AI Content Review Checklist: Pre-Publish Guide

Use this checklist on every AI-assisted draft before it goes live. Work through the rows in order, because later checks are wasted if the draft is the wrong article. Record each answer, the named owner and the decision in a review record. The sections after the checklist explain why each row exists and how to run it.

The AI content review checklist

Copy this table into your review record. Each row needs a yes/no answer or a recorded decision, not a general impression.

#	Check	Pass condition	Owner	If it fails
1	Brief match	The draft answers the commissioned topic, target keyword and article type	Editor	Return to the brief or rewrite before any other check
2	Claim inventory	Every name, title, quotation, company, number, date, statistic, age, comparison, cause-and-effect statement and sequence of events is listed	Editor	Do not continue until the list is complete
3	Source for each claim	Each listed claim has a source that states it, linked at the point of use	Editor	Remove, qualify or escalate the claim
4	Source supports the sentence	The linked page says what the sentence says, with the same metric, population and date	Editor	Narrow the sentence to what the source supports, or cut it
5	Numbers and dates	Each figure keeps its metric, population, period and evidence type	Editor	Restate with full context or remove
6	Named fact owner	A named person has signed off every company fact and product claim	Subject owner	Hold the page
7	Helpfulness	The page gives an original point, example, data or explanation a reader cannot get from a generic summary	Editor	Rework the page, or merge it into a stronger page
8	Search intent	The format and depth match what the reader is trying to do	Editor	Rework the structure
9	Overlap	No other page on your site already answers the same question	Editor	Merge, redirect or consolidate
10	Links	Every internal and external link opens, goes to the page it describes and is not a placeholder	Editor	Fix or remove the link
11	Metadata accuracy	Title tag, meta description, structured data and image alt text are accurate to the page	Editor	Correct before publishing
12	Sensitive claims	Health, legal, financial or safety claims have a qualified human approver	Named approver	Hold, do not publish
13	Review record	Version, reviewer, unresolved questions and approval scope are written down	Publisher	Do not publish
14	Decision	The page is marked publish, hold, rework or kill, with a reason	Publisher	Follow the decision in Step 7

These are editorial controls we recommend. They are not a Google requirement, and passing them does not guarantee any search result.

What you are actually reviewing for

Start with the policy question, because it sets how strict the review needs to be. Google’s spam policies describe scaled content abuse as many pages “generated for the primary purpose of manipulating search rankings and not helping users”. They say this typically involves creating large amounts of unoriginal content with little value to users, “no matter how it’s created” (Google Search Central, Spam Policies).

Google’s March 2024 announcement described the same focus: producing content at scale to boost search ranking, “whether automation, humans or a combination are involved” (Google, March 2024 update). The test is not whether a model was involved. It is what each page is for, what it adds, and whether it is one of many pages built for the same ranking purpose.

That sets the limit of this checklist. A passed review means the page is accurate, useful and meets your standards. It does not mean your site is clear of a spam policy issue, and a failed row does not prove spam. An enforcement question is a separate one.

Before you start: what you need

The original brief, including the topic, target keyword and the reader’s task.
The full draft, including metadata fields and image alt text.
Access to every source the draft cites, opened at the time of review.
A named person who can confirm company facts, product details and pricing.
A list of pages already on your site that cover similar questions.
A place to store the review record for each version.

Step 1: Confirm the draft is the article you commissioned

Why this comes first: a well-checked article on the wrong topic wastes the review and can drift away from the keyword you planned for.

Compare the draft’s title, opening paragraph and headings with the brief.
Check that the draft answers the same question and serves the same reader task.
Check that the article type matches. A checklist should contain a usable checklist, not an explanation that points to one.

Output: a yes/no for check 1 and a note on any drift. If the draft has drifted, return it before going further.

Step 2: List every checkable claim, then open its source

Why this matters: AI drafts can state a true-sounding fact with no source, or attach a real link to a sentence the link does not support. Both are invisible until someone lists the claims one by one.

TechTarget’s six-step fact-check method starts with a claim inventory covering names and titles, quotations, company names, numbers including dates, statistics and ages, and sequences of events (TechTarget, fact-checking AI-generated content, 6 August 2024). Add comparisons and cause-and-effect statements, which Trusted AI SEO’s checklist also flags (Trusted AI SEO, 29 January 2026).

