Presented by Verif
Americans can’t reliably distinguish real from AI-generated content, and this isn’t just a problem of media literacy; This is a direct threat to the way businesses verify identities online.
New research shows that although many people know about deepfakes, their ability to distinguish them from reality is barely better than flipping a coin. A 2026 survey conducted by Verif and Kantar among 3,000 respondents in the United States, the United Kingdom, and Brazil shows that Americans scored only 0.07 on that scale where 0 represents a random guess.
If people cannot distinguish authentic visual content, they cannot reliably distinguish authentic identity. In practice, this means that the same users interacting with digital services are often unable to tell whether the person on the other side of the screen is real or not.
That ineffectiveness has direct consequences for every digital business that relies on image and video-based identity verification to confirm who is on the other side of the screen. This includes everything from customer bank onboarding and account recovery to marketplace seller verification, high-value ecommerce transactions, social platform authentication, and enterprise access control.
In the US, those consequences are already significant – synthetic identity fraud now causes billions in losses annually, and the tools to generate credible fakes are now widely accessible.
The report also identifies a small but high-risk group: about 7% of users who perform poorly at detecting deepfakes, yet are confident in their ability and rarely verify what they see. Although this is small as a percentage, on a larger scale it represents millions of accounts that are highly exploitable targets for fraud.
If users cannot reliably distinguish real identity from synthetic identity, any system that relies on visual verification is fundamentally exposed. Identity verification can no longer be treated as a compliance function; Instead, it should be built as core digital infrastructure.
“Now that AI-generated content is becoming indistinguishable from reality, the human eye alone is no longer a reliable line of defense,” says Ira Bondar-Mucci, fraud platform lead at Verif. "Businesses and policymakers in the US need to urgently close this awareness gap, as well as invest in automated verification technologies that can catch what humans simply cannot."
The gap in awareness of deepfakes in the US is wider than expected
The United States may be the global center of generative AI development, but American consumers are the least familiar with deepfakes of the three markets surveyed. Only 63% of US adults are familiar with the term, compared to 74% in the UK and 67% in Brazil.
“There’s a paradox at play,” says Bondar-Mucci. “The U.S. is the global epicenter of AI development, yet American consumers are the least familiar with one of its most dangerous byproducts. Historically, consumers have had a high baseline of trust in digital content, leaving the conversation about fraud focused more on data privacy than content authenticity. The problem is that low awareness doesn’t reduce the risk, but rather increases it. If you don’t know what a deepfake is, your chances of stopping. And there’s very little chance of verifying whether you’ve encountered it.”
Detecting human deepfakes is little better than flipping a coin
In practice, the randomness that characterizes a consumer’s ability to distinguish between real and fake is evident in the ways people assess different types of content. Assessing video content proved particularly difficult, with fake videos often identified as authentic and genuine videos often marked as fake. Even in side-by-side comparisons, respondents split their judgments almost evenly, another indication that visual inspection alone is no longer a reliable method for confirming authenticity.
Overconfidence in detecting deepfakes creates a dangerous vulnerability
Nearly half of US respondents say they are confident in their ability to identify deepfakes, but this confidence far exceeds actual performance, indicating that self-assessment is effectively meaningless.
Within that population, there is that small but high-risk group: about 7% of users who are wrong, yet are overconfident in their ability and rarely verify questionable content.
“This confidence-competence gap creates a false sense of security that fraudsters take advantage of,” says Bondar-Mucci. “When people become confident that they can’t be fooled, they stop looking for signals. That’s when they are most vulnerable, whether it’s a synthetic identity used in financial fraud or a fabricated video designed to manipulate trust.”
For businesses, the implication is clear: any organization that still relies on manual review processes or customer self-verification is directly inheriting this vulnerability. Human judgment is an increasingly unreliable security measure, and verification needs to be built into systems by default. This means being automated, technology-based, and not relying on the end user’s self-assessment of their ability to distinguish real from fake.
Americans are concerned about deepfakes but trust platforms to handle them
Concern about deepfakes is high across the US, with 79% of respondents reporting that they are very, very concerned about personal fraud and impersonation.
The US is different from other markets where this concern is directed. Americans are more likely than UK or Brazilian respondents to rely on social media platforms and digital services to identify and manage AI-generated content. That delegation of responsibility can reduce individual vigilance at precisely the moment when the threat is heightened.
“We are seeing deepfake videos deployed to bypass the synthetic identities and basic verification checks used to open fraudulent accounts and authorize transactions,” he explains. “What makes this particularly urgent is the combination of great concern with relatively high platform trust. The gap between perceived and actual security is exactly where fraud thrives.”
The business case for automated identity verification has never been stronger
The gap between what Americans believe they can detect and what they actually can do is not a knowledge problem that awareness campaigns will solve, but rather a design flaw in any system that places the burden of identity verification on unaided human judgment.
The effective response is not to remove humans from the verification loop, but to stop assigning them tasks that human perception can no longer perform reliably. Organizations that rely on manual review processes or customer self-verification are incorporating this vulnerability into their operations.
The alternative is automated, AI-powered identity verification that operates at the point of interaction, detects synthetic media before human judgment is required, and does not rely on the end user’s ability to differentiate between genuine and fake.
“Seeing is no longer believing,” says Bondar-Mucci. “Companies that build verification infrastructure around that reality, rather than around the assumption that it will be otherwise, are best positioned to maintain customer trust as the synthetic media landscape continues to evolve.”
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