AI Image Recognition Market - Growth, Trends, and Forecast (2020 - 2025)
The AI Image Recognition Market is segmented by Type (Hardware, Software, Services), End-user Vertical (Automotive, BFSI, Healthcare), and Geography.
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Scope of the Report
Key Market Trends
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The AI Image Recognition Market estimated value was USD 1695.93 million in 2019 and is expected to reach a value of USD 622.03 million by 2025, registering a CAGR of 24.82% during the forecast period (2020 - 2025). Image recognition can be applied across various fields, such as vehicular safety, advertising, security and surveillance, biometric scanning machines, pedestrian recognition, and E-commerce, with various applications in multiple domains, the market is expected to witness strong growth during the forecast period.
The adoption of artificial intelligence (AI) technology is rising, owing to its ability to enhance and automate operations and enrich the user experience. Governments are also focusing on increasing their AI capabilities to revolutionize various sectors, from healthcare to transport. EU has committed to invest EUR 1.5 billion in AI to catch up with the United States and Asia.
With AI becoming the core of many technology-based applications, the investments in the sector are growing. Image recognition stands as one of the standard features for many AI-related applications. Thus, the market is expected to leverage the fast-growing technology and expand in the coming years.
According to Eirik Thorsnes at UNI Research in Bergen, Norway, “There has been a tremendous development in recent years, and we are now surpassing the human level in terms of image recognition and analysis. Computers never get tired of looking at near-identical images and may be capable of noticing even the tiniest nuances that we humans cannot see. In addition, as it gets easier to analyze large volumes of images and video, many processes in society can be improved and optimized,"
Scope of the Report
Image recognition is the ability of the software to identify places, objects, people, writing and actions in images. Computers can use machine vision technologies in combination with a camera and artificial intelligence software to achieve image recognition. Image recognition is used to perform a large number of machine-based visual tasks, such as labeling the content of images with meta tags, performing image content search, guiding autonomous robots and self-driving cars, and in accident avoidance systems.
By End-user Vertical
Other End-user Verticals
Middle East & Africa
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Key Market Trends
Banking Sector is Expected to Witness Significant Growth
Images are real and extensive, and unlike other forms of data, they also cannot be forged easily. These characteristics make the images, repositories of big data, and hence, exploiting such valuable data can be a great source of information for banks and financial institutions.
The BFSI industry has been a major benefactor of AI, with firms in the industry relying on the technology for a diverse range of applications, like staying competitive in a continuously evolving market, personalizing communication with customers, and improving the productivity drastically through automation of monotonous tasks (which are major tasks due to the conventional infrastructure in a number of old school financial institutions).
Facebook can now identify and map 98% of its images correctly to the right person. Imaging technology is being used for identifying and removing fake social accounts. Such image-based fake identification has immense potential in enriching credit-scoring and risk-modeling of banks. Images could also be used by underwriters in risk assessment and fraud identification.
With image processing and recognition becoming an important application of AI across various industries, it is thus expected to witness positive growth over the forecast period.
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Asia-Pacific Expected to Witness Rapid Growth
Image recognition solutions have been gaining prominence incessantly in Asia-Pacific, particularly to cater to the growing need for security solutions due to the advent of the smart homes and smart city initiatives in the developing economies in the region.
With the growing e-commerce segment in the retail industry in the recent past in the region, vendors in the market are investing majorly in the image recognition technologies to offer an enhanced digital experience to consumers.
Company preferences for different platforms vary greatly in this region, with AI vendors in China preferring Tensor Flow or Caffe, whereas companies in Singapore prefer Microsoft CNTK, and companies in Japan prefer Chainer Software, to support AI technologies. The ease of availability of such platforms has created huge potential opportunities for vendors to leverage these advanced technologies to develop tools for critical business needs.
Artificial intelligence offers the region massive opportunities for growth, innovation, and productivity, with the potential to address key issues in the social environment within the fast-developing economies.
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The AI image recognition market is highly competitive owing to the presence of many small and large players providing service and solutions in domestic as well as in the international market. The market appears to be fragmented. The key players operating in this market are innovating their products on a regular basis and this is leading them to gain sustainable competitive advantage. Due to this, there is always a high competition between players to innovate and introduce new products.
March 2019 - Amazon Rekognition launched enhanced face analysis. This is the fifth model update overall since the service launched. Face analysis generates rich metadata about detected faces in the form of gender, age range, emotions, attributes such as ‘Smile’, ‘Eyeglasses’ and ‘Beard’, face pose, face image quality, and face landmarks.
April 2019 - Google partnered with Atos in opening its new AI laboratory in Paris. The facility will enable the customers and private and public organizations to identify use cases for AI, co-create and prototype workable AI solutions, and drive adoption of the rapidly developing technology.