Deepfake Statistics By Market Size, Overview And Impacts (2026)

Introduction

Deepfake Statistics: Deepfakes are fake images, videos, or audio made using smart computer programs. They can make people appear to say or do things they never did. This technology uses artificial intelligence to look very real, which makes it both exciting and dangerous. Deepfakes are used in movies, games, and social media for fun and creativity. However, they can also spread false information, harm reputations, and invade privacy. As deepfakes become easier to create, it is important to stay aware and think carefully about what we see online. Understanding deepfakes helps us stay safe and make better decisions in the digital world.

Editor’s Choice

1. In 2026, the global deepfake detection market is expected to reach USD 168.7 million.
2. The global Deepfake Technology market is projected to be worth USD 7.44 billion.
3. The global DeepFake AI market size is USD 1,591.5 million, combining both software and services.
4. Around 25% of business leaders have little to no familiarity with deepfake technology.
5. 43% of deepfake targets are the general public, while 36% are politicians and 21% are celebrities.
6. Fraud is the most common type of harmful deepfake use across all formats, with 85 video cases, 53 audio cases, and 26 image cases.
7. Non-consensual explicit content is the most common use of deepfakes, accounting for about 60 cases in the dataset.
8. The global deepfake video market is projected to reach USD 1.67 billion by 2026.
9. Fraud is the most common type of harmful deepfake use across all formats, with 85 video cases, 53 audio cases, and 26 image cases.
10. North America accounts for 39% of global incidents, while Europe accounts for 26%.
11. As of 2026, financial services is the most targeted sector, at 28%, with deepfake voice calls impersonating executives.
12. Only 0.1% of people correctly identified all deepfake content in controlled tests.
13. About 25% of people verify information using other sources, while 11% check source credibility, and 29% take no action.
14. Businesses face an average loss of about USD 440k-USD 500k per incident.
15. News and media is the most impacted sector globally, with Mexico at 48%, above the global average of 33%, while the UAE is lower at 23%.

Key Takeaways

• According to Market.us, more than 1,500 finance professionals from the United States and the United Kingdom, 53% of businesses reported that deepfake scams have targeted them.
• Around 85% of respondents view deepfake technology as an existential threat to their companies.
• 70% lack confidence in identifying cloned voices, while 40% would still help their spouse after receiving an urgent voicemail request.
• Surfshark reported that in Q1 2025, deepfake incidents increased by 19% compared with full-year 2024.
• In the first half of 2025, deepfake-related fraud caused financial losses of approximately USD 547.2 million.
• By 2026, around 30% of enterprises are expected to consider standalone identity verification and authentication systems, as per DeepStrike.

Deepfake Detection Market Size

(Source: market.us)

• In 2026, the global deepfake detection market is expected to reach USD 249 million.
• By 2034, the market is forecast to reach USD 5,609.3 million.
• This implies a compound annual growth rate of 47.6% from 2025 to 2034.

Deepfake Technology Market Statistics

• According to research estimates by Coherent Market Insight, the global Deepfake Technology market is projected to be worth USD 7.44 billion in 2026.
• The market is expected to grow significantly and is forecasted to reach USD 32.58 billion by 2033.
• The market is anticipated to grow at a compound annual growth rate of 27.9% between 2026 and 2033.

By Components

(Reference: coherentmarketinsights.com)

• The software segment dominates the global Deepfake Technology market, accounting for 69.4% of the total market value.
• The services segment contributes the remaining 30.6% of the market.

By Technology

(Reference: coherentmarketinsights.com)

• Generative Adversarial Networks hold the largest share, accounting for 59.2% of the market.
• Based on technology, diffusion models make up 14.5%, autoencoders 10.3%, transformers 9.1%, and natural language processing technologies 6.9%.

Global Deepfake AI Statistics

(Source: market.us)

• In 2026, the global DeepFake AI market size is USD 1,591.5 million, combining both software and services.
• By 2033, the market is forecast to reach USD 18,989.4 million, with a compound annual growth rate of 42.5% from 2024 to 2033.

