describe software, rules and features as they were in their training data.
Check each product feature, setting name and policy against the vendor's current documentation.
Done when: every product claim matches a page you checked this week.
AI drafts love confident claims: years of experience, awards, guarantees, "trusted by hundreds".
Ask the business for proof of each one. No proof, no claim.
Done when: every claim about the business is confirmed by the business.
Check each link loads and says what you claim it says.
AI drafts sometimes cite pages that don't exist, or point to a real page that says something else.
Done when: every link resolves and supports its sentence.
A model writes the average of what's already out there.
Google's helpful content questions ask whether a page provides "substantial value when compared to other pages in search results". That's the bar.
Open the top results for your query, or the competitor notes in your content brief. Then write down, in one sentence, what your page adds.
A sharper answer, a real example, a process detail, a mistake you've seen. If you can't name it, the page isn't ready.
Done when: you can state the page's added value in one sentence.
Experience is the part a model can't fake.
Add at least one detail that only the business could know: how a job actually runs, what customers ask, what goes wrong.
Done when: the page contains something no competitor could have written.
AI drafts often open a section by restating its heading in different words.
Delete those. Start each section with the answer.
Done when: no paragraph exists only to rephrase the heading above it.
"A local business" and "a typical customer" tell your reader nothing.
Swap them for a real service, a real place or a real situation the business handles.
Done when: every example names something concrete.
A well-written page in the wrong shape still loses, however good your on-page SEO is. Check that your draft matches search intent before you polish sentences.
The first two sentences under the title should answer the question the searcher typed.
No scene-setting, no "in this article".
Done when: someone reading only the opening gets the answer.
If the top results are step-by-step guides, a listicle won't compete. If they're comparisons, an essay won't either.
Done when: your page is the same type as most of the top results.
Read only your headings, top to bottom.
They should tell the whole story and make sense out of context, because AI answers and featured snippets often lift sections on their own.
Done when: the headings alone summarise the page.
The main phrase belongs in the title, the main heading and the opening paragraph.
Then look for the opposite problem: the exact phrase forced into every heading.
Done when: the keyword sits where it should and nowhere it reads badly.
Readers spot machine-written copy fast. These checks remove the tells.
Keep a banned list and search your draft for it. Mine covers overused verbs, empty intensifiers and stock openers like "in this article".
Rewrite each hit. Don't just delete the word and leave a broken sentence.
Done when: a search for every banned phrase returns nothing.
Models drift into US spelling. On a UK site that means "optimise", "analyse" and "colour" all the way through.
Done when: a spelling check against your convention is clean.
Listen for repeated sentence openings, the same rhythm in every paragraph, and lists of three that appear everywhere.
Done when: you can read the page aloud without wincing.
Check point of view (first person singular, plural or neither), formality and the words the business uses for its own services.
Done when: the business owner would say "that sounds like us".
Google's AI guidance says the manual review also applies to title elements, meta descriptions, structured data and image alt text.
These are easy to skip because readers rarely see them on the page.
Check length, accuracy and whether the snippet would earn a click. Preview it in my SERP snippet preview tool, and see how to write title tags that hold up.
Done when: both fit and describe the page truthfully.
Every value in your markup must match what the page shows. FAQ answers, prices and ratings are the common mismatches.
Build or check it with the schema markup generator, then validate it.
Done when: markup validates and matches the page word for word.
AI-written alt text tends to be keyword lists. Describe what's actually in the image.
Done when: each alt text would make sense read aloud to someone who can't see it.
Google's helpful content guidance calls fabricated creator profiles, such as made-up names or AI-generated headshots, a form of deception.
Name the real person who wrote, edited or is accountable for the page.
Done when: the byline names a real person who stands behind the content.
One page can pass every check and still cause problems next to your other pages.
Batches of AI pages drift towards the same wording. Compare each new page with its siblings and rewrite shared passages.
Done when: no two pages share large blocks of near-identical text.
Search your own site for pages you've already aimed at the same query.
If one exists, merge, differentiate or drop the new page. My guide on avoiding keyword cannibalisation covers how to decide.
Done when: the page has a query no other page on your site targets.
Add links from the new page to related pages, and from at least one existing page to the new one.
The internal linking strategy guide explains which links matter most.
Done when: the page has relevant links in both directions.
Google suggests explaining how content was made where readers would reasonably ask. Decide whether that applies here.
Then get sign-off from the person accountable for the page.
Done when: disclosure is decided and a named person has approved the page.
Not every failed check blocks publishing. Sort what you find into three tiers:
| Tier | Checks | Rule |
|---|---|---|
| Blockers | 1-4, 20, 24 | Don't publish until fixed |
| Must fix before indexing | 5, 9, 10, 17, 18, 22 | Fix now; these decide whether the page can rank |
| Polish | 6-8, 11-16, 19, 21, 23 | Fix in the edit; batch them if time is short |
Accuracy failures always outrank style failures. A clumsy sentence costs you a little. A false claim costs you trust.
Pick the AI draft you're closest to publishing. Run checks 1 to 4 first and fix every failure before you touch the wording.
Then work down the tiers.
If you want to know why this matters and where Google draws the line, read my take on whether AI can write SEO content. For the on-page basics around it, the on-page SEO checklist is the companion.
And if you'd rather not run this by hand on every page, my SEO content writing service builds most of these checks into scripts, with a human edit and your approval on top. It's the same routine, run on every page I write through my automated writing pipeline.
It depends on the page and how good the brief was. The accuracy checks take the longest, because every claim has to be traced to a source. Wording and metadata checks go quickly once you know what to look for. Expect the full checklist to take longer than generating the draft did, which is the point.
Partly. Scripts can catch banned phrases, spelling drift, missing keywords, overlap between pages and broken links. They cannot tell whether a claim is true, whether an example is relevant or whether the page says anything new. Use automated checks to reject weak drafts quickly, and a person to approve the ones that remain.
I don't use them. Google's guidance focuses on whether content is helpful, accurate and made for people, not on how it was produced. A page that passes every check in this list is in good shape whatever a detector says, and a page that fails them is weak even if a detector scores it as human.
Factual accuracy. Google's own guidance on generative AI points out that models predict likely words rather than retrieve facts, so errors are expected. A wrong price, an invented statistic or a false claim about your business does more damage than any structural weakness, and it is the hardest problem for a reader to forgive.
About the author
Kristijan Gjorgjioski
Independent SEO consultant · 6+ years in SEO · 60+ client websites worked on
I'm an independent SEO consultant with 6+ years in SEO. I run audits, migrations and content programmes for businesses in Europe, the UK and the USA, and I build the automation behind my own research.
Book a free 30-minute call. I look at your site first and tell you plainly what I would fix, and in what order.