Google’s AI Overviews are right about nine times in ten, according to an independent study. At Google’s scale, even a small error rate adds up to millions of wrong answers. Some of them are about your brand. Auditing Google’s AI Overviews for brand accuracy is now a legal function as much as an SEO task, and most teams have no checklist for it. This one is built for brand and legal teams.
Why a wrong AI answer is now your problem
The Oumi study, covered by The Decoder, found that AI Overviews were correct 85 percent of the time with Gemini 2 and 91 percent with Gemini 3. Accuracy rose. Verifiability fell. With Gemini 3, 56 percent of correct answers were “ungrounded”, meaning the linked pages did not fully support them.
Read that twice. Even a right answer may cite a source that doesn’t back it up. If your legal team asks “where did Google get that claim about our product?”, the honest answer is often “nowhere you can point to.”
Then there’s the liability shift. A Munich court issued a preliminary injunction against Google after two German publishers were falsely portrayed as involved in scams. The court treated AI Overviews as Google’s own statements, not a neutral list of third-party links. It also noted that Google did not promptly stop similar claims after a cease-and-desist letter.
The detail that matters for brands: the court leaned on what happened after notice. A documented, dated complaint is the asset that turns a nuisance into a claim.
One caveat. This is a German preliminary ruling, not US law. US outcomes will turn on different doctrines, and nothing here is legal advice. But it tells you which evidence will matter everywhere: proof of the false statement, proof you told Google, and proof of what Google did next.
Step one: build a query set you can defend
Random spot checks won’t survive scrutiny. Build a fixed, versioned query list and run it on a schedule.
- Brand and product names, including common misspellings and abbreviations.
- Brand plus risk terms: “scam,” “lawsuit,” “recall,” “side effects,” “complaints,” “legit.”
- Comparison queries: “[Brand] vs [competitor],” “best [category].”
- Executive and founder names, plus named spokespeople and key creators.
- Transactional facts: pricing, return policy, warranty, ingredients, shipping, locations, hours.
Run each query in several locations and devices. Overviews vary by user, so a single screenshot from your laptop proves little. Log the date, time, location, account state (logged in or out), and the full text of the answer.
Creator-adjacent queries deserve their own bucket. If a partner’s name now surfaces next to a false claim about your product, you have a contract question too. Your morality clause triggers may or may not cover it, so check before you need them.
The risk classification that drives escalation
Not every error deserves a lawyer. Sort each finding into a tier.
- Tier 1, defamatory or safety-related. Claims of fraud, illegal conduct, health harm, or false recalls. Escalate to counsel the same day.
- Tier 2, material factual errors. Wrong pricing, false guarantees, invented features, incorrect eligibility. These can mislead purchasers and generate complaints aimed at you.
- Tier 3, stale or incomplete. Old store hours, discontinued products, outdated leadership. Fix through content and Business Profile updates.
- Tier 4, competitive framing. Unflattering but accurate comparisons. Usually not actionable.
Why does materiality matter? Because the same logic regulators apply to your own advertising applies to how you judge a third party’s mistake. Why does materiality matter? Because regulators ask whether a claim is likely to mislead reasonable consumers and whether it affects their purchasing decisions. Apply that same lens when you rank what you find. Use that test to rank what you find.
Is the false claim actually yours?
Here’s the trap many teams miss. Sometimes the AI Overview is wrong because your own content is wrong, vague, or contradicted across channels.
Before you blame Google, audit the inputs:
- Does your site say one thing on the product page and another in the FAQ?
- Did a creator post an offhand claim (“works in 3 days”) that now circulates as fact?
- Are old press releases or affiliate pages still live with outdated terms?
- Do third-party sources Google favors, such as Reddit threads or Facebook posts, contain the error? The Decoder reported that Facebook and Reddit ranked second and fourth among the 5,380 sources Google cited in the Oumi study.
