AI Image Recognition Market - Growth, Trends, COVID-19 Impact, and Forecasts (2022 - 2027)

Market Overview

The AI Image Recognition Market estimated value was USD 1695.93 million in 2020 and is expected to reach a value of USD 5161.04 million by 2026, registering a CAGR of 24.82% during the forecast period (2021 - 2026). 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.

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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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