How to Fact-Check AI-Generated Blog Posts Before You Publish

You don’t need a dedicated fact-checker to catch unsupported statistics, outdated product promises, and citations that don’t support the sentence beside them. You need a review process that sends each kind of claim to the right evidence and gives someone responsibility for the final decision.

For a small team, we recommend three review lanes: external factual claims, product details, and low-risk copy edits. Resolve the first two before polishing the third. Keep the evidence in a simple claim log, and hold publication whenever an unresolved claim is essential to the article’s advice.

Separate evidence checks from copy edits

Your AI content style guidelines should define the rules for evidence, voice, and approval. This workflow turns those rules into decisions on an individual draft.

Start by classifying what needs attention. The examples below are hypothetical.

Prioritize by consequence within each lane. A misplaced comma and an unsupported security certification shouldn’t compete for the same attention. Route legal, medical, financial, or security advice to someone qualified to approve it; a general editor shouldn’t guess.

Watch for edits that change lanes. Replacing “supports exports” with “automatically exports all your data” introduces new product claims. That sentence needs verification again, even if the change began as a readability fix.

Build a claim log before opening more tabs

Extract the assertions a reader could test

Read the draft once for meaning. Mark statistics, quotations, dates, feature descriptions, comparisons, and statements about what causes an outcome. Include first-person stories: “We increased conversions” needs an actual record of what happened.

Split compound sentences. “The integration syncs instantly and is available on every plan” contains separate claims about speed and availability. Evidence for one doesn’t establish the other.

You can ask AI to help identify candidates with this prompt:

Extract externally verifiable claims from this draft. Copy each claim exactly and classify it as an external fact or product detail. Flag statistics, quotations, absolute wording, and claims of firsthand experience. Suggest the evidence needed, but do not invent sources or mark anything verified. Return review notes separately from the article.

Then read the draft yourself to catch omissions. An extraction pass is useful preparation; it doesn’t replace checking the underlying evidence.

Keep one record per claim

A shared document or spreadsheet is enough. Use these fields:

• Exact claim and its location in the draft.

• Review lane and consequence if wrong.

• Source URL or internal record, plus the supporting passage.

• Source date and relevant scope, such as plan, population, or measurement period.

• Reviewer, status, and approved final wording.

Copy this table into your log. The completed row is illustrative: the evidence passage comes from Google’s guidance cited in the copy-editing section below, but the draft claim, reviewer, and decision are examples, not a record of an actual review.

The writer gathers evidence. The editor checks whether it supports the wording. A product owner or specialist handles questions outside the editor’s expertise. One person may fill multiple roles, but every unresolved item still needs an owner.

Don’t log every transition or clearly labeled recommendation. “We recommend a shared spreadsheet” describes the proposed workflow. “A shared spreadsheet reduces review time by 40%” requires measurement.

Check whether the source supports the sentence

Open the original evidence

Follow each citation and read the relevant passage in context. A working link establishes that a page exists; you still need to establish that it supports the claim.

Prefer original research for statistics, official documentation for platform behavior, and the original recording or transcript for quotations. If a blog cites a survey, follow the trail to the survey. A search snippet is a lead to investigate, not enough evidence for a detailed assertion.

Check who published it, when the underlying information was collected, and what it actually covers. A credible source can still be the wrong source for your sentence. Research about large enterprises doesn’t automatically support advice framed as a finding about small US startups.

Preserve the limits of numbers and quotations

For a statistic, record the measured population, timeframe, and metric. Recalculate derived numbers. A rate moving from 10% to 12% rises by two percentage points, or 20% relative to the starting rate; those descriptions aren’t interchangeable.

Consider this hypothetical draft sentence:

AI writing tools double productivity for marketing teams.

Suppose the supplied study instead says that 24 of 40 surveyed marketers reported spending less time drafting. An accurate rewrite would be:

In the survey, 24 of 40 marketers reported spending less time drafting when using AI writing tools.

That preserves the sample and self-reported outcome without inventing a productivity measurement or claiming causation. These numbers illustrate the edit; they aren’t research findings to cite.

For quotations, compare the wording with the original and read the surrounding discussion. Preserve qualifications. If you can verify the meaning but not the exact words, write an attributed paraphrase without quotation marks.

Resolve missing or conflicting evidence

When sources disagree, first compare their definitions, dates, and populations. They may describe different things. If the conflict remains, ask the responsible specialist or remove the disputed assertion.

There’s no universal freshness cutoff. Check current pricing against current plan information; assess older research according to whether its methods and context still support your point.

If you can’t access the underlying evidence, find an accessible source supporting a narrower statement. Remove optional claims that remain unsupported. Hold the draft when the missing evidence undermines its central recommendation. Adding “may” to a baseless promise doesn’t fix the evidence gap.

Product details need a different evidence trail

Verify the exact promise

Use current product documentation and plan information for feature claims. For instructions, test the described path in the relevant product version when possible. Confirm prerequisites: a workflow available after configuration shouldn’t be described as working immediately for everyone.

Pay particular attention to words such as “all,” “unlimited,” “automatic,” and “guaranteed.” They expand the promise. A screenshot showing an export button, for example, doesn’t prove that exports are unlimited across every subscription.

If the interface, help article, and pricing page conflict, get the product owner to resolve the discrepancy. Record the approved wording and its scope. For certifications, compliance statements, or data-handling commitments, obtain approval from the responsible specialist.

Give the writer approved company context

In ProjectHQ, you can add product documentation, approved messaging, and editorial rules to our knowledge base using URLs, PDFs, or pasted text. Keep that source pack current and remove superseded material so the writer isn’t working from conflicting instructions.

Our AI Article Writer draws on that company knowledge during drafting. In the editor, you can ask the agent to revise a section or add a source without restarting the article. Use those revisions to address specific review findings, then check the changed wording yourself.

For the next assignment, put the approved sources and the product reviewer’s name into your SEO content brief. That gives the writer a usable evidence trail before drafting begins.

Copy editing comes after factual fixes

Once the claims are resolved, review voice, grammar, structure, and formatting. Tighten the opening. Remove repetition. Make instructions easier to follow. Preserve every qualification the evidence review required.

Extend the check beyond the body. Google’s guidance on generative AI content calls for accuracy, quality, and relevance in metadata as well, including titles, meta descriptions, structured data, and image alt text. A careful paragraph doesn’t justify an exaggerated headline.

Open the final preview and check that citations sit beside the claims they support, links reach the intended pages, and captions don’t introduce new promises. Remove review notes and placeholders. If a late rewrite changes a number, capability, or outcome, return that sentence to its evidence lane.

Keep the questions separate when using automated checks: an assessment of originality or AI authorship does not establish whether a factual assertion is true.

The publish-or-hold checklist

Before publication, the named reviewer should be able to confirm all of the following:

• Consequential factual claims have evidence supporting their exact wording.

• Product details match the approved version, plan, and conditions.

• Statistics and quotations preserve their original context.

• Hypothetical examples are labeled, and firsthand claims have real records.

• The final headline, metadata, and body use consistent, supportable wording.

• No unresolved factual blocker remains.

Use four outcomes in the claim log: approved, narrowed and rechecked, removed, or blocked. A central or high-consequence blocked claim holds publication until it’s resolved.

Save the reviewer’s name, approval date, and final draft version together. Apply this process to your next post in a shared document before buying another review tool. You’ll have a concrete record of what was checked, what changed, and who approved the article readers actually see.