The deepfake AI detection market size is expected to reach US$ 3,463.82 million by 2031 from US$ 213.24 million in 2023. The market is estimated to record a CAGR of 41.7% from 2023 to 2031. The emergence of real-time deepfake AI detection solutions and deepfake AI detection with user behavioral elements are likely to bring new market trends.
In recent years, there has been a growing demand for deepfake AI detection software owing to the rise in cyber-attacks through deepfake content. Business processes are becoming increasingly dependent on the cloud, artificial intelligence, and advanced automation systems. Thus, the rising utilization of artificial intelligence across various sectors is driving the deepfake AI detection market. In addition, deepfake AI detection software helps provide better insights into the detection of deepfake content and recognize fraud associated with it. Furthermore, the increase in penetration of mobile devices, the growth of the media and entertainment industry, and the rise in social content across the globe are a few other key factors contributing to the market growth.
Deepfake is a form of artificial intelligence that can create convincing false images, sounds, and videos. The term "deepfake" combines the deep learning concept with something fake. Deepfake compiles fake images and sounds and stitches them together using machine learning algorithms. This creates people and events that do not exist or actually did not happen. Deepfake technology is primarily used for criminal purposes, such as misleading the public by spreading false information or propaganda. Detection technologies aim to identify counterfeit media without having to compare it to the original, unaltered media. These advanced technologies typically use a form of AI known as machine learning. The models are trained on data from known real and fake media. Methods include searching for facial recognition, evidence of deepfake creation, and color anomalies.
Deepfake AI can be used in positive and negative ways. Key utilization of deepfake AI by bad actors or scammers include election interference, blackmail, bullying, harassment, fake news, and financial frauds and scams. The huge growth in deepfake frauds is hitting people and businesses across the globe. For instance, according to Onfido's Identity Fraud Report 2023, identity fraud attacks showed a 31x increase in deepfake fraud from 2022 to 2023. In addition, as per the identity fraud report (2023) from Sum and Substance Ltd., the rate of identity fraud increased from 1.1% in 2021 to 2.0% in 2023. In Asia Pacific, deepfake attacks increased by 1530% from 2022 to 2023, with Vietnam, the Philippines, and Japan among the leaders.
North America registered the highest number of deepfake attacks detected globally across all industries, with a 1740% deepfake surge from 2022 to 2023. As per the report by Sum and Substance Ltd, social media, professional services, healthcare, digital transportation, and video gaming were the top five industries mostly affected by identity fraud and deepfake attacks in 2023. Deepfakes can affect people in many ways such as deepfake content, videos, images, and others. Regula's survey data in 2024 shows a significant rise in the prevalence of video deepfakes, with a 20% increase in companies reporting incidents compared to 2022. Approximately 29% of fraud decision-makers across Australia, France, Germany, Mexico, Turkey, the UAE, the UK, and the US reported encountering video deepfake fraud in 2022. Thus, the rising threat of deepfakes attacks globally demands a greater need for robust deepfake detection solutions.
With the number of deepfakes growing, deepfake detection software is becoming increasingly popular to protect against the harmful effects of fake videos and audio. Researchers are developing new methods for detecting deepfakes, such as AI models that detect color anomalies. According to recent studies, existing detection methods and models may not be able to accurately identify deepfakes in real-world scenarios. For example, accuracy may decrease if lighting conditions, facial expressions, or video or audio quality differ from the data used to train the recognition model or if the deepfake was created using a method other than that used in the training data. Additionally, future advances in deepfake generation are expected to eliminate hallmarks of current deepfake, such as abnormal eye blinking such as advanced machine learning, multimodal approach, and others. Therefore, technological advancements in deepfake AI detection tools and the rise in investments to develop advanced deepfake AI detection technologies are expected to create opportunities for the key companies operating in the market from 2023 to 2031.
Key segments that contributed to the derivation of the deepfake AI detection market analysis are component, deployment, enterprise size, and vertical.
The regional trends and factors influencing the Deepfake AI Detection Market throughout the forecast period have been thoroughly explained by the analysts at Insight Partners. This section also discusses Deepfake AI Detection Market segments and geography across North America, Europe, Asia Pacific, Middle East and Africa, and South and Central America.
| Report Attribute | Details |
|---|---|
| Market size in 2023 | US$ 213.24 Million |
| Market Size by 2031 | US$ 3,463.82 Million |
| Global CAGR (2023 - 2031) | 41.7% |
| Historical Data | 2021-2022 |
| Forecast period | 2024-2031 |
| Segments Covered |
By Component
|
| Regions and Countries Covered | North America
|
| Market leaders and key company profiles |
The Deepfake AI Detection Market market is growing rapidly, driven by increasing end-user demand due to factors such as evolving consumer preferences, technological advancements, and greater awareness of the product's benefits. As demand rises, businesses are expanding their offerings, innovating to meet consumer needs, and capitalizing on emerging trends, which further fuels market growth.
Market players density refers to the distribution of firms or companies operating within a particular market or industry. It indicates how many competitors (market players) are present in a given market space relative to its size or total market value.
Major Companies operating in the Deepfake AI Detection Market are:
Disclaimer: The companies listed above are not ranked in any particular order.
The deepfake AI detection market is evaluated by gathering qualitative and quantitative data post primary and secondary research, which includes important corporate publications, association data, and databases. A few of the developments in the deepfake AI detection market are listed below:
(Source: Microsoft, Press Release, May 2024)
(Source: BioID, Press Release, March 2024)
The "Deepfake AI Detection Market Size and Forecast (2021–2031)" provides a detailed analysis of the market covering the areas mentioned below:
The List of Companies - Deepfake AI Detection Market
The deepfake AI detection market was estimated to be US$ 213.24 million in 2023 and is expected to grow at a CAGR of 41.7 % during the forecast period 2023 – 2031.
Increasing number of deepfake frauds and scams, increased use of ai in media and entertainment, and stringent government regulations are the major factors that propel the deepfake AI detection market.
Emergence of real-time deepfake ai detection solutions and deepfake ai detection with user behavioral elements, which is anticipated to play a significant role in the deepfake AI detection market in the coming years.
The incremental growth expected to be recorded for the deepfake AI detection market during the forecast period is US$ 3,250.61 million.
The deepfake AI detection market is expected to reach US$ 3463.85 million by 2031.
The key players holding majority shares in the deepfake AI detection market are Sightengine, Clarity, FaceOnLive, Buster.Ai, SpoofSense, Facia.ai, Kroop AI, Reality Defender Inc., Au10tix, Microsoft, BioID, Sensity B.V., ValidSoft, Sentinel, HyperVerge Inc., DuckDuckGoose, McAfee Corp, deepfakedetector.ai, Attestiv Inc., and Intel Corporation.