Deepfake Fraud Statistics

• According to security.org, 25% of business leaders have little to no familiarity with deepfake technology.
• Around 31% of executives underestimate the risk of deepfakes, while 32% lack confidence in employees’ ability to detect or respond to such threats.
• More than 50% of business leaders report that no employees receive training on identifying or mitigating deepfake attacks.
• About 10% of executives confirm direct exposure to deepfake-based threats, while another 10% are unsure if their organizations have been targeted.
• Deepfake-related fraud has seen a 10x increase in incidents in recent years, with a 1,740% growth in North America.
• Industry exposure remains concentrated, with 88% of cases in the crypto sector.
• In fintech, deepfake incidents have increased by around 700%.

By Targets

(Source: infogram.com)

• 43% of deepfake targets are the general public, while 36% are politicians and 21% are celebrities.
• In fraud-related deepfake activity, 41% involve the general public, 38% involve celebrities, and 14% involve politicians.
• For explicit content categories, 39% of targets are the general public, 26% are celebrities, and 9% are politicians.
• In miscellaneous deepfake cases, 33% involve celebrities, 22% involve the general public.
• In political deepfake content, politicians are the primary targets, accounting for 76% of all cases.
• Among well-known people, the reported targets include Donald Trump (25 cases), Joe Biden (20), Elon Musk (20), Taylor Swift (11), Kamala Harris (6), Volodymyr Zelenskyy (4), Tom Hanks (3), Brad Pitt (2), Emma Watson (2), and Kanye West (2).

Deepfake Media Formats Overview

Deepfake Incident Distribution

(Source: infogram.com)

• Fraud is the most common type of harmful deepfake use across all formats, with 85 video cases, 53 audio cases, and 26 image cases.
• Explicit content is the second most frequent category, with 60 video cases and 77 image cases.
• Political deepfakes are also important, with 74 video cases, 40 audio cases, and 15 image cases.
• Miscellaneous deepfake cases are relatively lower but still present, including 41 video cases, 24 audio cases, and 14 image cases.
• The general public is the most targeted group, facing 102 video cases, 74 image cases, and 47 audio cases, showing widespread exposure.
• Politicians are nearly equally targeted, with 101 video cases, 47 audio cases, and 29 image cases.
• Celebrities are less targeted compared to others but still affected, with 57 video cases, 29 image cases, and 23 audio cases.

Geographical Distribution Of Deepfake Attacks

• According to Zero Threat, North America accounts for 39% of global incidents, while Europe accounts for 26%.
• Asia-Pacific, Latin America, and the Middle East & Africa account for smaller but growing shares, with 21%, 9%, and 5% of incidents, respectively.

Industries Most Affected by Deepfake Attacks and AI Phishing

• As of 2026, financial services is the most targeted sector, at 28%, with deepfake voice calls impersonating executives, AI-based invoice fraud, and business email compromise scams.
• Meanwhile, healthcare is responsible for 19% of attacks, the government and the public sector account for 17%, legal and professional services represent 15%, and retail and e-commerce contribute 12%.

Primary Purpose Of Deepfakes

(Reference: amazonaws.com)

• The most common use of deepfakes is the creation of non-consensual explicit content, with about 60 cases in the dataset. Next, scams and fraud come second, with around 45 cases linked to cheating or financial tricks.
• Political manipulation is also seen, with about 35 cases, while misinformation (false or misleading content) appears in around 30 cases.
• Impersonation, where someone’s identity is copied or faked, has about 25 cases.
• The remaining 15 cases fall under different or mixed purposes.

Consumer Openness To Deepfake Ads By Generation

Deepfake Marketing Statistics

• According to Amra and Elma, the global deepfake video market is projected to reach USD 1.67 billion by 2026.
• Around 74% of marketers report higher engagement from deepfake content.
• More than 2.1 million deepfake videos are already publicly indexed online, indicating large-scale content growth.
• About 53% of consumers cannot correctly identify deepfake videos.
• Nearly 51% of Gen Z audiences are open to deepfake advertisements.
• Around 83% of brands use deepfakes for localization.
• Production costs for deepfake content have fallen by 75%.
• 47% of brands have tested AI-generated spokespersons in advertising campaigns.
• Nearly 79% of consumers want deepfake ads to be clearly labeled for transparency.
• Deepfake ads deliver 38% higher ad recall than traditional videos.
• Only 19% of deepfake ads disclose their use of AI.
• About 67% higher share rates are recorded for AI-generated video ads, improving virality.