Copy every checkable claim into a table with three columns: the sentence, the claim type and the source.
Open each source. Do not rely on the link’s title or a search snippet.
Check that the source states the same metric, population, period and location as the sentence.
Mark each row as supported, narrowed, unsupported or no source.

Trusted AI SEO’s rule for the last case is “no source, no publish”. It is a sound default. Its limit is that a source can exist and still not support the sentence, which is what step 3 above catches.

A labelled hypothetical example of a failed match

This example is illustrative. It is not a real article, customer or measured defect.

A draft says: “Most marketing teams now review AI drafts for accuracy before publishing.” It links to a survey page. When you open the page, the survey asked about one company’s internal policy, in one industry, in one year. It does not report what most teams do.

Field	Entry
Sentence	“Most marketing teams now review AI drafts for accuracy before publishing.”
Claim type	Statistic about a population
Source	Survey page linked in the draft
What the source says	One survey of one industry and year, about a company policy
Result	Unsupported as written
Disposition	Narrowed to what the survey reports, with its industry and year stated, or cut
Reviewer	Editor
Date	Date of review

The disposition matters most. The sentence cannot stay in its original form, and the record shows who decided and why.

What a link does and does not prove

The Tow Center for Digital Journalism tested eight generative search tools on 1,600 queries (20 publishers, 10 articles each, 8 chatbots) in February 2025 and reported results on 6 March 2025. The authors wrote that “collectively, they provided incorrect answers to more than 60 percent of queries” when asked to identify a news article’s headline, publisher, publication date and URL from an excerpt (Columbia Journalism Review, “AI Search Has a Citation Problem”).

That figure measures source identification in a news-attribution task, in generative search products. It is not how often AI-written sentences are factually wrong, and should not be quoted that way. The lesson for your review is narrower: naming a source and the source supporting a sentence are separate tests. A link being present tells you little on its own.

Output: a completed claim table with a disposition for every row.

Step 3: Test whether the page adds anything

Why this matters: a page can be accurate and still not be worth publishing. Google’s people-first content guidance gives self-assessment questions you can use as written (Google Search Central, Creating helpful, reliable, people-first content):

“Does the content provide original information, reporting, research, or analysis?”
“If the content draws on other sources, does it avoid simply copying or rewriting those sources, and instead provide substantial additional value and originality?”

Ask each question of the draft.
Require a specific answer. “Yes, it is useful” is not enough. Name the original element: a worked example, a data point with its source, a decision rule.
If the answer is no, choose rework or merge in Step 7. Do not publish a rewritten summary of other pages.

Output: a written answer to each question, with the specific element named.

Step 4: Check the metadata as facts, not just as fields

Why this matters: many checklists treat the title tag, meta description, structured data and alt text as SEO mechanics. Google says the manual fact-check of AI-generated content “also applies to metadata like <title> elements, meta description elements, structured data, and alternate texts for images, which can appear in Search results” (Google Search Central, generative AI content guidance).

Read the title tag and meta description against the page. Every claim in them must appear in the body and be accurate.
Read any structured data and confirm the values match the visible content.
Read each image’s alt text. It should describe the image accurately, not repeat the keyword.

Output: a corrected metadata set, or a note that no changes were needed.

Step 5: Check intent, overlap and links

Why this matters: an accurate page can still miss the reader’s task or compete with a page you already have.

Intent and format. A how-to should contain steps. A comparison should compare the same attributes across options.
Overlap. Search your own site for pages answering the same question. If one exists, decide whether to merge, redirect or consolidate.
Links. Open every internal and external link. Internal links should point to existing pages that support the sentence, not to a homepage standing in for one. If your site has no suitable page, leave the link out.

If you check a published page afterwards, Search Console’s URL Inspection tool shows Google’s indexed version of a page and can test whether a URL might be indexable (Search Console Help). A successful live test shows the page could be indexed. It is not proof that it is.

Output: notes on intent, overlap and link status.

Step 6: Escalate what the reviewer is not qualified to sign

Why this matters: some claims cost more if wrong, and a general editor should not sign them alone.

