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Before publishing AI-generated or AI-assisted content, manually verify every material factual claim—including claims in headings, page titles, meta descriptions, structured data and image alt text. Google Search Central says it is “critical to manually factcheck and review all AI-generated content for accuracy and trustworthiness before publishing.” Treat the draft as a starting document, not evidence: a fluent sentence can still be wrong.
Why AI-generated content needs a human fact-check
Generative models predict likely sequences of text; they do not reliably retrieve and verify facts as they write. An answer may sound confident while getting a date, quotation, statistic, attribution or causal explanation wrong. Google’s guidance is not a blanket ban on AI use: the concern is whether content is useful, reliable and created for people, rather than primarily to manipulate Search rankings. Google also says its systems place greater emphasis on reliability for topics where information quality is critically important, including health, civic and financial information. Apply especially careful scrutiny to consequential claims without treating that guidance as a substitute for professional or legal standards. Google’s 2023 AI-content guidance
1. Pull out the claims that need checking
Read the whole piece and mark statements that could be true or false. Do not limit the pass to the body: check headings, summaries and all metadata that may appear in Search. Give particular attention to claims that readers are likely to rely on or that shape the article’s main conclusion.
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- Dates, names, roles, organizations and locations.
- Numbers, percentages, rankings and descriptions of who or what a statistic covers.
- Quotations and claims about what a person, organization, policy or product said or does.
- Cause-and-effect statements, comparisons and claims that generalize from a specific case.
- Image descriptions, captions, structured data, page titles and meta descriptions.
The International Fact-Checking Network says signatories select claims primarily according to reach and importance and explain their choices where possible. Use that principle to prioritize effort, but verify every material claim on which the article depends. IFCN Code commitments
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2. Trace each important claim to evidence
Open the source behind a claim; do not trust an AI-generated citation, link description or summary without checking it. Prefer an appropriate primary source—such as an official document, dataset, transcript or direct statement—when one is available. If the claim depends on secondary reporting, make that basis clear and look for independent corroboration where practical. A source link is useful only if it supports the precise wording and scope of the claim.
For a working record, use a table like this. It is an editorial aid, not a form Google requires.
| Record | What to note |
|---|---|
| Claim as written | The exact sentence or discrete factual assertion. |
| Source and date | Publisher, document or page, and publication or update date when available. |
| Supporting evidence | The exact passage, table, dataset or other evidence that bears on the claim. |
| Counterevidence and caveats | Conflicting evidence, limits, definitions, population, geography or time period. |
| Outcome | Keep, revise, qualify or remove; note confidence and any follow-up needed. |
This record makes it easier for another editor to retrace the check. IFCN commitments emphasize significant, transparent sources and methods, as well as evidence readers can inspect. IFCN Code commitments
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3. Look for corroboration and evidence against the claim
For key claims, seek another named source where possible. Check evidence that supports the statement and evidence that might undermine it; use the same standard regardless of who made the claim. If sources disagree, do not quietly choose the most convenient one. Explain the conflict or narrow the wording to what the evidence establishes.
Preserve the boundaries of the original evidence. A statistic should retain its population, date, location and publisher; a result from one group or period does not automatically describe everyone or the present. The IFCN’s standards address multiple sources, counterevidence and consistent assessment, and call for disclosure of relevant source interests. IFCN Code commitments
4. Verify quotations, attribution and source context
Compare quotations with the original recording, transcript or document where possible. Confirm the speaker’s identity and role at the time, and preserve enough surrounding context to avoid changing the meaning. For a statistic or policy description, check that the source actually says what the draft attributes to it.
Consider whether a source has an interest readers would reasonably want to know about. Google recommends clear sourcing and accurate authorship, and warns against inventing author credentials. A polished biography or confident attribution generated by AI is not verification. Google’s guidance on helpful, reliable, people-first content
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Google’s tools can help locate context, but they do not make the editorial decision for you. Google’s overview of Search tools for checking facts, images and sources describes several useful starting points:
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- Fact Check Explorer: Search for existing fact-checks related to a claim or image. An existing check is a lead to inspect, not automatic proof that a different claim is settled. Google product manager Nidhi Hebbar wrote that “Fact Check Explorer helps journalists and fact-checkers dig deeper into a topic.”
- About this image: Depending on what is available, Search may show when an image or similar image was first seen, earlier appearances on other pages, how sites describe or use it, and creator-supplied metadata. These details can help establish context, but they do not authenticate every image conclusively.
- About this result or page: Source-background information can help you decide what to investigate next. It does not prove an individual claim on that source’s page.
Google’s 2023 summary of a Poynter Institute MediaWise study said seven in ten respondents were not totally or very confident in their ability to tell whether online images were authentic and reliable. That finding concerns confidence about online images; it is not a measure of AI-written text, detector accuracy or all internet users. Google’s 2023 overview of image and source checks
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.6. Keep media provenance separate from factual accuracy
Signals about where a file came from or how it was edited answer a different question from whether its claims are true. In a May 19, 2026 announcement, Google described SynthID checks for images, video and audio, C2PA Content Credentials for information about whether content is an unaltered camera original or has been modified and by which tools, and an enterprise AI Content Detection API with fact-checking and labeling use cases. These features concern origin, alteration or detection; they do not establish that a factual sentence, statistic or claim is true. Check current documentation before relying on availability: the announcement described expansion and rollout, not universal access across readers, regions and media types. Google’s May 2026 announcement on content origin and editing information
A detector score is not proof of who wrote a passage or whether it is accurate. The cited product announcement does not establish independent accuracy rates across languages, genres or levels of editing. For factual claims, return to evidence that can be inspected and assessed.
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If evidence does not support a claim, remove or rewrite it. If the evidence is mixed, limited to a particular time or place, or still developing, qualify the wording rather than making it sound universal or settled. Keep source links and editorial notes that allow another person to reproduce the check.
When AI substantially contributed to an article, consider whether readers would reasonably want to know how it was used and why. Google recommends providing that context where it would be useful; keep any disclosure accurate and proportionate rather than implying a human verified work that was not checked. If an error is confirmed after publication, correct it openly and, where possible, help readers who saw the original find the corrected version. Google’s guidance on helpful, reliable, people-first content IFCN Code commitments
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