Testing suggests Google’s AI Overviews tell millions of lies per hour

Is 90 percent accuracy good enough for a search robot?

Looking up information on Google today means confronting AI Overviews, the Gemini-powered search robot that appears at the top of the results page. AI Overviews has had a rough time since its 2024 launch, attracting user ire over its scattershot accuracy, but it’s getting better and usually provides the right answer. That’s a low bar, though. A new analysis from The New York Times attempted to assess the accuracy of AI Overviews, finding it’s right 90 percent of the time. The flip side is that 1 in 10 AI answers is wrong, and for Google, that means hundreds of thousands of lies going out every minute of the day.

The Times conducted this analysis with the help of a startup called Oumi, which itself is deeply involved in developing AI models. The company used AI tools to probe AI Overviews with the SimpleQA evaluation, a common test to rank the factuality of generative models like Gemini. Released by OpenAI in 2024, SimpleQA is essentially a list of more than 4,000 questions with verifiable answers that can be fed into an AI.

Oumi began running its test last year when Gemini 2.5 was still the company’s best model. At the time, the benchmark showed an 85 percent accuracy rate. When the test was rerun following the Gemini 3 update, AI Overviews answered 91 percent of the questions correctly. If you extrapolate this miss rate out to all Google searches, AI Overviews is generating tens of millions of incorrect answers per day.

The report includes several examples of where AI Overviews went wrong. When asked for the date on which Bob Marley’s former home became a museum, AI Overviews cited three pages, two of which didn’t discuss the date at all. The final one, Wikipedia, listed two contradictory years, and AI Overviews confidently chose the wrong one. The benchmark also prompts models to produce the date on which Yo Yo Ma was inducted into the classical music hall of fame. While AI Overviews cited the organization’s website that listed Ma’s induction, it claimed there’s no such thing as the Classical Music Hall of Fame.

Google doesn’t much like this test. Google spokesperson Ned Adriance tells the Times that Google believes SimpleQA contains incorrect information. Its model evaluations often rely on a similar test called SimpleQA Verified, which uses a smaller set of questions that have been more thoroughly vetted. “This study has serious holes,” Adriance told the Times. “It doesn’t reflect what people are actually searching on Google.”

Benchmark problems

Evaluating new AI models sometimes feels more like art than science, which is part of the problem. Every company has its own preferred way of demonstrating what a model can do, and the non-deterministic nature of gen AI can make it hard to verify anything. These robots can get a factual question right and then completely miss it if you rerun the query immediately. Oumi even uses AI tools to run its assessments, and those models can hallucinate, too.

The other wrinkle is that AI Overviews isn’t a single monolithic model. Google told Ars Technica that it uses the “right model” for each query. While AI Overviews would get the best answers from always running Gemini 3.1 Pro, that’s slow and expensive. To load things promptly on a search page, the overview uses faster Gemini Flash models when possible (which appears to be most of the time).

Google’s response to this report is telling. In the realm of AI factuality, 9 out of 10 isn’t even that bad. Google has recently published benchmarks for new model releases featuring measurements of factuality in the range of 60 to 80 percent—these tests are run without tools like web search. Grounding an AI with more data, like the wealth of human knowledge on the Internet, does make it more accurate than the naked model itself. However, the truth is in the blue links somewhere, and AI Overviews encourages people to accept its sometimes inaccurate summaries instead of checking those sources manually.

While Google says the Times’ results don’t match what people see, you have to wonder how the company could even know that. You’ve probably seen mistakes in AI Overviews—we all have because that’s just how generative AI works. As Google itself reminds you at the bottom of every overview: “AI can make mistakes, so double-check responses.”

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Posted Wednesday 8 April 2026 at 5:24 am AEST (my time).

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