Name a person for each kind of claim:

Company facts, pricing, product capabilities and customer results: the person who owns those facts.
Health, legal, financial or safety guidance: a qualified approver chosen by your organisation.
Quotations and personal data: the person who can confirm permission and wording.

Where one of these is unresolved, hold the page. This is a risk-based workflow rule, not a legal or compliance requirement for your sector. Blogo’s guide makes a similar separation between the reviewer for the reader’s task, the owner of company facts and the person who can authorise release (Blogo, AI content review checklist, 7 October 2026).

Output: a named approver for each escalated claim, or a hold.

Step 7: Record publish, hold, rework or kill

Why this matters: a review without a recorded decision cannot be audited later, and “it looked fine” is not a decision.

CopyMate’s checklist ends in an explicit publish, hold or rework decision. It defines hold as “a blocking risk, such as unverified data or missing approval”, and rework as a sound topic whose draft needs material improvement in evidence, usefulness or format (CopyMate, AI Content QA Checklist). The four outcomes below build on those definitions:

Publish: every row passes and the approver has signed.
Hold: a blocking issue is open, such as an unverified claim or missing approval. Fix it, then review again.
Rework: the topic is right, but evidence, usefulness or format needs substantial change.
Kill or merge: the page should not exist as a separate article. Merge its useful parts into an existing page, or remove it.

Keep two judgements apart. “This paragraph failed” is a row-level finding, and the fix is usually an edit. “This page should not exist” is a page-level finding, and the fix is a merge or removal. SERP Mentor, for example, advises cutting or merging page groups that do not earn their place (SERP Mentor, October 2026).

Keep a review record for each version containing:

Article version and date.
Reviewer and approver names.
Each checklist row with its answer.
Unresolved questions.
The decision and its scope, such as “approved for this version only”.

Blogo’s guide describes a similar record: article version, reviewer, unresolved questions and approval scope.

Output: a completed review record with one of the four decisions.

Why a detector score is not a publishing gate

Teams often ask whether an AI detector should decide if a draft goes live. It should not be the gate, and the reason is not that detectors never work.

Results vary sharply by tool. OpenAI’s notice says “as of July 20, 2023, the AI classifier is no longer available due to its low rate of accuracy”. In its own evaluation on an English challenge set, the classifier correctly identified 26% of AI-written text as likely AI-written and labelled human-written text as AI-written 9% of the time (OpenAI). Those are results for one retired tool on one test set, not a general detector error rate.

Later work shows the variation. A September 2025 NBER working paper evaluating several detectors reports that “commercial detectors outperform open-source, with Pangram achieving near-zero FNR and FPR rates” on its corpus (NBER Working Paper 34223). A 2026 EMNLP industry-track study of 135,389 pairs of non-native and native-edited academic manuscripts found false-positive rates for human-written text that “varied widely, from 0.0% to 100.0%” across 13 detectors (Park, Jeong & Kim, ACL Anthology). That population is academic manuscripts, not marketing drafts.

The stronger reason is that a detector answers a question about authorship, while a pre-publication review must answer questions about accuracy, usefulness and ownership. A score cannot tell you whether a claim is true, whoever wrote it. A 2023 study by Liang and colleagues also found that the detectors it tested consistently misclassified non-native English writing samples as AI-generated (arXiv:2304.02819). If writers on your team work in a second language, a score-based gate may create a fairness risk. That is a risk to weigh, not an established result for your team.

Recommendation: do not make a detector score the only condition for publishing. Use the claim, source, usefulness and approval checks above.

What this checklist cannot do

Guarantee rankings, traffic or AI citations. Publishing a reviewed page does not produce any of them on its own.
Make a policy finding. A passed review is an editorial decision, not clearance under Google’s spam policies.
Verify a claim with no source. If nothing supports a sentence, remove it or qualify it.
Catch every defect. CopyMate notes that automated checks cannot judge every quality question, such as whether a page deserves to exist. A named human still has to make that call.

Run it on your next draft

Apply the checklist to your next AI-assisted draft and keep the review record. After five to ten reviews, count which rows failed most often. Those rows show where your drafting process needs to change, and they give you your own evidence to act on.

Once your review passes are running, the checklist gives you a consistent structure for each draft. review record Reviewing which rows fail most often turns routine checks into evidence for fixing your drafting process.