Charted: AI Articles Have Overtaken Human Written Ones
Mapped: The States Where Businesses Use AI Most
Ranked: The Smartest AI Models of 2026
Ranked: AI Models U.S. Businesses Pay For
Ranked: The Companies That Sell the Most AI Chips
Ranked: The World’s 50 Largest Banks by Assets
Every S&P 500 Company in One Giant Chart
SpaceX’s IPO Would Make It a Top 10 Company Globally
Charted: The Global Stock Selloff as Oil Fears Rise
Warren Buffett vs. the S&P 500: Growth of $100 (1965–2025)
Mapped: Where Housing Takes the Biggest Share of Income
Mapped: Which States Give More to Washington Than They Get Back
The $126T Global Economy in One Giant Chart
Charted: U.S. Debt Could Hit $182 Trillion by 2056
Mapped: Most Americans Can’t Afford New Homes
Mapped: Europe’s Social Media Gap by Country
Mapped: Social Media Use Among Europe’s Youth
Charted: AI Articles Have Overtaken Human Written Ones
Mapped: The States Where Businesses Use AI Most
Ranked: The Smartest AI Models of 2026
How Government Debt Has Diverged Across Major Economies (2005–2025)
Ranked: Where Wages Go Furthest Around the World
The $126T Global Economy in One Giant Chart
Charted: U.S. Debt Could Hit $182 Trillion by 2056
Where the World’s $13T in Sovereign Wealth Is Held
Mapped: The U.S. Is Split on Legal Marijuana—Here’s Where
Mapped: Life Expectancy by U.S. State
Mapped: U.S. States With the Highest Diabetes Rates
Mapped: Adult Obesity Rates Across All 50 U.S. States
Ranked: The World’s 10 Deadliest Viruses by Fatality Rate
Charted: The Global Fertility Divide
Ranked: Where the World’s Migrants Live Today
Mapped: Europe’s Social Media Gap by Country
Mapped: Every Country’s Fertility Rate as Births Decline Worldwide
Mapped: Europe’s Birth Rate Collapse
Ranked: The Fastest-Growing Battery Materials Since 2020
China Produces More Coal Than the Rest of the World Combined
Coal Still Generates More Electricity Than Any Other Source
Ranked: The World’s Biggest Coal Consumers
Ranked: Global Helium Production by Country
Mapped: Where Housing Takes the Biggest Share of Income
Mapped: Which States Give More to Washington Than They Get Back
Mapped: Most Americans Can’t Afford New Homes
Mapped: The U.S. Is Split on Legal Marijuana—Here’s Where
Mapped: Every Country’s Fertility Rate as Births Decline Worldwide
These Countries Hold Most of the World’s Copper
Ranked: Central Banks Buying and Selling Gold in 2026
Ranked: U.S. Import Reliance for 37 Critical Minerals
Visualizing the Critical Minerals Powering the AI Boom
Ranked: The Critical Minerals Lost to U.S. Mining Waste, by Tonnage
Ranked: Where Emissions Are Rising Fastest
How Much Clean Energy Have Countries Added Since 2015?
Mapped: Only One Country Can Feed Itself Fully
Ranked: The Countries Building the Most Nuclear Power
Ranked: CO2 Emissions Per Person by Major Economy
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Does your AI always give you the right answer? Unfortunately, its “truth” may be an illusion.
This infographic breaks down AI hallucination rates by model. It’s a preview of the brand-new executive guide from Terzo and Visual Capitalist, AI’s Illusion of Truth: The Data Behind AI Errors.
An “AI hallucination” refers to cases where a language model presents information as fact even though it is false or ungrounded.
These hallucinations happen because standard training systems reward guessing over showing uncertainty. Think about it this way: if you guess on a multiple choice test, you are more likely to get it right than if you give no answer.
To measure AI hallucination rates, researchers presented models from leading AI companies with news excerpts. They then asked the models to identify the original article, publication, and URL.
Notably, the researchers specifically chose excerpts that, if pasted into a traditional Google search, returned the original source within the first three results.
The models’ responses were then checked for accuracy. Below, the table shows how often each model got an answer partially or entirely incorrect.
Source: Columbia Journalism Review, March 2025. Responses where no answer was provided were not considered a hallucination.
Grok‑3 had the worst performance, hallucinating 94% of the time. Perplexity, by contrast, delivered the most accurate answers.
Notably, paid models fared worse than their free counterparts. Most models failed to express any uncertainty in their answers, despite frequent errors.
For company executives, the takeaway is clear. It’s risky to take an AI model’s answers at face value. Assuming output is accurate without verification can lead to many negative outcomes:
With AI agents, where every action builds on the last, the consequences of AI hallucination can compound quickly. That’s why leaders need strategies to keep humans in the loop, verify output, and use a model that’s built on trusted company data.
See the data behind AI’s errors and how to get 99% accuracy in the free executive guide, AI’s Illusion of Truth.
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