Global Artificial Intelligence (AI) Image Recognition Market 2016-2027 by Offering, Function, Industry Vertical, and Region: Trend Forecast and Growth Opportunity

Global Artificial Intelligence (AI) Image Recognition Market 2016-2027 by Offering, Function, Industry Vertical, and Region: Trend Forecast and Growth Opportunity

Bonafide Trust 28-06-2022 160 Pages Figures : 82 Tables : 74
Region : Global Category : Manufacturing & Industry Construction & Building Materials

Global AI image recognition market will reach $8,898.2 million by 2026, growing by 26.9% annually over 2020-2026 owing to the rising need for AI-enabled image recognition technology amid the COVID-19 pandemic. The development of artificial intelligence and machine learning is driving industry and business model transformations. Al is driving numerous applications including computer vision, pattern recognition, machine vision, and many more. Static image detection, recognition, classification, and tagging are projected to be some of the top revenue-generating applications of Al across industries. Additionally, Al-driven autonomous machine vision vehicles are also stimulating demand for image detection technologies. Apart from this, the increasing popularity of Al-based visual search engines for object recognition is anticipated to fuel product demand in the coming years. Several Al-based healthcare applications such as modern radiology interpretation and chronic diagnosis are enhancing the value of this market. Thus, the development of artificial intelligence-based applications is simultaneously escalating the demand for the product. The development of smart cities and buildings is stoking the demand for Al-supported security camera networks for robust surveillance. Many public as well as private sector entities are adopting face recognition technology for surveillance purposes. The IT industry is majorly adopting face recognition-based identification systems for authentication and staff attendance purposes. Besides this, face recognition technology is becoming essential for self service check-ups and border check-ups at airports. Furthermore, since database serves as the training material to image recognition solutions, open-source frameworks such as software libraries and software tools form the building blocks of the solution. It helps to prepare or train machines to learn from the images available in the database by providing different types of computer vision functions such as medical screening, obstacle detection in vehicles, and emotion & facial recognition, among others. Furthermore, the retail and e-commerce industries are evolving face recognition-based payment solutions, which are also gaining traction across the BFSI industry. In October 2019, for instance, Google LLC updated its Google Pay Android mobile application to support facial recognition along with fingerprint recognition technology. Additionally, face recognition tools are also applicable in the fields of digital marketing, healthcare, social networks, voting, and criminal investigations. The expanding application areas of facial recognition technology are, therefore, fueling the growth of this market. Also the automated image recognition system plays a crucial role in computer vision, which is used to identify or detect an image or an attribute in digital images or videos. It enables users to gather and analyze data in real-time. The data is collected in high dimension and produces numerical or symbolic information. As part of image recognition, computer vision enables object recognition, event detection, image reconstruction, learning, and video tracking. The cloud based AI imaging process is gaining market share due to lower investment requirement. This growth in the cloud-based market is attributed to its increased adoption in verticals where centralized monitoring is required, such as Banking, Financial Services, and Insurance (BFSI), media and entertainment, and government.

In spite of image recognition gaining traction across the public and private sectors, with the growing acceptance of Al and computer vision technology, federal and local regulations are hampering the market growth. For example, in September 2020, Portland, Oregon banned the use of facial recognition technology by various city departments including public-facing businesses and local police. Face recognition technology has to become a common tool in the past several years for ensuring public safety and surveillance. However, this technology has been banned in several regions across the United States, Europe, and Asia-Pacific owing to residential privacy concerns. Such government policies are, as a result, hampering the demand for image identification solutions.