That last point changes your remediation plan. If the origin is a forum post, a takedown request to Google won’t fix the root cause. This is also where creator contracts earn their keep. Tight caption clause indemnities and a clean licensing rights audit help you trace and correct claims that originated in sponsored content.
Evidence, notice, and escalation: the paper trail
Treat every Tier 1 and Tier 2 finding like a future exhibit.
- Capture. Full-page screenshot plus screen recording, with visible timestamp and URL. Save the raw text.
- Preserve sources. Archive the pages the Overview cites. Note any that don’t support the claim.
- Report in-product. Use the feedback option on the Overview and record the submission time.
- Send formal notice. For Tier 1, have counsel send a written notice through Google’s legal removal channels. Keep delivery proof.
- Re-test. Rerun the same queries after 48 hours, one week, and 30 days. Log whether the claim persists, mutates, or returns in similar form.
- Escalate on persistence. Repetition after notice is the pattern the Munich court found significant.
One practical point. Claims mutate. A court order or a fix on one phrasing doesn’t stop a near-identical sentence, so your re-test queries should include paraphrases.
What about your own use of AI answers?
Auditing outward is half the job. If your team quotes AI Overviews in sales decks, or lets chatbots and shopping assistants state product facts, you inherit the same accuracy risk in your own voice. See how AI chatbot product recommendations raise FTC disclosure questions, and how state UDAP exposure attaches to assistants that speak for a brand.
Section 5 of the FTC Act applies to AI-related claims, and Lanham Act plaintiffs can seek preliminary injunctions, so ask your counsel how both apply to your case. If a competitor’s marketing feeds a false comparison into AI answers, that private right of action is a lever. If your marketing feeds one, it’s a risk.
Fixing it at the source: content hygiene
You can’t edit Google’s answer, but you can shape what it draws on.
- Publish one canonical, plainly worded facts page for pricing, policies, and product specs.
- Keep structured data and Google Business Profile current.
- Answer risk-term queries directly (“Is [Brand] legit?”) with verifiable proof.
- Align creator briefs so sponsored posts repeat only approved claims.
Related work on extraction and disclosure is covered in our piece on GEO content disclosures. And if creators’ work is being summarized without credit, the creator copyright gap is the companion issue.
One more business reason to care: Pew Research data, cited by Malwarebytes, shows clicks to traditional results drop from around 15% to about 8% when an AI Overview appears. Fewer people click through to correct the record on your own site. The Overview often is the whole story.
Next step
This week, build your 30-query brand set, run it across three locations, and log every finding in a shared sheet with a tier rating. Send the Tier 1 and Tier 2 results to counsel with screenshots attached.
FAQs
Can a brand sue Google over a false AI Overview?
It depends on jurisdiction. A Munich court granted a preliminary injunction in a case brought by two publishers, treating the Overview as Google’s own statement. That ruling is not binding in the US, where outcomes will depend on different doctrines. Talk to counsel before assuming a claim exists.
How often should we audit AI Overviews for brand accuracy?
Monthly for your core query set, weekly during launches, recalls, or crises. Re-test any flagged error at 48 hours, one week, and 30 days.
How do we report an inaccurate AI Overview to Google?
Use the in-product feedback option on the Overview for general errors, and record when you submitted it. For defamatory or legally actionable claims, have counsel file through Google’s legal removal process and keep proof of delivery.
What evidence should we keep?
Timestamped screenshots and screen recordings, the full text, the location and account state used, archived copies of cited sources, and every notice sent. Also keep re-test results, since persistence after notice is what strengthens a claim.
Could our own content be causing the error?
Yes, often. Conflicting pages, old press releases, and offhand creator claims can all feed a wrong answer. Audit your owned and sponsored content before blaming the platform.
Who should own this audit?
Make it a shared process. Brand or SEO runs the queries, legal triages Tier 1 and Tier 2 findings, and the creator partnerships team checks whether sponsored content is the source.
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