The global AI in image recognition market is estimated to witness a robust growth rate of over 22.3% over the period of 2022–2028. The substantial rise in the value of global AI in the image recognition market is driven by its potential application in a wide range of industries such as automotive, banking, financial services and insurance (BFSI), healthcare, security, and retail. AI-based image recognition software has been considerably used in the BFSI industry to provide a substantial level of protection to customers.
Major AI applications in the BFSI industry include personalization, fraud detection, and compliance. Recent ground-breaking developments in big data analytics, cloud computing, social networks, natural language processing (NLP), and machine learning significantly impact AI in the image recognition industry. Social media platforms, such as Facebook and Instagram, use big data to keep track of all the information. Image recognition allows social media platforms to analyze images and detect several objects, logos, and faces used for authentication and other security purposes.
In addition, image recognition has a significant role in self-driving cars. AI-based technology is offering new avenues for image recognition capabilities, which is acting as a vital driving factor for the growth of the market.
BFSI industry is dominating the global market whereas the automobile is gaining momentum significantly
The BFSI industry has been a major benefiter of AI, with firms in the industry relying on technology for a diverse range of applications. Facial recognition is one of the numerous ways banks can increase efficiency and accessibility. Many tech giants such as Apple and Microsoft are offering their services to the banking and financial industry. For instance, US-based banks such as Chase, HSBC, and the United Services Automobile Association (USAA) are using FaceID offered by Apple, which allows customers to securely log into their mobile banking apps.
Moreover, Google Cloud exclaimed that it is seeing the financial services sector test face recognition as a part of multi-factor authentication for ATM withdrawals, mobile banking enrollment, and mobile account access and transactions. With AI-powered automation, labor-intensive work such as documentation, compliance reporting, and new customer onboarding communications can become highly efficient and accurate.
Further, the increased adoption of AI in image recognition in automobiles can be attributed to rapid technological advancements in GPS systems, sensor systems; computer power; digital mapping, and other applications. Besides, it is self-driving and automated cars that are powering image recognition in automotive; also, owing to several advantages and benefits of image recognition, such as driverless car functions that are not achievable by humans, is fostering the AI in image recognition.
Global AI in Image Recognition Market: Regional Outlook
North America is leading the global market on account of factors such as increased R&D activities and high expenditure by the government as well as private organizations in AI technology. North America has a well-developed ICT infrastructure and has witnessed the huge adoption of a large number of connected devices in recent years. Moreover, high internet penetration across the economies of the region is one of the major factors that is augmenting market growth in North America.
Further, with the growing advances in technologies across the economies of Asia-Pacific, the adoption of AI in image recognition technologies is anticipated to grow significantly over the forecast period. For instance, in China, the schools are adopting high-tech gates that are fully leveraged with facial-recognition cameras to keep track of their students. High-tech barriers AI-based facial-recognition cameras are installed to build smart campuses and improve the security of schools.
Additionally, the Europe region is observing a significant rise in the market value in recent years due to rising internet penetration coupled with supportive government policies and growing activities by major industry players. One of the prominent companies is Cortexica Vision Systems, which offers an AI-based platform that provides video analytics and camera processing solutions for the retail sectors across Europe. In February 2019, Cortexica introduced that it had launched an app that allows users to demo AI-powered visual search and image recognition technology. The company’s visual commerce app offers users to interact with a wide range of retail solutions to get an idea of how the app is working.
Competition Landscape and Key Market Developments
The global AI in image recognition market is fragmented in nature with the presence of various players operating in the market. Some of the prominent players that contribute significantly to the market growth include Amazon Web Services Inc. (Amazon.com Inc.), Alphabet Inc. (Google LLC), Clarifai Inc., IBM Corp., Intel Corp., Micron Technologies Inc., Microsoft Corp., Nvidia Corp., Qualcomm Corp., Samsung Electronics Co., Ltd., Xilinx Inc., SAP SE, NEC Corp., Oracle Corp., and Huawei Technologies Co., Ltd. among others. These players adopt various strategies in order to reinforce their market share and gain a competitive edge over other competitors in the market. Acquisitions and product launches are among the key strategies adopted by major industry players. For instance,
- In May 2020, a hand-wash movement recognition tool named “Actlyzer” was developed by Fuji Laboratories and Fujitsu Research and Development Center. Actlyzer utilizes advanced technologies such as AI and ML capabilities to identify complex hand wash movements from video data, which ensures proper, standardized hand washing practices.