Deepfake Detection Ability

• A report published by Programs further stated that only 0.1% of people correctly identified all deepfake content in controlled tests.
• Around 29% of people say they feel confident in identifying deepfakes, while 21% admit low confidence in their ability to do so.
• People correctly identify AI-generated voices 60% of the time, while deepfake audio is detected 73% of the time in some studies.
• Deepfake images are usually correctly identified about 86% of the time, but videos are much harder and are only correctly identified about 18.75% of the time.
• About 68% of deepfake content looks so real that people can’t easily tell it apart, and tools used to detect fake voices only work about 38.2% of the time.

Deepfake Risks, Awareness, And Response

• According to iProov, about 25% of people verify information using other sources, while 11% check source credibility, and 29% take no action.
• Moreover, 48% do not know how to report deepfakes.
• Around 22% of people have never heard of deepfakes, including 30% aged 55-64 and 39% aged 65+.
• Only 25% of executives are highly familiar with deepfake technology, while 53% of U.S. adults share voice data weekly.
• About 46 U.S. states have deepfake laws, with 169 laws passed since 2022 and 146 bills introduced in 2025 alone.
• Deepfake videos cost USD 300-20,000 per minute, but 91% can be made for USD 50 in 3.2 hours.
• Only 3 seconds of audio can create an 85% accurate voice clone.
• About 43% of finance professionals targeted by deepfake fraud fall victim, and 87% of professionals would act on CEO/CFO payment requests.

How Individuals Respond To Deepfakes

(Source: programs.com)

• 25% people check other sources, 11% critically analyze sources, 75% fail to verify information correctly in online content.
• Around 29% take no action when encountering deepfakes, and 48% do not know how to report them.

Impacts Of Deepfake Threats

• Deepfake fraud has rapidly increased from a few cases per month to hundreds globally.
• According to edtsure, businesses face an average loss of about USD 440k-USD 500k per incident, and many firms have already been targeted or affected.
• A Hong Kong case involved a fake video meeting that caused losses of about USD 25.6 million through executive impersonation.
• Australian reports show widespread exposure to scams, with around 20% of businesses targeted and multi-million-dollar losses linked to deepfake-driven fraud incidents.
• 25% fintech firms lose over USD 1 million from AI fraud attacks.
• Deepfakes are detected in 80% of images, 64% of videos, and 48% of audio; only 22% are reported.
• 42% of firms are confident in detecting deepfakes; 62% want alert systems; pauses boost detection by 8%, according to PwC’s study.

Key Areas Most Impacted By Deepfakes

• According to McAfee, news and media is the most impacted sector globally, with Mexico at 48%, above the global average of 33%, while the UAE is lower at 23% Legal and judicial systems face rising risks, with the UAE at 36%, the USA at 35%, and a global average of 32%.
• Political elections and campaigns are highly vulnerable, with Germany reporting a 34% impact.
• Personal relationships and social media are also significantly affected, with Germany at 34%, the UAE at 28%, and a global average of 26% Healthcare and medical advice are the least impacted globally, at 24%, but Singapore, at 35%, and Mexico, at 28%, show higher regional vulnerability.
• Healthcare and medical advice remain the least impacted globally, at 24%, followed by Singapore (35%) and Mexico (28%).

Conclusion

In conclusion, deepfakes are powerful but risky. They can be fun and useful, but they can also spread lies and hurt people. As this technology grows, we must use it carefully. Always check what you see online and do not trust everything. Rules and awareness can help stop misuse. If we stay smart and alert, we can enjoy the good side of deepfakes and avoid the harm.

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