Impact of COVID-19
The COVID-19 pandemic is anticipated to have a mixed impact on the image recognition market growth. On one hand, the pandemic has accelerated the adoption of AI-based automation technologies among businesses, with AI also aiding the fight against the pandemic; on the other hand, growing misuse of facial recognition is pushing lawmakers to ban the deployment of such tools, which is limiting the growth of the market. The novel coronavirus pandemic has transformed the world by accelerating digitization trends. All economic sectors have been forced to deploy advanced technologies to transform their traditional business models. The pandemic has led numerous organizations to deploy advanced recognition technologies such as facial recognition for supporting social distancing during the time of the pandemic. Several banking and financial organizations are developing face recognition-based mobile payment services. For instance, in June 2020, Caixa Bank, S.A. started a project to roll-out a facial recognition technology at over 100 ATMs across Spain to offer touchless payment withdrawal services to ATM users. The drastic shift of businesses towards digitization is anticipated to boost the usage of image detection and recognition technology.

Highlighted with 82 tables and 74 figures, this 160-page report “Global Artificial Intelligence (AI) Image Recognition Market 2020-2026 by Offering, Function, Industry Vertical, and Region: Trend Forecast and Growth Opportunity” is based on a comprehensive research of the entire global AI image recognition market and all its sub-segments through extensively detailed classifications. Profound analysis and assessment are generated from premium primary and secondary information sources with inputs derived from industry professionals across the value chain. 

In-depth qualitative analyses include identification and investigation of the following aspects:
• Market Structure 
• Growth Drivers 
• Restraints and Challenges
• Emerging Product Trends & Market Opportunities
• Porter’s Fiver Forces

The trend and outlook of global market is forecast in optimistic, balanced, and conservative view by taking into account of COVID-19. The balanced (most likely) projection is used to quantify global AI image recognition market in every aspect of the classification from perspectives of Offering, Function, Industry Vertical, and Region. 

By Offering
     • Hardware
     • Software
     • Service

By Function

     • Biometrics Recognition
          • Facial Recognition
          • Hand and Fingerprint Scan
          • Eyes Recognition
          • Other Biometrics
     • Object Identification
By Industry Vertical
     • Automotive 
     • BFSI
     • Healthcare
     • Security
     • Retail
     • Other Industry Verticals

By Geography
     • APAC (Japan, China, South Korea, Australia, India, and Rest of APAC; Rest of APAC is further segmented into Malaysia, Singapore, Indonesia, Thailand, New Zealand, Vietnam, and Sri Lanka)
     • Europe (Germany, UK, France, Spain, Italy, Russia, Rest of Europe; Rest of Europe is further segmented into Belgium, Denmark, Austria, Norway, Sweden, The Netherlands, Poland, Czech Republic, Slovakia, Hungary, and Romania)
     • North America (U.S., Canada, and Mexico)
     • South America (Brazil, Chile, Argentina, Rest of South America)
     • RoW (Saudi Arabia, UAE, Egypt)

For each aforementioned region and country, detailed analysis and data for annual revenue are available for 2016-2027. The breakdown of all regional markets by country and split of key national markets by Offering, Function, and Industry Vertical over the forecast years are also included.

The report also covers current competitive scenario and the predicted trend; and profiles key vendors including market leaders and important emerging players.
Specifically, potential risks associated with investing in global AI image recognition market are assayed quantitatively and qualitatively through GMD’s Risk Assessment System. According to the risk analysis and evaluation, Critical Success Factors (CSFs) are generated as a guidance to help investors & stockholders identify emerging opportunities, manage and minimize the risks, develop appropriate business models, and make wise strategies and decisions.

Key Players (this may not be a complete list and extra companies can be added upon request): 
Aether, Inc., Amazon Web Services, Inc., Clarifai, Inc., Cortexica Vision Systems, Ltd., Cortica, Google LLC, IBM Corporation, Intel Corporation,  LPixel, Inc., Micron Technology, Inc., Microsoft Corporation,  Nvidia Corporation, Pixelab, Procter & Gamble Co., Qualcomm Corp., Samsung Electronics Co., Ltd., Softech, Ltd., Vee Technologies, Inc., Visenze, Webtunix, Xilinx Inc. 

(Please note: The report will be updated before delivery so that the latest historical year is the base year and the forecast covers at least 5 years over the base year.) 

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