Google Says Fact-Check AI Content, Metadata Included

Your site's business hours are wrong in the schema. The meta description promises a "free consultation" you stopped offering in the spring. An image on the services page has alt text describing a different service entirely. Nobody typed any of it on purpose. A tool wrote it, it looked fine, and it shipped.

Google just put that scenario in writing, and it did it in a short sentence.

What changed on October 1

The guidance on generative AI content has always allowed AI-assisted writing. What's new is the verb. Google now says it's critical to manually fact-check and review AI-generated content before publishing, and the coverage I found agrees the review reaches past the article body into the small stuff: the title tag, the meta description, structured data, and alt text.

Why the small stuff? Because that's where AI gets used without anyone calling it "AI content." Nobody thinks of a plugin that auto-fills image descriptions as a content strategy. It is. Every one of those fields is text a model can get wrong, and several of them are read by machines first and humans never.

The reason Google gave is plain. A language model doesn't look anything up. It predicts what words are likely to come next. Sometimes the likely words happen to be true.

Why the metadata is the risky part

Body copy gets read. Somebody on your team skims the blog post before it goes up, or at least feels guilty about not doing it. Metadata gets no such courtesy.

Think about what a typical small-business site now has generated for it:

• Title tags and meta descriptions, batch-written by an SEO plugin across every page at once.
• Alt text, filled in by a tool that "sees" the image and guesses.
• Schema markup, drafted by a chatbot from a prompt like "write LocalBusiness JSON-LD for my shop."
• Service-page blurbs and FAQ answers, drafted in one afternoon and never looked at again.

Each one is a place where a confident wrong answer can sit for a year. And the readers of those fields include Google's systems and the AI tools that quote your pages. A wrong hour in schema doesn't embarrass you in front of one visitor. It gets repeated. We've written about how AI tools get business hours wrong even when the facts are available; feeding them a wrong version yourself makes that worse.

A review pass that takes an hour, not a week

You don't need a committee. You need a list and a rule: a human who knows the business checks every machine-written field against reality.

Here's the version I'd run on a small site.

1. Inventory what a tool wrote. Open your SEO plugin, your image library, and your schema output. If you can't say who or what wrote a field, treat it as machine-written.
2. Check the facts that cost you money first. Hours, phone number, service area, prices, what you do and don't offer, guarantees. These are the claims a customer will act on.
3. Read titles and meta descriptions in a list. Most plugins can export them. Scan the column in one sitting and you'll spot the wrong ones fast, because wrong ones sound like a stranger describing your business.
4. Compare schema to the visible page. Structured data should say what the page says. If the JSON-LD says Saturday hours and the footer says closed Saturday, one of them is lying. Our schema audit post covers how to run that comparison without guessing.
5. Spot-check alt text against the image. Ten images is enough to learn whether your tool is any good.
6. Write down the date. Put it in the log. When a fact changes next quarter, you'll know which fields to re-check.

Notice what's missing: no AI-detector, no scoring tool. The check is a person comparing text to the truth. Software can't do that part, because the truth lives in your head and your price list.

Shortcuts that won't pass for review

• Running AI text through a second AI "to fact-check it." A model grading a model's homework shares the same blind spot: it doesn't know your hours either.
• Paying for an AI-detector. Google's sentence is about accuracy, not about whether a tool wrote the text. Whether something sounds machine-made tells you nothing about whether it's correct.
• Deleting everything and starting over. Nobody asked for that. The guidance asks for a checkpoint before publishing, not a ban.
• Skimming only the blog. The riskiest text on your site is usually the stuff nobody thinks of as writing.
• Treating this as an SEO trick. Accurate information is also what AI answer engines need when they decide what to quote. It belongs with the rest of getting cited in AI answers, not in a separate compliance pile.

It's also worth keeping in proportion. This is a documentation update, not a ranking-system change, and nothing in the coverage I found says it triggers a penalty by itself. It tells you what Google considers the minimum standard for AI-assisted publishing. If your site already has a person checking facts before anything goes live, you've been meeting it.

FAQ

Does Google ban AI-generated content?

No. The October 1 update asks publishers to fact-check and review AI-generated content before publishing it. It doesn't prohibit using AI to help write.

What exactly did Google add on October 1, 2026?

Per the trade press, a line saying it is critical to manually factcheck and review all AI-generated content for accuracy and trustworthiness before publishing, along with an explanation that generative models predict likely word sequences rather than retrieve facts. The review is described as covering titles, meta descriptions, structured data, and alt text too.

Does this apply if I only used AI for a first draft?

Yes, in spirit. Anything a model produced and a human then published should have a person confirm the facts in it. A light edit for tone doesn't count as a check on the claims.

Will my site be penalized for not fact-checking?

Nothing I found says this update creates a new penalty. It reads as a statement of expectations in Google's documentation. The practical risk is simpler: wrong information on your site gets read, repeated, and acted on by customers and by AI tools.

Is alt text really worth reviewing?

Yes. It's easy to ignore because it's invisible on the page, and tools that auto-generate it can describe the wrong thing with total confidence. Ten minutes comparing it to the images will show you how reliable your tool is.

How often should I run this check?

Run it once now for everything machine-written, then again whenever a business fact changes, such as hours, prices, or services, and before publishing anything new.

If a review pass like this is more than you can fit in a week, that is the kind of job we take on under website care: someone checks the fields that matter, and you hear about it when something's wrong.