- In May 2020, Microsoft Corp. announced a collaboration with Sony Corp. with an aim to develop software tools to enable simplified sharing of and access to their mutual customer data. These tools would be integrated into AI-powered smart cameras and video analytics by companies through leveraging Microsoft’s Azure AI and Sony’s IMX500 intelligent vision sensor.
Key Market Segmentation
RationalStat has segmented the global AI in the image recognition market on the basis of component, technology, application, end-user, and region.
- By Component
- Hardware
- Software
- Services
- By Technology
- Code Recognition
- Facial Recognition
- Object Recognition
- Pattern Recognition
- Others (Optical Character Recognition)
- By Application
- Scanning and Imaging
- Security and Surveillance
- Image Search
- Augmented Reality
- Others (Marketing and Advertising)
- By End-User
- Banking, Financial Services, and Insurance (BFSI)
- Automobile
- Healthcare
- Retail
- Gaming
- Security
- Others (Media & Entertainment)
- By Region
- North America
- US
- Canada
- Latin America
- Brazil
- Mexico
- Rest of Latin America
- Western Europe
- Germany
- UK
- France
- Spain
- Italy
- Benelux
- Nordic
- Rest of Western Europe
- Eastern Europe
- Russia
- Poland
- Rest of Eastern Europe
- Asia Pacific
- China
- Japan
- India
- South Korea
- Australia
- ASEAN (Indonesia, Vietnam, Malaysia, etc.)
- Rest of Asia Pacific
- Middle East & Africa
- GCC
- South Africa
- Turkey
- Rest of the Middle East & Africa
- North America
Research Methodology
RationalStat has developed a state-of-the-art research methodology to crunch numbers and provide the best possible real-time insights to clients. We combine a varied range of industry experience, data analytics, and experts’ viewpoint to create a research methodology for market sizing and forecasting.
RationalStat combines a mix of secondary sources as well as primary research to assess the market size and develop a forecast. Key steps involved in accurately deriving the market numbers are:
- Defining the problem by understanding the type of market and data required by the client.
- Data gathering and collection through relevant paid databases, publicly available sources, company reports, annual reports, surveys, and interviews.
- Formulating a hypothesis to create market numbers, forecast, influencing factors, and their relevance.
- Evaluating and analyzing the data by referring to data sources utilized and leveraged.
- Validating, interpreting, and finalizing the data by combining the details gathered from primary and secondary sources with the help of experienced analysts.
Secondary Sources
- Annual reports, company filings, investor presentations, product catalogs, industry associations, and company documents
- Industry and market-related documents available in the public domain
- Paid database including Bloomberg, Factiva, S&P Capital IQ, FactSet, Refinitiv Eikon, ICIS, EUWID, Thomson Reuters, among others
- Whitepapers, research papers, and industry blogs.
Why Buy this Report?
The report is intended for AI in image recognition service providers, consumer electronics manufacturers, government organizations, market educational organizations, regulatory agencies, and market research firms, among others. The report provides an in-depth analysis of market size, consumption pattern, ongoing market trends and challenges, and future market opportunities. The report will serve as a source for a 360-degree analysis of the market thoroughly delivering insights to clients to find the right answers to their business questions.
Frequently Asked Questions (FAQs)
The expected CAGR of the global AI in image recognition market is 22.3% during 2022-2028.
The leading region in the global AI in image recognition market is APAC in 2022.
The market value of the global AI in image recognition market is expected to reach US$ 70 – 75 billion.
Soaring application areas in a wide range of sectors, such as automotive, banking, financial services and insurance (BFSI), healthcare, security, and retail.
Leading companies operating in the global AI in image recognition market are Amazon Web Services Inc. (Amazon.com Inc.), Alphabet Inc. (Google LLC), Clarifai Inc., IBM Corp., Intel Corp..